This document provides an overview of change detection techniques for landcover using remote sensing data. It begins by discussing issues that can impact change detection accuracy, such as image acquisition parameters, viewing geometry, and radiometric correction. It then categorizes change detection techniques as either pre-classification or post-classification. Pre-classification techniques extract minimal change information, while post-classification techniques separate changes in more detail but may miss subtle within-class changes. Object-based techniques that segment images into objects before analysis are also discussed as a recent development.
A Review of Change Detection Techniques of LandCover Using Remote Sensing Dataiosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
The document summarizes seven categories of change detection techniques:
1. Algebra based approaches include image differencing, regression, ratioing, and change vector analysis. These methods are simple to implement but cannot provide complete change matrices.
2. Transformation techniques apply transformations like PCA and tasseled cap to images before change detection.
3. Classification based techniques perform post-classification comparison or combine classification with other algorithms.
4. Advanced models use techniques like spectral mixture analysis and biophysical parameters.
5. GIS and remote sensing are integrated in some methods.
6. Visual analysis relies on human interpretation of image differences.
7. Other techniques include measures of spatial dependence,
Using Remote Sensing Techniques For Monitoring Ecological Changes In Lakes: C...IJERA Editor
The ability to use remote sensing in studying lake ecology lies in the capability of satellite sensors to measure
the spectral reflectance of constituents in water bodies. This reflectance can be used to determine the
concentration of the constituents of the water column through mathematical relationships. This work identified a
simple linear equation for estimating suspended matter in Lake Naivasha with reflectance in Landsat7 ETM+
image. A R² = 0.94, n = 6 for suspended matter was obtained. Archive of Landsat imagery was used to
produce maps of suspended matter concentrations in the lake. The suspended matter concentrations at five
different locations in the lake over 30 year’s period were then estimated. It was therefore concluded that the
ecological changes Lake Naivasha is experiencing is the result of the high water abstraction and the effect of
climate change.
Tarımsal Toprak Haritalama'da Jeofizik MühendisliğiAli Osman Öncel
1) The document discusses a study evaluating the reliability and reproducibility of electromagnetic induction (EMI) data collection.
2) The study compared data from two identical EMI instruments, the calibration methods of different individuals, and variations in calibration height.
3) The results showed significant differences between instruments, calibrations, and heights. This demonstrates the need for standardization of EMI data collection procedures to ensure reliable and reproducible data.
Comparing canopy density measurement from UAV and hemispherical photography: ...IJECEIAES
UAV and hemispherical photography are common methods used in canopy density measurement. These two methods have opposite viewing angles where hemispherical photography measures canopy density upwardly, while UAV captures images downwardly. This study aims to analyze and compare both methods to be used as the input data for canopy density estimation when linked with a lower spatial resolution of remote sensing data i.e. Landsat image. We correlated the field data of canopy density with vegetation indices (NDVI, MSAVI, and AFRI) from Landsat-8. The canopy density values measured from UAV and hemispherical photography displayed a strong relationship with 0.706 coefficient of correlation. Further results showed that both measurements can be used in canopy density estimation using satellite imagery based on their high correlations with Landsat-based vegetation indices. The highest correlation from downward and upward measurement appeared when linked with NDVI with a correlation of 0.962 and 0.652, respectively. Downward measurement using UAV exhibited a higher relationship compared to hemispherical photography. The strong correlation between UAV data and Landsat data is because both are captured from the vertical direction, and 30 m pixel of Landsat is a downscaled image of the aerial photograph. Moreover, field data collection can be easily conducted by deploying drone to cover inaccessible sample plots.
A Simplified and Robust Surface Reflectance Estimation Method (SREM) for Use ...Muhammad Bilal
The document describes a new Simplified and Robust Surface Reflectance Estimation Method (SREM) for estimating surface reflectance from multi-sensor remote sensing data. SREM is based on equations from the widely-used 6S radiative transfer model but does not require inputs on aerosols and atmospheric gases. The method is tested using Landsat 5, 7, and 8 data from 2000-2018. Results show SREM produces surface reflectance with high correlation and low errors compared to in situ measurements and other Landsat surface reflectance products. SREM also performs well when applied to Sentinel-2A and MODIS data, suggesting it can be used with other satellite sensors.
Shallow Water Depth Mapping Using Single Band and Band Ratio on High-Resoluti...Luhur Moekti Prayogo
This document summarizes a study that compares the accuracy of single band and band ratio methods for shallow water depth mapping using Worldview-3 satellite imagery of the Karimunjawa Islands, Indonesia. Depth data was collected via field surveys and corrected for tides. The study found that the band ratio method, specifically the blue/green ratio, produced more accurate depth estimates with a root mean square error of 1.669 meters compared to 2.373 meters for the best single band method. Therefore, the band ratio method is concluded to provide better shallow water depth estimates than the single band method for this study area and image dataset.
Automatic traffic light controller for emergency vehicle using peripheral int...IJECEIAES
Traffic lights play such important role in traffic management to control the traffic on the road. Situation at traffic light area is getting worse especially in the event of emergency cases. During traffic congestion, it is difficult for emergency vehicle to cross the road which involves many junctions. This situation leads to unsafe conditions which may cause accident. An Automatic Traffic Light Controller for Emergency Vehicle is designed and developed to help emergency vehicle crossing the road at traffic light junction during emergency situation. This project used Peripheral Interface Controller (PIC) to program a priority-based traffic light controller for emergency vehicle. During emergency cases, emergency vehicle like ambulance can trigger the traffic light signal to change from red to green in order to make clearance for its path automatically. Using Radio Frequency (RF) the traffic light operation will turn back to normal when the ambulance finishes crossing the road. Result showed the design is capable to response within the range of 55 meters. This project was successfully designed, implemented and tested.
A Review of Change Detection Techniques of LandCover Using Remote Sensing Dataiosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
The document summarizes seven categories of change detection techniques:
1. Algebra based approaches include image differencing, regression, ratioing, and change vector analysis. These methods are simple to implement but cannot provide complete change matrices.
2. Transformation techniques apply transformations like PCA and tasseled cap to images before change detection.
3. Classification based techniques perform post-classification comparison or combine classification with other algorithms.
4. Advanced models use techniques like spectral mixture analysis and biophysical parameters.
5. GIS and remote sensing are integrated in some methods.
6. Visual analysis relies on human interpretation of image differences.
7. Other techniques include measures of spatial dependence,
Using Remote Sensing Techniques For Monitoring Ecological Changes In Lakes: C...IJERA Editor
The ability to use remote sensing in studying lake ecology lies in the capability of satellite sensors to measure
the spectral reflectance of constituents in water bodies. This reflectance can be used to determine the
concentration of the constituents of the water column through mathematical relationships. This work identified a
simple linear equation for estimating suspended matter in Lake Naivasha with reflectance in Landsat7 ETM+
image. A R² = 0.94, n = 6 for suspended matter was obtained. Archive of Landsat imagery was used to
produce maps of suspended matter concentrations in the lake. The suspended matter concentrations at five
different locations in the lake over 30 year’s period were then estimated. It was therefore concluded that the
ecological changes Lake Naivasha is experiencing is the result of the high water abstraction and the effect of
climate change.
Tarımsal Toprak Haritalama'da Jeofizik MühendisliğiAli Osman Öncel
1) The document discusses a study evaluating the reliability and reproducibility of electromagnetic induction (EMI) data collection.
2) The study compared data from two identical EMI instruments, the calibration methods of different individuals, and variations in calibration height.
3) The results showed significant differences between instruments, calibrations, and heights. This demonstrates the need for standardization of EMI data collection procedures to ensure reliable and reproducible data.
Comparing canopy density measurement from UAV and hemispherical photography: ...IJECEIAES
UAV and hemispherical photography are common methods used in canopy density measurement. These two methods have opposite viewing angles where hemispherical photography measures canopy density upwardly, while UAV captures images downwardly. This study aims to analyze and compare both methods to be used as the input data for canopy density estimation when linked with a lower spatial resolution of remote sensing data i.e. Landsat image. We correlated the field data of canopy density with vegetation indices (NDVI, MSAVI, and AFRI) from Landsat-8. The canopy density values measured from UAV and hemispherical photography displayed a strong relationship with 0.706 coefficient of correlation. Further results showed that both measurements can be used in canopy density estimation using satellite imagery based on their high correlations with Landsat-based vegetation indices. The highest correlation from downward and upward measurement appeared when linked with NDVI with a correlation of 0.962 and 0.652, respectively. Downward measurement using UAV exhibited a higher relationship compared to hemispherical photography. The strong correlation between UAV data and Landsat data is because both are captured from the vertical direction, and 30 m pixel of Landsat is a downscaled image of the aerial photograph. Moreover, field data collection can be easily conducted by deploying drone to cover inaccessible sample plots.
A Simplified and Robust Surface Reflectance Estimation Method (SREM) for Use ...Muhammad Bilal
The document describes a new Simplified and Robust Surface Reflectance Estimation Method (SREM) for estimating surface reflectance from multi-sensor remote sensing data. SREM is based on equations from the widely-used 6S radiative transfer model but does not require inputs on aerosols and atmospheric gases. The method is tested using Landsat 5, 7, and 8 data from 2000-2018. Results show SREM produces surface reflectance with high correlation and low errors compared to in situ measurements and other Landsat surface reflectance products. SREM also performs well when applied to Sentinel-2A and MODIS data, suggesting it can be used with other satellite sensors.
Shallow Water Depth Mapping Using Single Band and Band Ratio on High-Resoluti...Luhur Moekti Prayogo
This document summarizes a study that compares the accuracy of single band and band ratio methods for shallow water depth mapping using Worldview-3 satellite imagery of the Karimunjawa Islands, Indonesia. Depth data was collected via field surveys and corrected for tides. The study found that the band ratio method, specifically the blue/green ratio, produced more accurate depth estimates with a root mean square error of 1.669 meters compared to 2.373 meters for the best single band method. Therefore, the band ratio method is concluded to provide better shallow water depth estimates than the single band method for this study area and image dataset.
Automatic traffic light controller for emergency vehicle using peripheral int...IJECEIAES
Traffic lights play such important role in traffic management to control the traffic on the road. Situation at traffic light area is getting worse especially in the event of emergency cases. During traffic congestion, it is difficult for emergency vehicle to cross the road which involves many junctions. This situation leads to unsafe conditions which may cause accident. An Automatic Traffic Light Controller for Emergency Vehicle is designed and developed to help emergency vehicle crossing the road at traffic light junction during emergency situation. This project used Peripheral Interface Controller (PIC) to program a priority-based traffic light controller for emergency vehicle. During emergency cases, emergency vehicle like ambulance can trigger the traffic light signal to change from red to green in order to make clearance for its path automatically. Using Radio Frequency (RF) the traffic light operation will turn back to normal when the ambulance finishes crossing the road. Result showed the design is capable to response within the range of 55 meters. This project was successfully designed, implemented and tested.
Multi sensor data fusion for change detectionsanu sharma
This document summarizes a study that used multi-sensor data fusion to detect changes in a coastal zone in Trabzon, Turkey between 2000 and 2003. The study fused higher resolution aerial photographs and IKONOS panchromatic data with lower resolution ETM+ multispectral data to create 1m resolution multi-spectral images for both time periods. Post-classification comparison of the fused images from 2000 and 2003 was then used to detect changes in the coastal zone due to highway construction, identifying an area of 186023 m2 of new filled earth. Fusion was performed using the à trous wavelet transform algorithm to preserve spectral content while improving spatial resolution for accurate change detection.
Satellite based observations of the time-variation of urban pattern morpholog...Beniamino Murgante
Satellite based observations of the time-variation of urban pattern morphology using geospatial analysis
Gabriele Nolè, Rosa Lasaponara - Institute of Methodologies for Environmental Analysis, National Research Council, Italy
study and analysis of hy si data in 400 to 500IJAEMSJORNAL
This document summarizes a research paper that analyzed hyperspectral data in the 400-500nm visible and near infrared (VNIR) spectrum for precision agriculture applications. Specifically:
1) Hyperspectral imagery of the Amravati region of India was classified using maximum likelihood classification to determine soil, water, and vegetation indices. Spectral graphs showed reflectance curves for each.
2) The analysis aims to extract information about the terrain from hyperspectral data in a way that is easily understood. Such data provides more accurate information than multispectral data due to the large number of narrow bands.
3) Supervised classification with maximum likelihood was used to categorize pixels into classes for producing the
Safety is the primary and most important reason for monitoring the deformations of engineering structures. It could also help in improving our knowledge of the mechanical behaviour of engineering structures. Engineering structures are subject to deformation due to factors such as changes of ground water level, traffic load changes, tidal and tectonic phenomena. The Ikpoba River Bridge in Benin City whose traffic load has increased was monitored using GPS technology. The bridge was investigated as a result of carrying more load than usual due to the expansion of the road and dredging activities that had taken place in the river in 2008. One reference station and six monitoring points were involved in the monitoring of the bridge. The regularity of the survey was thirty days, and six observation epochs were used. Each monitoring point was occupied for about thirty minutes during the observation. The observation data were processed with compass software. The processed coordinates were adjusted with least squares adjustment technique. The standard deviation of unit weight for the weighted observations (σo) was computed for each observation epoch and was less than 1cm. The observation epochs were compared consecutively by finding the difference between successive observation results. The maximum differences in coordinates of the successive epochs were all less than 1mm. It was seen from the results that the bridge
was stable and did not undergo any displacement/movement within the period of study. It is recommended that the results of the six monitored points on the bridge should be further analyzed using other appropriate model of adjustment technique.
APPLICATION OF REMOTE SENSING AND GIS IN AGRICULTURELagnajeetRoy
India is a country that depends on agriculture. Today in this era of technological supremacy, agriculture is also using different new technologies like some robotic machinery to remote sensing and Geographical Information System (GIS) for the betterment of agriculture. It is easy to get the information about that area where human cannot check the condition everyday and help in gathering the data with the help of remote sensing. Whereas GIS helps in preparation of map that shows an accurate representation of data we get through remote sensing. From disease estimation to stress factor due to water, from ground water quality index to acreage estimation in various way agriculture is being profited by the application of remote sensing and GIS in agriculture. The applications of those software or techniques are very new to the agriculture domain still much more exploration is needed in this part. New software’s are developing in different parts of the world and remote sensing. Today farmers understand the beneficiaries of these kinds of techniques to the farm field which help in increasing productivity that will help future generation as technology is hype in traditional system of farming.
This document provides an overview of a course on applying remote sensing and geographical information systems in civil engineering. The course consists of lectures and seminars covering topics in remote sensing and GIS. For remote sensing, lectures will discuss principles, sensors, data processing, platforms, image processing software, and microwave sensing. For GIS, lectures will cover concepts, data structures, software tools like ArcGIS, spatial queries, and applications in hydrological modeling. The goal of the course is to provide students with an understanding of remote sensing and GIS and their integration, and to learn basic skills in working with related data and software.
The application of remote sensing technique to verify changes in landscape du...Alexander Decker
Remote sensing techniques were used to analyze changes in landscape in an area of Nigeria due to mineral exploration activities. Satellite images from 1987 and 2001 were processed and analyzed. Visual interpretation of the images showed evidence of mining in 1987 that had expanded significantly by 2001. Unsupervised classification identified land cover features and showed significant changes between the two time periods, indicating increased mining activity. The analysis confirmed that remote sensing methods can effectively detect and analyze landscape changes caused by human activities like mineral exploration.
During the past decade, the size of 3D seismic data volumes and the number of seismic attributes have increased
to the extent that it is difficult, if not impossible, for interpreters to examine every seismic line and time
slice. To address this problem, several seismic facies classification algorithms including k-means, self-organizing
maps, generative topographic mapping, support vector machines, Gaussian mixture models, and artificial neural
networks have been successfully used to extract features of geologic interest from multiple volumes. Although
well documented in the literature, the terminology and complexity of these algorithms may bewilder the average
seismic interpreter, and few papers have applied these competing methods to the same data volume. We have
reviewed six commonly used algorithms and applied them to a single 3D seismic data volume acquired over the
Canterbury Basin, offshore New Zealand, where one of the main objectives was to differentiate the architectural
elements of a turbidite system. Not surprisingly, the most important parameter in this analysis was the choice of
the correct input attributes, which in turn depended on careful pattern recognition by the interpreter. We found
that supervised learning methods provided accurate estimates of the desired seismic facies, whereas unsupervised
learning methods also highlighted features that might otherwise be overlooked.
Innovations in the Geoscience Research: Classification of the Landsat TM Imag...Universität Salzburg
Current research presents application of the ILWIS GIS for satellite image processing and classification aimed at land cover types mapping. Two images were classified and analysed. Changes in land cover types were detected for the time 1988 - 2011. The study area covers selected example regions of North Russia. Supervised classification of the raster imagery aims at recognizing of the class membership for each pixel during image analysis. The results demonstrate application of the ILWIS GIS approach of technical processing of the raster images and recognizing classes of the land cover types. The The Minimal Distance Classifier was used as an approach. due to its applicability, logical methodology and precision. The supervised classification of the multi-spectral imagery has been performed using 'Classify' operator in ILWIS GIS applied to Landsat TM 1988, 2001 and 2011. This work has a technical character of GIS applications for remote sensing (RS) data processing. It reports ILWIS GIS approach of the RS data processing Landsat TM satellite image using unsupervised and supervised classification methods. The methods of ILWIS GIS are compared and the results described. Presented at the 8th International Conference 'Prospects for the Higher School Development', Grodno State Agrarian University (GGAU) Grodno, Belarus, May 28-29 2015.
Application of remote sensing in forest ecosystemaliya nasir
Established remote sensing systems provide opportunities to develop and apply new measurements of ecosystem function across landscapes, regions and continents.
New efforts to predict the consequences of ecosystem function change, both natural and human- induced, on the regional and global distributions and abundances of species should be a high research priority
This document compares the ability of Landsat 8 and Landsat 7 data to map geology and visualize lineaments in central Kenya. It finds that:
1) Principal component analysis and band ratio techniques on Landsat 8 and 7 data enhanced geological contrasts in the study area, which has both semi-arid and highland terrain.
2) Knowledge-based classification of principal component and band ratio outputs from both sensors produced geology maps superior to existing maps, which could be used to update them.
3) False color combinations of independent component analysis and principal component analysis bands on both datasets effectively visualized lineaments for structural geology analysis.
Convolutional neural networks can be used to automatically identify stratigraphic patterns in seismic data. The CNNs can be trained on various seismic facies and depositional sequences to recognize visual similarities. This will help perform seismic stratigraphic interpretation more efficiently and objectively compared to current methods that rely heavily on human expertise. The automated identification of stratigraphic features could further allow the detection of potential play types, leads, and prospects within the seismic volume.
Remote sensing involves obtaining information about an area through analysis of physical data collected from a distance by devices without direct contact. It has been used since the 1850s for aerial photography from balloons and developed further for military purposes. Key concepts include data acquisition using various energy sources and sensors, data analysis including interpretation of imagery, and applications in ecology such as monitoring terrestrial, aquatic and animal environments as well as ecological damage. Geographic information systems (GIS) integrate spatial and non-spatial data for managing, analyzing and visualizing information. GIS techniques include data capture, storage, management, retrieval, analysis and display. GIS has many applications including environmental studies and improving understanding of processes and human activities.
This document discusses remote sensing and geographical information systems. It defines remote sensing as obtaining information about the Earth's surface without direct contact using sensors. Applications of remote sensing include urban planning, agriculture, and environmental monitoring. Geographical information systems integrate spatial data to analyze and visualize patterns. The document outlines how remote sensing from satellites provides a global perspective and both technologies are useful for civil engineering tasks like infrastructure planning, site analysis, and structural health monitoring.
3 d seismic method for reservoir geothermal exploration n assessmentMuhammad Khawarizmi
1) 3-D seismic reflection methods have potential to image fractures controlling geothermal reservoirs but past studies often failed to identify drill targets due to scattering and heterogeneity.
2) Recent advances in 3-D seismic acquisition and processing, as well as modeling of fracture effects on seismic waves, may enable more detailed subsurface imaging capable of locating productive fracture pathways.
3) Methods analyzing amplitude versus offset, azimuth, and frequency content across 3-D volumes can help characterize fracture orientations that may control fluid flow. However, higher resolution is still needed to define the specific fractures controlling permeability.
This document describes a study that used remote sensing and GIS techniques to analyze land use/land cover change in Dehradun District, India over a 22-year period from 1994 to 2016. Landsat satellite images from 1994, 1999, and 2016 were classified into six land use/land cover classes: vegetation, agriculture, built-up, barren, sediment, and water. The results found increases in vegetation, built-up, barren and sediment areas, and decreases in agricultural land and water bodies. The approach demonstrated the potential of remote sensing and GIS for measuring and understanding land use/land cover change dynamics over time.
In this deck from the 2018 HPC User Forum in Tucson, Christine Goulet from the Southern California Earthquake Center presents: HPC Use for Earthquake Research.
"The Southern California Earthquake Center (SCEC) was founded as a Science & Technology Center in 1991, with joint funding by the NSF and the U. S. Geological Survey. SCEC coordinates fundamental research on earthquake processes using Southern California as its principal natural laboratory. This research program is investigator-driven and supports core research and education in seismology, tectonic geodesy, earthquake geology, and computational science. The SCEC community advances earthquake system science through three basic activities: (a) gathering information from seismic and geodetic sensors, geologic field observations, and laboratory experiments; (b) synthesizing knowledge of earthquake phenomena through physics-based modeling, including system-level hazard modeling; and communicating our understanding of seismic hazards to reduce earthquake risk and promote community resilience."
Watch the video: https://wp.me/p3RLHQ-imT
Learn more: https://www.scec.org/about
and
http://hpcuserforum.com
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
Feature Extraction from the Satellite Image Gray Color and Knowledge Discove...IJMER
Satellite take images of the Earth in selected spectral bands that are in both the visible and
the infrared portions of the electromagnetic spectrum. Many Satellites provide three types of Satellite
Images. These Images are Visible Satellite Image, Infrared Satellite Image, and Water Vapor Satellite
Image. These images are important for different reasons, and, in some cases, all three are needed to
accurately interpret atmospheric conditions. These Satellite images contain different types of cloud. This
paper shows cloud feature extraction using Histogram. A table that shows cloud existence in different
image is created, called Association table in which Y represents cloud is exist and N represent not exist.
Association rule mining is applied to this table to make relations between different clouds and discover
the knowledge about cloud existence.
This document summarizes various stemming algorithms used for information retrieval. It discusses rule-based stemming algorithms like the Porter stemmer and Lovins stemmer which use language rules to remove suffixes and extract word stems. It also describes statistical stemming methods which use machine learning on text corpora to identify morphological variants. Finally, it analyzes different techniques for conflating words during stemming, such as affix removal, successor variety, table lookup, and n-gram methods.
This document evaluates the hydraulic conductivity of a marble dust-soil composite. Laboratory tests were conducted to determine the index properties and compaction characteristics of a clayey soil treated with 0-20% marble dust. Hydraulic conductivity tests using a consolidometer found that permeability decreased with up to 12.5% marble dust addition and remained constant thereafter. Permeability also decreased with higher compaction moisture content. Based on the results, 25% marble dust addition was proposed to satisfy the regulatory permeability requirement of ≤ 1 x 10-9 m/s for landfill liner materials.
Multi sensor data fusion for change detectionsanu sharma
This document summarizes a study that used multi-sensor data fusion to detect changes in a coastal zone in Trabzon, Turkey between 2000 and 2003. The study fused higher resolution aerial photographs and IKONOS panchromatic data with lower resolution ETM+ multispectral data to create 1m resolution multi-spectral images for both time periods. Post-classification comparison of the fused images from 2000 and 2003 was then used to detect changes in the coastal zone due to highway construction, identifying an area of 186023 m2 of new filled earth. Fusion was performed using the à trous wavelet transform algorithm to preserve spectral content while improving spatial resolution for accurate change detection.
Satellite based observations of the time-variation of urban pattern morpholog...Beniamino Murgante
Satellite based observations of the time-variation of urban pattern morphology using geospatial analysis
Gabriele Nolè, Rosa Lasaponara - Institute of Methodologies for Environmental Analysis, National Research Council, Italy
study and analysis of hy si data in 400 to 500IJAEMSJORNAL
This document summarizes a research paper that analyzed hyperspectral data in the 400-500nm visible and near infrared (VNIR) spectrum for precision agriculture applications. Specifically:
1) Hyperspectral imagery of the Amravati region of India was classified using maximum likelihood classification to determine soil, water, and vegetation indices. Spectral graphs showed reflectance curves for each.
2) The analysis aims to extract information about the terrain from hyperspectral data in a way that is easily understood. Such data provides more accurate information than multispectral data due to the large number of narrow bands.
3) Supervised classification with maximum likelihood was used to categorize pixels into classes for producing the
Safety is the primary and most important reason for monitoring the deformations of engineering structures. It could also help in improving our knowledge of the mechanical behaviour of engineering structures. Engineering structures are subject to deformation due to factors such as changes of ground water level, traffic load changes, tidal and tectonic phenomena. The Ikpoba River Bridge in Benin City whose traffic load has increased was monitored using GPS technology. The bridge was investigated as a result of carrying more load than usual due to the expansion of the road and dredging activities that had taken place in the river in 2008. One reference station and six monitoring points were involved in the monitoring of the bridge. The regularity of the survey was thirty days, and six observation epochs were used. Each monitoring point was occupied for about thirty minutes during the observation. The observation data were processed with compass software. The processed coordinates were adjusted with least squares adjustment technique. The standard deviation of unit weight for the weighted observations (σo) was computed for each observation epoch and was less than 1cm. The observation epochs were compared consecutively by finding the difference between successive observation results. The maximum differences in coordinates of the successive epochs were all less than 1mm. It was seen from the results that the bridge
was stable and did not undergo any displacement/movement within the period of study. It is recommended that the results of the six monitored points on the bridge should be further analyzed using other appropriate model of adjustment technique.
APPLICATION OF REMOTE SENSING AND GIS IN AGRICULTURELagnajeetRoy
India is a country that depends on agriculture. Today in this era of technological supremacy, agriculture is also using different new technologies like some robotic machinery to remote sensing and Geographical Information System (GIS) for the betterment of agriculture. It is easy to get the information about that area where human cannot check the condition everyday and help in gathering the data with the help of remote sensing. Whereas GIS helps in preparation of map that shows an accurate representation of data we get through remote sensing. From disease estimation to stress factor due to water, from ground water quality index to acreage estimation in various way agriculture is being profited by the application of remote sensing and GIS in agriculture. The applications of those software or techniques are very new to the agriculture domain still much more exploration is needed in this part. New software’s are developing in different parts of the world and remote sensing. Today farmers understand the beneficiaries of these kinds of techniques to the farm field which help in increasing productivity that will help future generation as technology is hype in traditional system of farming.
This document provides an overview of a course on applying remote sensing and geographical information systems in civil engineering. The course consists of lectures and seminars covering topics in remote sensing and GIS. For remote sensing, lectures will discuss principles, sensors, data processing, platforms, image processing software, and microwave sensing. For GIS, lectures will cover concepts, data structures, software tools like ArcGIS, spatial queries, and applications in hydrological modeling. The goal of the course is to provide students with an understanding of remote sensing and GIS and their integration, and to learn basic skills in working with related data and software.
The application of remote sensing technique to verify changes in landscape du...Alexander Decker
Remote sensing techniques were used to analyze changes in landscape in an area of Nigeria due to mineral exploration activities. Satellite images from 1987 and 2001 were processed and analyzed. Visual interpretation of the images showed evidence of mining in 1987 that had expanded significantly by 2001. Unsupervised classification identified land cover features and showed significant changes between the two time periods, indicating increased mining activity. The analysis confirmed that remote sensing methods can effectively detect and analyze landscape changes caused by human activities like mineral exploration.
During the past decade, the size of 3D seismic data volumes and the number of seismic attributes have increased
to the extent that it is difficult, if not impossible, for interpreters to examine every seismic line and time
slice. To address this problem, several seismic facies classification algorithms including k-means, self-organizing
maps, generative topographic mapping, support vector machines, Gaussian mixture models, and artificial neural
networks have been successfully used to extract features of geologic interest from multiple volumes. Although
well documented in the literature, the terminology and complexity of these algorithms may bewilder the average
seismic interpreter, and few papers have applied these competing methods to the same data volume. We have
reviewed six commonly used algorithms and applied them to a single 3D seismic data volume acquired over the
Canterbury Basin, offshore New Zealand, where one of the main objectives was to differentiate the architectural
elements of a turbidite system. Not surprisingly, the most important parameter in this analysis was the choice of
the correct input attributes, which in turn depended on careful pattern recognition by the interpreter. We found
that supervised learning methods provided accurate estimates of the desired seismic facies, whereas unsupervised
learning methods also highlighted features that might otherwise be overlooked.
Innovations in the Geoscience Research: Classification of the Landsat TM Imag...Universität Salzburg
Current research presents application of the ILWIS GIS for satellite image processing and classification aimed at land cover types mapping. Two images were classified and analysed. Changes in land cover types were detected for the time 1988 - 2011. The study area covers selected example regions of North Russia. Supervised classification of the raster imagery aims at recognizing of the class membership for each pixel during image analysis. The results demonstrate application of the ILWIS GIS approach of technical processing of the raster images and recognizing classes of the land cover types. The The Minimal Distance Classifier was used as an approach. due to its applicability, logical methodology and precision. The supervised classification of the multi-spectral imagery has been performed using 'Classify' operator in ILWIS GIS applied to Landsat TM 1988, 2001 and 2011. This work has a technical character of GIS applications for remote sensing (RS) data processing. It reports ILWIS GIS approach of the RS data processing Landsat TM satellite image using unsupervised and supervised classification methods. The methods of ILWIS GIS are compared and the results described. Presented at the 8th International Conference 'Prospects for the Higher School Development', Grodno State Agrarian University (GGAU) Grodno, Belarus, May 28-29 2015.
Application of remote sensing in forest ecosystemaliya nasir
Established remote sensing systems provide opportunities to develop and apply new measurements of ecosystem function across landscapes, regions and continents.
New efforts to predict the consequences of ecosystem function change, both natural and human- induced, on the regional and global distributions and abundances of species should be a high research priority
This document compares the ability of Landsat 8 and Landsat 7 data to map geology and visualize lineaments in central Kenya. It finds that:
1) Principal component analysis and band ratio techniques on Landsat 8 and 7 data enhanced geological contrasts in the study area, which has both semi-arid and highland terrain.
2) Knowledge-based classification of principal component and band ratio outputs from both sensors produced geology maps superior to existing maps, which could be used to update them.
3) False color combinations of independent component analysis and principal component analysis bands on both datasets effectively visualized lineaments for structural geology analysis.
Convolutional neural networks can be used to automatically identify stratigraphic patterns in seismic data. The CNNs can be trained on various seismic facies and depositional sequences to recognize visual similarities. This will help perform seismic stratigraphic interpretation more efficiently and objectively compared to current methods that rely heavily on human expertise. The automated identification of stratigraphic features could further allow the detection of potential play types, leads, and prospects within the seismic volume.
Remote sensing involves obtaining information about an area through analysis of physical data collected from a distance by devices without direct contact. It has been used since the 1850s for aerial photography from balloons and developed further for military purposes. Key concepts include data acquisition using various energy sources and sensors, data analysis including interpretation of imagery, and applications in ecology such as monitoring terrestrial, aquatic and animal environments as well as ecological damage. Geographic information systems (GIS) integrate spatial and non-spatial data for managing, analyzing and visualizing information. GIS techniques include data capture, storage, management, retrieval, analysis and display. GIS has many applications including environmental studies and improving understanding of processes and human activities.
This document discusses remote sensing and geographical information systems. It defines remote sensing as obtaining information about the Earth's surface without direct contact using sensors. Applications of remote sensing include urban planning, agriculture, and environmental monitoring. Geographical information systems integrate spatial data to analyze and visualize patterns. The document outlines how remote sensing from satellites provides a global perspective and both technologies are useful for civil engineering tasks like infrastructure planning, site analysis, and structural health monitoring.
3 d seismic method for reservoir geothermal exploration n assessmentMuhammad Khawarizmi
1) 3-D seismic reflection methods have potential to image fractures controlling geothermal reservoirs but past studies often failed to identify drill targets due to scattering and heterogeneity.
2) Recent advances in 3-D seismic acquisition and processing, as well as modeling of fracture effects on seismic waves, may enable more detailed subsurface imaging capable of locating productive fracture pathways.
3) Methods analyzing amplitude versus offset, azimuth, and frequency content across 3-D volumes can help characterize fracture orientations that may control fluid flow. However, higher resolution is still needed to define the specific fractures controlling permeability.
This document describes a study that used remote sensing and GIS techniques to analyze land use/land cover change in Dehradun District, India over a 22-year period from 1994 to 2016. Landsat satellite images from 1994, 1999, and 2016 were classified into six land use/land cover classes: vegetation, agriculture, built-up, barren, sediment, and water. The results found increases in vegetation, built-up, barren and sediment areas, and decreases in agricultural land and water bodies. The approach demonstrated the potential of remote sensing and GIS for measuring and understanding land use/land cover change dynamics over time.
In this deck from the 2018 HPC User Forum in Tucson, Christine Goulet from the Southern California Earthquake Center presents: HPC Use for Earthquake Research.
"The Southern California Earthquake Center (SCEC) was founded as a Science & Technology Center in 1991, with joint funding by the NSF and the U. S. Geological Survey. SCEC coordinates fundamental research on earthquake processes using Southern California as its principal natural laboratory. This research program is investigator-driven and supports core research and education in seismology, tectonic geodesy, earthquake geology, and computational science. The SCEC community advances earthquake system science through three basic activities: (a) gathering information from seismic and geodetic sensors, geologic field observations, and laboratory experiments; (b) synthesizing knowledge of earthquake phenomena through physics-based modeling, including system-level hazard modeling; and communicating our understanding of seismic hazards to reduce earthquake risk and promote community resilience."
Watch the video: https://wp.me/p3RLHQ-imT
Learn more: https://www.scec.org/about
and
http://hpcuserforum.com
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
Feature Extraction from the Satellite Image Gray Color and Knowledge Discove...IJMER
Satellite take images of the Earth in selected spectral bands that are in both the visible and
the infrared portions of the electromagnetic spectrum. Many Satellites provide three types of Satellite
Images. These Images are Visible Satellite Image, Infrared Satellite Image, and Water Vapor Satellite
Image. These images are important for different reasons, and, in some cases, all three are needed to
accurately interpret atmospheric conditions. These Satellite images contain different types of cloud. This
paper shows cloud feature extraction using Histogram. A table that shows cloud existence in different
image is created, called Association table in which Y represents cloud is exist and N represent not exist.
Association rule mining is applied to this table to make relations between different clouds and discover
the knowledge about cloud existence.
This document summarizes various stemming algorithms used for information retrieval. It discusses rule-based stemming algorithms like the Porter stemmer and Lovins stemmer which use language rules to remove suffixes and extract word stems. It also describes statistical stemming methods which use machine learning on text corpora to identify morphological variants. Finally, it analyzes different techniques for conflating words during stemming, such as affix removal, successor variety, table lookup, and n-gram methods.
This document evaluates the hydraulic conductivity of a marble dust-soil composite. Laboratory tests were conducted to determine the index properties and compaction characteristics of a clayey soil treated with 0-20% marble dust. Hydraulic conductivity tests using a consolidometer found that permeability decreased with up to 12.5% marble dust addition and remained constant thereafter. Permeability also decreased with higher compaction moisture content. Based on the results, 25% marble dust addition was proposed to satisfy the regulatory permeability requirement of ≤ 1 x 10-9 m/s for landfill liner materials.
This document discusses continuous testing of service-oriented applications using service virtualization. It begins with an introduction to service-oriented architecture and discusses how service virtualization can address challenges in testing SOA applications by virtualizing dependencies and unavailable components. The document then discusses how service virtualization enables simultaneous development and testing, handles out-of-scope data dependencies, and supports heterogeneous technologies and platforms. It also provides an overview of the service virtualization lifecycle and some popular service virtualization tools.
This document summarizes an encryption technique for securing data in cloud computing environments. It begins by introducing cloud computing and some of the security concerns with storing data in the cloud. It then discusses previous encryption algorithms like the Caesar cipher, Vigenere cipher, and Playfair cipher and their limitations. The document proposes using the Advanced Encryption Standard (AES) algorithm with Rijndael cipher to encrypt data before uploading it to cloud servers. It describes implementing AES encryption in two steps: 1) using an authentication channel to verify user identities, and 2) encrypting the data using the AES Rijndael algorithm in 9 to 13 rounds depending on the key size. The document argues this encryption technique can help make customer data in the
The document summarizes a proposed fuzzy logic-based joint space path planning system for a 3 degree-of-freedom robot manipulator. The system is composed of three separate fuzzy logic units that each control one of the manipulator joints. The inputs and outputs of each fuzzy block control the change in joint position for each time step. Simulation results show the robot is able to reach the goal configuration successfully using this approach. The fuzzy logic method is able to meet real-time requirements for robot motion planning without requiring an exact model of the robot.
1) The document analyzes the interaction forces between two non-identical cylinders spinning around their stationary and parallel axes in an ideal fluid.
2) It derives the exact equations for the velocity field of the fluid using Laplace's equation and the boundary conditions.
3) It then determines the pressure field from the velocity field using Bernoulli's equation and integrates the pressure around the cylinder surfaces to find the forces acting on their axes.
4) It finds that the cylinders will repel or attract each other in inverse relation to their separation distance, depending on whether their directions of rotation are similar or opposite.
This document summarizes the design of an air conditioning system for cooling the cabin of a truck using an air refrigeration cycle. The system uses a turbocharger and waste exhaust gases from the truck engine. Atmospheric air is compressed using the turbocharger and sent to an intercooler to reduce its temperature. It is then expanded in a turbo-expander to further lower its temperature before being supplied to the truck cabin. Thermodynamic and heat transfer analyses are presented to evaluate the performance of the system components and the cooling capacity. The results show that the air refrigeration cycle can provide enough cooling to lower the truck cabin temperature by 10-15°C without significantly impacting engine performance.
This document summarizes the design and analysis of an inverted-F antenna for wideband applications. It presents the geometry of the coaxially-fed inverted-F antenna and discusses its ability to resonate at wideband frequencies. The antenna is designed on an FR4_epoxy substrate using simulation software. Key parameters like return loss, VSWR, and gain are simulated and validated through measurements. The antenna operates in five bands from 1.18GHz to 7.97GHz with good matching between simulated and measured results, making it suitable for multi-band applications.
This document discusses centralized fault management of docks in marine sensor networks. It proposes a distributed routing algorithm (DRA) and network topology management technique (NTMT) to address issues with existing systems. DRA allows for pre-failure detection of nodes by having nodes send heartbeat messages to neighbors. If a node fails, NTMT selects a replacement node from the smallest affected network partition and coordinates moving related nodes to restore connectivity while maintaining existing links. The techniques are analyzed through simulations which show improvements over previous approaches by enabling pre-failure detection and recovery without significantly increasing path lengths or overhead.
This document provides a critical review of factors influencing labor productivity in the construction industry. It identifies supervision, skill of laborers, tools/equipment, absenteeism, and financial constraints as the most significant factors based on prior research. The review also examines how factors can be grouped, with human, management, material/tool, environmental, and technological groups found to be important. Analysis methods like factor analysis are discussed that can help identify independent and group factors to improve labor productivity.
This document describes using particle swarm optimization (PSO) to detect defective elements in a spaceborne planar antenna array. PSO is an optimization technique that models social behavior to iteratively find the global minimum of a cost function. Here, PSO is used to minimize the difference between measured and expected far-field radiation patterns to determine the location of any defective array elements. The document outlines designing a 2x2 planar array in IE3D software, introducing defects, calculating error patterns, and using PSO to optimize element positions to minimize error and correctly identify defective elements based only on far-field power measurements. The technique is shown to successfully detect randomly defective elements in the array, making it useful for locating failures in space applications where
This document summarizes an adaptive fuzzy logic power filter for nonlinear systems. It proposes using a Takagi-Sugeno fuzzy logic controller (FLC) to control a three-phase shunt active power filter (SAPF) to compensate for harmonic distortion and power quality issues caused by nonlinear loads. The FLC generates reference compensation currents and maintains the SAPF DC capacitor voltage. It is compared to a conventional PI controller, with the FLC showing better robustness to load and system parameter changes. The document describes the instantaneous reactive power theory used to estimate compensation currents, the design of the Takagi-Sugeno FLC, and an adaptive hysteresis current control method to generate switching signals for the SAPF
1) The document describes a study conducted to improve call drop rates in a GSM network through RF optimization.
2) Drive testing was performed before and after optimization using TEMS software to record network parameters like RxLevel, RxQuality, and events.
3) Analysis found call drops were occurring due to issues like handover failures between sectors, interference from adjacent channels, and overshooting due to antenna tilt.
4) Corrective actions taken included defining neighbors between sectors, adjusting frequencies to reduce interference, and lowering the mechanical tilt of an antenna.
5) Post-optimization drive testing showed improvements in RxLevel, RxQuality, and a reduction in dropped calls.
This document describes the design and analysis of India's first tiltrotor aircraft called the V-44. A tiltrotor aircraft has the capability of vertical takeoff and landing like a helicopter, as well as high-speed horizontal flight like a fixed-wing aircraft. The authors conducted computational fluid dynamics simulations to analyze the V-44's airflow and constructed the aircraft using lightweight aluminum. Key features of the V-44 include coaxial rotary wings controlled by heavy-duty servos, a tilting mechanism allowing wing rotation from 0 to 90 degrees, and an estimated takeoff weight of 2.37 kg. The conclusion is that the V-44 design is feasible and could have applications for military transport and civilian rescue operations.
This document summarizes a research paper on developing a multi-account embedded ATM card with enhanced security. Key points include:
1) The proposed system would embed multiple bank accounts onto a single smart ATM card, allowing customers to access all accounts from any ATM without carrying multiple cards.
2) Security would be enhanced through fingerprint authentication instead of just a PIN. A fingerprint scanner would be integrated into the ATM to verify customers' identities.
3) This would provide more convenience for customers while reducing fraud risks compared to traditional single-account cards authenticated solely with PINs.
This document summarizes a research paper that proposes a multitasking stick to assist visually impaired people in navigating safely. The stick uses ultrasonic sensors to detect obstacles, a temperature sensor to detect high heat areas, electrodes to detect water, and a voice playback module to notify the user of detections. It also includes an RF module to help locate the stick if misplaced. The stick was tested indoors and outdoors and performed accurately in detecting obstacles of different materials at varying distances, demonstrating its effectiveness as an assistive device for the blind.
Crack Detection for Various Loading Conditions in Beam Using Hilbert – Huang ...IOSR Journals
The document discusses crack detection in beams using the Hilbert-Huang transform (HHT). It first provides background on using vibration-based methods to detect structural damage. It then describes modeling a cracked beam using finite element analysis, representing the crack as a rotational spring. Vibration analysis is performed on simply supported, fixed-fixed, free-free, and cantilever beams with cracks. HHT is applied to the transformed response to determine crack location based on changes in spatial variation. Both analytical and experimental results show good agreement with the model and that HHT is effective for analysis.
Feature Based Semantic Polarity Analysis Through OntologyIOSR Journals
This document summarizes a research paper that proposes an opinion mining methodology using ontologies and natural language processing techniques to perform feature-based sentiment analysis of customer reviews. It begins by collecting customer reviews from websites. The reviews are preprocessed by removing URLs, usernames, etc. and performing part-of-speech tagging to extract product features. An ontology is constructed to organize the features and their relationships. Term frequencies are calculated to determine feature importance. Sentiment scores from -5 to 5 are assigned to each feature using a sentiment analysis tool and N-gram analysis. The methodology is evaluated using precision, recall, and F-measure. The feature-level sentiment analysis provides more detailed and helpful information for customers and developers compared to document-level
Path-Loss Determination of 91.5 MHZ FM Radio Channel of Ekiti StateIOSR Journals
This document summarizes a study that measured the field strength distribution of a 91.5 MHz FM radio signal across Ekiti State, Nigeria. Field strength, location coordinates, and distance from transmitter were measured along four routes moving away from the broadcast station. The path loss along each route was calculated using Friis and Okumura-Hata propagation models and compared to measured values. Okumura-Hata provided closer predictions, with a mean error of 2.68dB across all routes, and is thus more suitable for predicting path loss for VHF waves in Ekiti State when a 2.68dB loss factor is included.
The document describes an experiment to optimize cutting parameters during CNC turning of AISI 8620 alloy steel using response surface methodology. Speed, feed rate, and depth of cut were varied as factors in a 3-level factorial design. The response variable was surface roughness, which was measured after each experimental run. Regression analysis in Minitab was used to develop a model relating the factors to surface roughness. Response optimization was then used to determine the optimal settings of the factors to minimize surface roughness. The goal of the experiment was to evaluate the best cutting parameter settings for achieving a smooth surface finish during CNC turning of AISI 8620 alloy steel.
Performance analysis of change detection techniques for land use land coverIJECEIAES
Remotely sensed satellite images have become essential to observe the spatial and temporal changes occurring due to either natural phenomenon or man-induced changes on the earth’s surface. Real time monitoring of this data provides useful information related to changes in extent of urbanization, environmental changes, water bodies, and forest. Through the use of remote sensing technology and geographic information system tools, it has become easier to monitor changes from past to present. In the present scenario, choosing a suitable change detection method plays a pivotal role in any remote sensing project. Previously, digital change detection was a tedious task. With the advent of machine learning techniques, it has become comparatively easier to detect changes in the digital images. The study gives a brief account of the main techniques of change detection related to land use land cover information. An effort is made to compare widely used change detection methods used to identify changes and discuss the need for development of enhanced change detection methods.
he data obtained from remote sensing satellites fu
rnish information about the land at varying resolut
ions
and has been widely used for change detection studi
es. There exist a huge number of change detection
methodologies and techniques with the continual eme
rgence of new ones. This paper provides a review of
pixel based and object-based change detection techn
iques in conjunction with the comparison of their
merits and limitations. The advent of very-high-res
olution remotely sensed images, exponentially incre
ased
image data volume and multiple sensors demand the p
otential use of data mining techniques in tandem
with object-based methods for change detection
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
This document summarizes a research paper that classified multi-date remote sensing images using NDVI values. It discusses how NDVI values were calculated from Terra satellite imagery using red and infrared band values. A similarity measure formula was proposed to classify images based on comparing NDVI values of unknown images to reference images. The formula measured similarity between image windows using sum of absolute differences of NDVI values. Five Terra images from different dates were classified into 20 reference classes using this approach.
Evaluation and Accuracy Assessment of Static GPS Technique in Monitoring of ...IJMER
It is well known that, deformation monitoring systems are considered, nowadays, to be the
back bone factor for human safety as well as preserving the ultimate economy of his achievements. In
this context, there has been always an increasing demand for precise deformation measurements in
keeping up several engineering structures and historical monuments. Measuring and monitoring
monumental deformation is the sequence of operations that allows the finding of movements of points
or features in a specified coordinate system, during two different times for the same investigated
feature. The time interval sometimes is the main factor in measuring horizontal deformation, especially
in loading test of steel bridges. Hence, the present paper investigates the accuracy of the GPS in
monitoring of horizontal deformation with respect to the time of observation. So, a practical
simulation test was made to assess the accuracy of GPS with time in measuring horizontal
deformation. The obtained results indicated that, the used methods and techniques presented in the
current research paper have possessed a very good accuracy, reliability and applicability in
monitoring horizontal deformations efficiently. The accuracy of measuring horizontal deformation of
points on structure using relative static technique of GPS is from (0.1mm) to (1.8mm) for time interval
from 30 minute to 5 minute and has R.M.S.E (0.3mm)
This document summarizes and compares two image registration techniques: Scale Invariant Feature Transform (SIFT) and Curvature Scale-Space (CSS) Corner Detection with robust corner matching.
SIFT detects and describes local features in images that are invariant to changes in scale, rotation, and illumination. It finds key points at multiple scales and assigns orientations based on local image gradients. CSS corner detection uses the Canny edge detector to find edges, then detects corners as curvature maxima along edges. It parameterizes edges using affine-length for stability to affine transformations. Robust corner matching finds candidate matches based on curvature and affine-length, then estimates transformation matrices from triangle areas to find the best matches.
The document shows
Object Classification of Satellite Images Using Cluster Repulsion Based Kerne...IOSR Journals
Abstract: We investigated the Classification of satellite images and multispectral remote sensing data .we
focused on uncertainty analysis in the produced land-cover maps .we proposed an efficient technique for
classifying the multispectral satellite images using Support Vector Machine (SVM) into road area, building area
and green area. We carried out classification in three modules namely (a) Preprocessing using Gaussian
filtering and conversion from conversion of RGB to Lab color space image (b) object segmentation using
proposed Cluster repulsion based kernel Fuzzy C- Means (FCM) and (c) classification using one-to-many SVM
classifier. The goal of this research is to provide the efficiency in classification of satellite images using the
object-based image analysis. The proposed work is evaluated using the satellite images and the accuracy of the
proposed work is compared to FCM based classification. The results showed that the proposed technique has
achieved better results reaching an accuracy of 79%, 84%, 81% and 97.9% for road, tree, building and vehicle
classification respectively.
Keywords:-Satellite image, FCM Clustering, Classification, SVM classifier.
Distorted Path Analysis of Different Layered Soil Pressurized Under Uniform D...IRJET Journal
This document summarizes a study on analyzing the distorted paths of different layered soils under uniform displacement pressure using digital imaging technology. The study uses digital photography and image analysis to non-contact measure soil deformation at pre-failure strain levels without needing target markers. Results from the study help determine which soil formations are best for foundation design by concluding sandy soils deform more with higher deformation widths and less settlement compared to clayey soils.
This document compares three methods for mapping land cover of Vaderahalli Village, India: analysis of satellite imagery using GIS software MapInfo, analysis of Google Earth images using Google Pro software, and analysis of Google Earth images using MATLAB software. Land cover features mapped included green cover, water bodies, open spaces, paved surfaces and built-up areas. Results from each method were verified on-site using GPS. Analysis with MapInfo using satellite imagery provided the most accurate results but was more expensive and complex. Google Pro analysis was less accurate but simpler and cheaper. MATLAB analysis was least accurate and most complex and time-consuming. Overall, remote sensing with GIS provided the most effective land cover mapping approach.
Hyperspectral object classification using hybrid spectral-spatial fusion and ...IJECEIAES
Because of its spectral-spatial and temporal resolution of greater areas, hyperspectral imaging (HSI) has found widespread application in the field of object classification. The HSI is typically used to accurately determine an object's physical characteristics as well as to locate related objects with appropriate spectral fingerprints. As a result, the HSI has been extensively applied to object identification in several fields, including surveillance, agricultural monitoring, environmental research, and precision agriculture. However, because of their enormous size, objects require a lot of time to classify; for this reason, both spectral and spatial feature fusion have been completed. The existing classification strategy leads to increased misclassification, and the feature fusion method is unable to preserve semantic object inherent features; This study addresses the research difficulties by introducing a hybrid spectral-spatial fusion (HSSF) technique to minimize feature size while maintaining object intrinsic qualities; Lastly, a soft-margins kernel is proposed for multi-layer deep support vector machine (MLDSVM) to reduce misclassification. The standard Indian pines dataset is used for the experiment, and the outcome demonstrates that the HSSF-MLDSVM model performs substantially better in terms of accuracy and Kappa coefficient.
This document discusses using convolutional neural networks (CNNs) to classify and segment satellite imagery. It presents a novel approach using a CNN to perform per-pixel classification of multispectral satellite imagery and a digital surface model into five categories (vegetation, ground, roads, buildings, water). The CNN is first pre-trained with unsupervised clustering then fine-tuned for classification and segmentation. Results show the CNN approach outperforms existing methods, achieving 94.49% classification accuracy and improving segmentation by reducing salt-and-pepper effects from per-pixel classification alone.
Land Use/Land Cover Mapping Of Allahabad City by Using Remote Sensing & GIS IJMER
The present study was carried out to produce and evaluate the land use/land cover maps by on
screen visual interpretation. The studies of land cover of Allahabad city (study area) consist of 87517.47 ha
out of which 5500.35 ha is build up land (Urban / Rural) Area. In this respect, the Build up land (Urban /
Rural) area scorers 6.28% of the total area. It has also been found that about 17155.001ha (19.60 %) of
area is covered by current fallow land. The double/triple crop land of 30178.44ha (34.84%). The area
covered by gullied / ravines is 1539.20 ha (1.75 %) and that of the kharif crop land is 2828.00 ha (3.23 %).
The area covered by other wasteland is 2551.05ha (2.91%). Table 4.1 shows the area distribution of the
various land use and land cover of Allahabad city.
This document describes an improved particle filter tracking system that uses both color and moving edge information. It aims to address limitations of existing color-based particle filter tracking systems, such as inaccurate tracking when the target and background have similar colors, occlusion occurs, or the target is deformed. The proposed system selects an appropriate bounding box around the target using moving edge information to maintain an accurate target model during tracking. An experiment using 100 targets in 10 video clips showed the new system achieved a 94.6% accuracy rate for tracking, higher than an existing color-based particle filter system. It also had a 91.8% accuracy for occluded targets, much better than the previous system.
IRJET- Land Use & Land Cover Change Detection using G.I.S. & Remote SensingIRJET Journal
This document discusses land use and land cover change detection in Vadodara, India between 1998 and 2008 using remote sensing and GIS techniques. Specifically, it analyzed Landsat satellite images from those two decades to map and classify land use, including built up area, vegetation, vacant land, and water bodies. The methodology involved image preprocessing like geometric correction and radiometric normalization. Images were then enhanced and classified using both supervised and unsupervised classification. Comparing the classified maps from 1998 and 2008 allowed analyzing changes in land use over that 10-year period and calculating the rate of land consumption. The study aimed to provide information to urban planners for predicting future growth and avoiding problems associated with rapid urbanization.
This document summarizes a study that evaluated the accuracy of GPS and automatic level instruments for topographic surveying. The study collected elevation data using both instruments at points in a study area in Iraq. The data was input into GIS software to create contour maps and digital elevation models (DEMs) from each dataset. The accuracy of the DEMs was then evaluated and compared. The results showed the effect that the source data, DEM resolution, and ground control point distribution had on accuracy. This allowed the study to assess the relative accuracy and effectiveness of GPS versus automatic leveling for topographic data collection and DEM generation.
This document summarizes a study that evaluated the accuracy of GPS and automatic level instruments for topographic surveying. Researchers collected elevation data for 25 points in the study area using both a GPS receiver and an automatic level. They then used ArcGIS to create contour maps and digital elevation models from each dataset. The results showed that the GPS data had lower standard deviation and was therefore more accurate than the automatic level data. However, automatic leveling remains a cost-effective method for small study areas. The integration of GPS and GIS techniques allows for efficient processing and analysis of spatial data to produce high accuracy topographic maps and DEMs.
1) The document proposes a knowledge-based multi-agent geo-simulation approach to simulate the deployment of sensor webs in virtual geographic environments.
2) In the approach, sensors are modeled as intelligent agents that can reason about spatial knowledge of the environment and react to dynamic phenomena.
3) Spatial knowledge is represented using conceptual graphs and is used by agents during simulation to support decision making, and after simulation to analyze results and provide decision support to users.
IJERD (www.ijerd.com) International Journal of Engineering Research and Devel...IJERD Editor
This document provides a summary of feature extraction techniques in both the spatial and transformed domains. In the spatial domain, traditional methods like Canny, Sobel, and Harris detectors are discussed. The paper then focuses on the Scale Invariant Feature Transform (SIFT) technique developed by David Lowe, which extracts local features that are invariant to scale, rotation, and illumination changes. Several variants of SIFT are also examined, including PCA-SIFT, ASIFT, and A2SIFT, which improve robustness, distinctiveness, and performance. In the transformed domain section, the document explores techniques that use Fourier and wavelet transforms for feature extraction.
IJERD (www.ijerd.com) International Journal of Engineering Research and Devel...IJERD Editor
This document provides a summary and analysis of various feature extraction techniques in both the spatial and transformed domains. In the spatial domain, traditional methods like Canny, Sobel, and Harris detectors are discussed. The paper then focuses on the Scale Invariant Feature Transform (SIFT) algorithm developed by David Lowe, which extracts key local image features that are invariant to scale, rotation, and illumination changes. Several variants of SIFT are also examined, including PCA-SIFT, ASIFT, and A2SIFT, which improve upon SIFT's robustness and performance. In the transformed domain section, the document explores feature extraction methods that use transforms like the Fourier and wavelet transforms to extract image features.
IJERD (www.ijerd.com) International Journal of Engineering Research and Devel...IJERD Editor
This document provides a summary of feature extraction techniques in both the spatial and transformed domains. In the spatial domain, traditional methods like Canny, Sobel, and Harris detectors are discussed. The paper finds these methods extract too much irrelevant information or lose some prominent features. The Scale Invariant Feature Transform (SIFT) is presented as addressing these issues by detecting local features in a scale and rotation invariant manner. In the transformed domain, techniques using Fourier and wavelet transforms are explored. The paper provides an overview of various feature extraction methods and their advantages and limitations.
This document provides a technical review of secure banking using RSA and AES encryption methodologies. It discusses how RSA and AES are commonly used encryption standards for secure data transmission between ATMs and bank servers. The document first provides background on ATM security measures and risks of attacks. It then reviews related work analyzing encryption techniques. The document proposes using a one-time password in addition to a PIN for ATM authentication. It concludes that implementing encryption standards like RSA and AES can make transactions more secure and build trust in online banking.
This document analyzes the performance of various modulation schemes for achieving energy efficient communication over fading channels in wireless sensor networks. It finds that for long transmission distances, low-order modulations like BPSK are optimal due to their lower SNR requirements. However, as transmission distance decreases, higher-order modulations like 16-QAM and 64-QAM become more optimal since they can transmit more bits per symbol, outweighing their higher SNR needs. Simulations show lifetime extensions up to 550% are possible in short-range networks by using higher-order modulations instead of just BPSK. The optimal modulation depends on transmission distance and balancing the energy used by electronic components versus power amplifiers.
This document provides a review of mobility management techniques in vehicular ad hoc networks (VANETs). It discusses three modes of communication in VANETs: vehicle-to-infrastructure (V2I), vehicle-to-vehicle (V2V), and hybrid vehicle (HV) communication. For each communication mode, different mobility management schemes are required due to their unique characteristics. The document also discusses mobility management challenges in VANETs and outlines some open research issues in improving mobility management for seamless communication in these dynamic networks.
This document provides a review of different techniques for segmenting brain MRI images to detect tumors. It compares the K-means and Fuzzy C-means clustering algorithms. K-means is an exclusive clustering algorithm that groups data points into distinct clusters, while Fuzzy C-means is an overlapping clustering algorithm that allows data points to belong to multiple clusters. The document finds that Fuzzy C-means requires more time for brain tumor detection compared to other methods like hierarchical clustering or K-means. It also reviews related work applying these clustering algorithms to segment brain MRI images.
1) The document simulates and compares the performance of AODV and DSDV routing protocols in a mobile ad hoc network under three conditions: when users are fixed, when users move towards the base station, and when users move away from the base station.
2) The results show that both protocols have higher packet delivery and lower packet loss when users are either fixed or moving towards the base station, since signal strength is better in those scenarios. Performance degrades when users move away from the base station due to weaker signals.
3) AODV generally has better performance than DSDV, with higher throughput and packet delivery rates observed across the different user mobility conditions.
This document describes the design and implementation of 4-bit QPSK and 256-bit QAM modulation techniques using MATLAB. It compares the two techniques based on SNR, BER, and efficiency. The key steps of implementing each technique in MATLAB are outlined, including generating random bits, modulation, adding noise, and measuring BER. Simulation results show scatter plots and eye diagrams of the modulated signals. A table compares the results, showing that 256-bit QAM provides better performance than 4-bit QPSK. The document concludes that QAM modulation is more effective for digital transmission systems.
The document proposes a hybrid technique using Anisotropic Scale Invariant Feature Transform (A-SIFT) and Robust Ensemble Support Vector Machine (RESVM) to accurately identify faces in images. A-SIFT improves upon traditional SIFT by applying anisotropic scaling to extract richer directional keypoints. Keypoints are processed with RESVM and hypothesis testing to increase accuracy above 95% by repeatedly reprocessing images until the threshold is met. The technique was tested on similar and different facial images and achieved better results than SIFT in retrieval time and reduced keypoints.
This document studies the effects of dielectric superstrate thickness on microstrip patch antenna parameters. Three types of probes-fed patch antennas (rectangular, circular, and square) were designed to operate at 2.4 GHz using Arlondiclad 880 substrate. The antennas were tested with and without an Arlondiclad 880 superstrate of varying thicknesses. It was found that adding a superstrate slightly degraded performance by lowering the resonant frequency and increasing return loss and VSWR, while decreasing bandwidth and gain. Specifically, increasing the superstrate thickness or dielectric constant resulted in greater changes to the antenna parameters.
This document describes a wireless environment monitoring system that utilizes soil energy as a sustainable power source for wireless sensors. The system uses a microbial fuel cell to generate electricity from the microbial activity in soil. Two microbial fuel cells were created using different soil types and various additives to produce different current and voltage outputs. An electronic circuit was designed on a printed circuit board with components like a microcontroller and ZigBee transceiver. Sensors for temperature and humidity were connected to the circuit to monitor the environment wirelessly. The system provides a low-cost way to power remote sensors without needing battery replacement and avoids the high costs of wiring a power source.
1) The document proposes a model for a frequency tunable inverted-F antenna that uses ferrite material.
2) The resonant frequency of the antenna can be significantly shifted from 2.41GHz to 3.15GHz, a 31% shift, by increasing the static magnetic field placed on the ferrite material.
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1. IOSR Journal of Computer Engineering (IOSR-JCE)
e-ISSN: 2278-0661,p-ISSN: 2278-8727, Volume 17, Issue 3, Ver. IV (May – Jun. 2015), PP 17-21
www.iosrjournals.org
DOI: 10.9790/0661-17341721 www.iosrjournals.org 17 | Page
A Review of Change Detection Techniques of LandCover Using
Remote Sensing Data
Sonam Ross1
, H.S. Bhadauria2
1
M.Tech (CSE) Scholar, Govind Ballabh Pant Engineering College (Pauri garhwal),
Uttarakhand-246194, India
2
Assistant Professor (CSE), Govind Ballabh Pant Engineering College (Pauri garhwal),
Uttarakhand-246194, India
Abstract:This paper goes to provide an overview of various techniques used for change detection of landcover
with conventional and object based techniques. Now days, progression in remote sensing technologies has
become a great encouragement for the researchers to analyze various changes in landcover to maintain the
environmental balance on the earth surface but due to some addressable issues, it is relatively difficult for
researchers to choose one most effective technique.Change detection techniques are having various limitations
of extent of defining changes, correctness of classification maps to point out the variations and so on. Therefore
several methods have been modeled to prove their effectiveness and accurateness in context of change detection.
This paper starts with illustration of prime issues in change detection procedure; review the elementary
techniques of change detection followed by the recent object oriented methods for change analysis. Study
highlighted the technical soundness of the demonstrated approaches.
Keywords:Change Detection, Forest monitoring, Object-oriented,Remote sensing data.
I. Introduction
The surface of earth is changing day by day that is a matter of great concern for researchers to device
strong methods that able to identify the various fluctuations on earth surface at various temporal and spatial
scales.The prime necessities of researchers to build robust techniques for change analysis are the truthful and
constantly updated data so that through appropriate statistics changes can be analyzed and various
recommendations can be offered. Until now we were dependent on the visual interpretation of ground truth
information and some obsolete conventional methods to demonstrate the landcover changes but now new
automated systems have changed the scenario of the research and latest cutting edge object based techniques
brings theconcept of automation and rapidity. In 1972 Landsat-1 has been launched which manifest the
inauguration of satellite remote sensing for various applications. Satellite centered sensors hold the aptitude to
spot the variations systematically and consistently over time due to their snottyand repetitive data acquisition
abilities.The constant observation of land cover is required to provide the information on various changes on
earth surface and especially define the unit of interaction among various phenomenon provides the basis to use
natural assets in a more better way [1]. Basically the idea of change detection has been defined as „the process
of identifying differences in the state of an object or phenomenon by observing it at different times‟, delivers a
means to understand the phenomena and related concepts of change detection [2]. However the updated
knowledge base about changes in surroundings is very essential to demonstrate the latest trends of specific
changes that would help in designing goal-oriented techniques for change analysis.
The viability and accuracy of various change analysis methods have been explored in past three
decades for different purposes [1, 2, 3].Conventionally, pixel based change detection techniques consider single
pixel as their basic elements of change analysis but recentlywith the arrivalof effectual image analysis
algorithms that integrated the change analysis systems with various segmentation and feature extraction
capabilities from satellite imagery, which in turn facilitatenovel functionalities. The new developments in the
field of image analysis introduced most influential object based change detection approach which has evolved
from the concept of object based change analysis [4, 5]. This technique considers the group of pixels as its basic
unit of functionality. Basically image analysis process begins with elementary segmentation step which cut the
image into desired pieces called image objects followed by various classification processes to identify variations
in the study area. The development in the field of remote sensing technologies has increased the demands of
users for accurate and timely change detection information that remain compatible with different
platforms.Change detection is useful in many applications such as land use changes, habitat fragmentation, rate
of deforestation, coastal change, urban sprawl, and other cumulative changes. The various challenges of
selection of appropriate method, data and study of their limitations still need to be addressed.
2. A Review Of Change Detection Techniques Of Landcover Using Remote Sensing Data
DOI: 10.9790/0661-17341721 www.iosrjournals.org 18 | Page
II. Considerations In Change Detection
Many factors ruled the accuracy of change detection procedure using satellite images. Moreover, there
is not a single technique of change detection that has claimed to be suitable for all scenarios. Each method has
its own pros and cons that must be taken under considerations.There are various issues needs to be understand
while performing change detection, as these issues actually going to affect the accuracy of change detection
method.
2.1 Image acquisition
The most crucial step in the change detection pre-processing is the selection of appropriate data
registration dates so that variations and erroneous results can be avoidedin order to increase the interpretability
of the outcomes as same geographic objects are compared at different points of time [6]. The choice of desired
algorithms, sensors, spatial scale and temporal scale are also very important factors to consider. These factors
also affect the performance of image acquisition and it has been proved that in a particular image, finer spatial
resolution enhance the effects of misregistration on change detection accuracy [7]. Basically spatial scale
defines the size of pixel [8] moreover corresponds to the view window of the scene [9, 10]. At a very important
node it has been considered that satellite imagery with low resolution are able to observe the environmental flux
precisely over large geographical area but several difficulties are encountered in case of mixed pixels to mark
the variations efficiently. However, interested image objects can be outlined from high-spatial-resolution images
more efficiently but with possibility of creation of fake alterations.A further note on high resolution is that with
it, it is more difficult to perform an accurate image registration than by using low resolution, resulting in a
decrease of change detection accuracy.
The concept of image acquisition is also influenced by the temporal scale which corresponds to the
time gap between consecutive acquisitions of the desired site images from same geographic location [11].
Temporal scale is also term as temporal resolution. Several time it has been argued that what kind of images
would be suitable for what kind of region and what would be the correct temporal scale to analyze the
differences in that area. In order to tackle such kind of difficulties analyst first clarify the research objective and
then go for other factors to get expected outcomes.
2.2Viewing geometry and Radiometric correction or normalization
During acquisition of satellite images, there are several factors works to affect the reflectance value of
image objects on the surface of earth such as the value of angle, means at the time of image acquisition what is
the value of angle has been chosen. Basically in ideal situation sensors remain at nadir position so that top view
of the images can be captured but these sensors may tilt accordingly to capture the detailed view of the desired
objects as Quickbird can tilt up to 20 degree [12]. Furthermore, spatial resolution of a particular object is a
significant aspect to consider which is decreased by the different look angles of the sensors in order to collect
more views of that object whereas sun angle is equally important to affect the reflectance of the objects at
different locations. Therefore, it has been suggested that same sensor angle should be selected in order to collect
the object information for change detection [12].There is one more factor calledRadiometric correction which is
also responsible for checkout of the changes as multidate data used for the process of change detection as it
could be the possibility to occur radiance dissimilarities due to atmospheric turbulences and senor‟s improper
working. In order to improve the accuracy of change detection process, different complex radiometric
calibration improvement algorithm not even achieve the target and therefore relative radiometric correction has
taken into consideration to standardize the images bands intensities.
III. Change Detection Techniques Classification
It has been claimed by the researchers that it is very difficult to observe earth surface corresponding to
the changes with satisfactory results [13]. Therefore, so many methods or algorithms have been explored as well
as modified with fast changing remote sensing technologyto notice the changes on earth surface. Basically,
change detection techniques have been divided into two categories that is pre-classification and post-
classification change detection [14, 15]. The techniques that comes under pre-classification category, just extract
minimal information about changes whereas post classification techniques separate changes in detail way with
appropriate attributes [16, 17] but have some limitations of not detecting subtle changes within land cover
classes [18].Here, we tried to describe as many as methodologies including latest object oriented change
detection methods. All methods are equally important and possess their own strengths and weaknesses.The
general structure of the change detection procedure is depicted in fig 1 and several categories of the change
detection have been tabulated in table 1.
Monotemporal Change Delineation outlined the change detection algorithm using pattern recognition
module which acts as functions for it. Existing records are the basis of this approach to represent the condition
of interested area before destructions. Delta classification technique individually creates results of spectral
3. A Review Of Change Detection Techniques Of Landcover Using Remote Sensing Data
DOI: 10.9790/0661-17341721 www.iosrjournals.org 19 | Page
extraction in timely manner, complete change matrix is achieved through separate comparisons of pixels and
segments and finally changes can be defined. This method comes under post-classification category and
advantageous in avoiding radiometric calibration problem of multi date data. Initial classifications are very
important as it determine the accuracy of delta classification. Appropriate classification method selection can
particularize the abrupt changes in desired area [19].Unsatisfactory results can be obtained using delta
classification due to misclassification and misregistration errors [17]. The most effective algorithm for natural
environments is multidimensional temporal feature space analysis to identify the tiny changes but analyst
complained about its less information providing nature about changes [15]. This method uses the concept of
image overlay for pixel enrichment to define the changes. Composite Analysis is a complex method due to
addition of data from two different dates. In this method, combined registration of image data can create
confusion or provide confusing change information where the final decision is based on the decision of each
stage. Image Differencing is robust, easy and most commonly applied algorithm for change detection for
different geographical conditions [2] but requires atmospheric calibration and its same value may represent
ambiguous meaning. Basically, subtraction is the main theme of this method as it subtracts the date 1 image
from date 2 image to create change matrix where positive and negative value means change occur in study area
and zero means no change occur in that particular area.
Fig 1 Change detection procedure
The concept of Image Ratioingcircled around threshold value chosen for change, it is simplest, fast but
may encounter with viewing geometry aspects. The value of ratio is defined by the pixel analysis as unchanged
pixel yield one ratio value and change areas yield ratio value higher or lower than one.Multitemporal linear data
transformation techniques can be successfully applied to data sets from different dates that piled in two different
n-dimensional space where n represents the number of bands comprises in a particular image. Principal
component analysis and tasseled cap are the examples of this technique that are able to find out the minor
transformations in the forest area. Even recently generalize version of tasseled cap has been developed to
improve the functionality of the underlined method [20].Change vector analysis has been considered as the first
automated method to mark the variation. This method produces direction and intensity image of particular
changes where direction image is responsible for detecting change. Moreover, it combines the tasseled cap
transformation and tries to catch the movement of different segments derived from the image in n-dimensional
spectral space in the form of direction and magnitude [21]. It is used in the situation when detailed change
information is required.Image Regression technique makes use of powerful regression function to establish the
relationship between pixel values of multi-date images where changes indicated by the dimension of the
residuals. Furthermore, this technique avoids atmospheric influence and is not able to present change
matrix.Multitemporal Biomass Index method was developed for forest monitoring but it is not able to fulfill the
objective. Background Subtraction techniques were used for observe the deforestation in tropical region. But the
use of both methods was limited as results was not that much efficient and useful [2].
In continuation, some object based change detection algorithms also have been reviewed in order to
highlight the recent advancement in remote sensing field. Image-object change detection algorithm utilize
threshold value in order to compare image-objects like pixel based algorithms perform operations pixel-by-
pixelto determine the exact changes. Spectral values are responsible to analyze the changes in segmented
imagery and direct image comparisons are accentuated in these algorithms.A class-object change detection
Image Selection
Radiometric Corrections
Multitemporal Analysis
Image Registration
Change Detection
4. A Review Of Change Detection Techniques Of Landcover Using Remote Sensing Data
DOI: 10.9790/0661-17341721 www.iosrjournals.org 20 | Page
algorithmclassifies different objects from multi-temporal data independently to determine the detailed variations
where texture and spectral features of the objects are not considered. There are several factors such as viewing
geometry, atmospheric attenuation and so on that can affect the originality of the geographic feature while areas
remain same but at different dates [21].Multitemporal-object change detection algorithm combines sequential
images of same place but taken at different point of time to segment and determine corresponding geographic
changes in the scene.Hybrid change detection algorithmsarea kind of unique category that make use of pixel and
object phenomenon and the concept behind this strategy is that pixels derived the initial changes that further
refined by the object criteria for better understanding of the results.
Table 1.The seven change detection technique categories
Techniquecategories Example of techniques
1 Algebra Based Approach Image differencing
Image regression
Image ratioing
Vegetation index differencing
Change vector analysis
2 Transformation PCA
Tasseled Cap (KT)
Gramm-Schmidt (GS)
Chi-Square
3 Classification Based Post-Classification
Comparison
Spectral-Temporal Combined Analysis
EM Transformation
Unsupervised Change Detection
Hybrid Change Detection
Artificial Neural Networks
4 Advanced Models Li-Strahler Reflectance Model
Spectral Mixture Model
Biophysical Parameter Method
5 GIS Integrated GIS and RS Method
GIS Approach
6 visual Analysis Visual Interpretation
7 other Change Detection Techniques Measures of spatial dependence
Knowledge-based vision system
Area production method
Combination of three indicators: vegetation indices, land surface
temperature, and spatial structure
Change curves
Generalized linear models
Curve-theorem-based approach
Structure-based approach
Spatial statistics-based method
IV. Conclusions
Monitoring of earth surface is possible with the wide range of multi-source remote sensing data and
feasible techniques to observe the alterations. There are lot of methods have been evolved in past decades and
these methods also succeed to produce quality results but automation, cost , time and accuracy is the real
challenge that needs to be meet. In past decade, new object-based techniques have been introduced to overcome
the mentioned shortcomings and up to some level these techniques meet the goal of generating satisfactory
outcomes of change detection with great potential but it does not mean conventional methods are useless, they
are also useful in other context. Object-based methods are highly recommended due to their efficient nature in
presenting detailed change information. The potential of this paradigm can be incorporated with reconsideration
of conventional methods to increase the functionality and it is possible to use both methods simultaneously to
produce results with better precision.This is a wide area of research; all the methods we have discussed above
have great potential and promising capabilities in the field of change detection but still have lot of scope to
develop innovative techniques and methods in order to get effective results of change detection.
References
[1] D. Lu, P.Mausel, E. Brondizioand E. Moran, “Change detection techniques”, International Journal of Remote Sensing, 25, pp.
2365–2407, 2004.
[2] A.Singh, “Digital change detection techniques using remotely-sensed data”, International Journal of Remote Sensing, 10, pp. 898–
1003, 1989.
[3] P.R. Coppin, M.E. Bauer, “Digital change detection in forest ecosystems with remote sensing imagery”, Remote Sensing Reviews,
13, pp. 207–234, 1996.
[4] T.Blaschke, “Towards a framework for change detection based on image objects”,GöttingerGeographischeAbhandlungen, 113, pp.
1–9, 2005.
5. A Review Of Change Detection Techniques Of Landcover Using Remote Sensing Data
DOI: 10.9790/0661-17341721 www.iosrjournals.org 21 | Page
[5] O.Hall, G.J. Hay, “Amultiscale object-specific approach to digital change detection”, International Journal of Applied Earth
Observation and Geoinformation, 4, pp. 311–327, 2003.
[6] J.R.G. Townshend, C.O. Justice, W. Li, C. Gurney, J. Mcmanus, “The impact of misregistration on change detection”, IEEE
Transactions on Geoscience and Remote Sensing, 30, pp. 1054–1060, 1992.
[7] X. Dai, S.Khorram, “The effects of image misregistration on the accuracy of remotely sensed change detection”, IEEE Transactions
on Geoscience and Remote Sensing, 36, pp. 1566–1577, 1998.
[8] C.E.Woodcock, A.H. Strahler, “The factor of scale in remote sensing. Remote Sensing of Environment”,21, pp. 311–332, 1987.
[9] D.J. Marceau, G.J. Hay, “Remote sensing contribution to the scale issue. Canadian Journal of Remote Sensing”, 25, pp. 357–366,
1999.
[10] P. Aplin, “On Scales and dynamics in observing the environment. International Journal of Remote Sensing”, 27, pp. 2123–2140,
2006.
[11] P.M.Mather, “Computer Processing of Remotely-Sensed Images: An Introduction”, 3rd ed. (Chichester: John John Wiley & Sons,
Inc.), 2004
[12] J.R. Jensen, “ Introductory Digital Image Processing”, 3rd ed. (Upper Saddle River, NJ:Pearson Prentice Hall),2005
[13] D. Muchoney, B. Haack, “Change detection for monitoring forest defoliation”, PE & RS- Photogrammetric Engineering & Remote
Sensing, 60(10): 1243-1251, 1994.
[14] R. Nelson, “Detecting forest canopy change due to insect activity using Landsat MSS”, Photogrammetric Engineering and Remote
Sensing, 1983, 49: 1303-1314, 1983.
[15] P. Pilon, P. Howarth, “An enhanced classification approach to change detection in semi-arid environments”, Photogrammetric
Engineering and Remote Sensing, 54: 1709-1716, 1988.
[16] J.Colwell, F. Weber, “Forest change detection”, Proceedings of the 15th International Symposium on Remote Sensing of
Environment, Ann Arbor, MI, USA, ERIM, 1981.
[17] P. Howarth, G. Wickware, “Procedures for change detection using Landsat digital data”, International Journal of Remote Sensing
2(3): 277-291, 1981.
[18] R. Macleod, R. Congalton, “A quantitative comparison of change-detection algorithms for monitoring eelgrass from remotely
sensed data”, Photogrammetric Engineering and Remote Sensing 64(3): 207-216, 1998.
[19] J.E. Colwell, G. Davis, F. Thomson, “Detection and measurement of changes in the productionand quality of renewable resources”,
USDA Forest Service Final Report No. 145300-4-F, ERIM,Ann Arbor, Michigan. 1981.
[20] J.B. Collins, C.E. Woodcock, C.E, “Change detection using the Gramm–Schmidt transformation applied to mapping forest
mortality”, Remote Sensing of Environment, 50, pp. 267–279, 1994.
[21] W. Malila, “Change vector analysis- An approach for detecting forest changes with Landsat”, Machine processing of remotely
sensed data and soil information systems and remote sensing and soil survey: 326-336, 1980.
[22] M.A. Wulder, S.M. Ortlepp, J.C. White, N.C. Coops, N.C, “Impact of sun-surfacesensor geometry upon multitemporalhighspatial
resolution satellite imagery”, Canadian Journal of Remote Sensing, 34, pp. 455–461, 2008a.