IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Combination of Geographic Information System, Fuzzy Set Theory And Analytic H...IRJESJOURNAL
ABSTRACT :- In Hung Ha district, planning new industrial zones along with enlarging the existing ones are the key policies of the authorities. Locations, however, of the planned industrial zones are facing protests of surrounding residential areas because of environmental impacts. The purpose of this research is to assist Hung Ha government in assessing the suitability of planned locations of industrial zones by utilizing the combinations of Geographic Information System (GIS) technology, Analytic Hierarchy Process (AHP) technique and Fuzzy set theory. Firstly, opinions were surveyed from people residing near planned locations for determining which problems were complained mostly, and subsequently consulted suggestions from the authorities to form affected factors table. Secondly, AHP was applied for calculating weights of criteria and factors, and Fuzzy set theory was employed for obtaining continuous score of relevant degree from 0 to 1. GIS technology was applied throughout the paper from standardizing input spatial data to overlapping layers. The assessment results revealed that all 18 planned industrial zones in the researched district were not rational because of close to residential areas or water sources.
This document describes a practical demonstration on using GIS for land suitability mapping for precision farming. The goals of the demonstration are to identify areas suitable, moderately suitable, and highly suitable for crop production based on soil characteristics. The demonstration will use ArcGIS to interpolate soil property rasters from sample data, reclassify the rasters into classes, overlay the reclassified rasters to combine criteria, and label the final overlay classes as the soil suitability map.
USING THE ANALYTIC HIERARCHY PROCESS AND GIS FOR DECISION MAKING IN RURAL HIG...IAEME Publication
Rural highway route location is a very complex case, requiring significant time and effort from the planners. This study presented the route location method by applying Analytic Hierarchy Process (AHP) and Geographical Information System (GIS). The location of the study is confined to south Mosul city in Iraq of the area (198km2). The researcher is behind defining the route which connects Baghdad-Mosul and Mosul-Kirkuk roadways. This route is considered the suggested turn to Mosul city. A variety of data set from different sources and at different scales are managed.
Spatial analysis for the assessment of the environmental changes in the lands...Universität Salzburg
Presented research is focused on the spatial analysis aimed at the assessment of the environmental changes in the landscapes of Izmir surroundings, Turkey. Methods include Landsat TM images classification using Erdas Imagine, clustering segmentation and classification, verification via the Google Earth and GIS Mapping. Tme span is 13-years (1987-2000). Images were taken from the Global Land Cover Facility (GLCF) Earth Science Data Interface. The selected area of Izmir has the most diverse landscape structure and high heterogeneity of the land cover types. Accuracy results computed. Kappa statistics for the image 2000: 0.7843, for the image 1987: 0.7923. The classification of the image 1987: accuracy 81.25%, 2000: 80,47%. The results indicate changes in land cover types affected by human activities, i.e. increased agricultural areas. Results include following findings. 1987: croplands (wheat) covered 71% of the today’s area (2000): 2382 vs. 3345 ha. Increase in barley cropland areas is noticeable as well: 1149 ha in 1987 vs. 4423 ha in 2000. Sparsely vegetated areas now also occupy more areas : 5914 ha in 2000 against 859 ha in 1987. Natural vegetation, decreased, which can be explained by the expansion of the agricultural lands. 1987: coppice areas covered 5500 ha while later on there are only 700 ha in this land type.
This document discusses key properties of spatial data including projection, accuracy, scale, and resolution. It defines projection as the conversion of 3D earth coordinates to a 2D map representation using mathematical formulas. Accuracy refers to how closely a map matches real-world values, which can be measured horizontally, vertically, or relatively. Scale compares distances on a map to actual distances on earth. Resolution is the smallest feature that can be recognized on a map.
This document provides an overview of geographic information system (GIS) analysis functions. It discusses several types of analysis that GIS is used for, including selection and measurement, overlay analysis, neighbourhood operations, and connectivity analysis. Overlay analysis allows for spatially interrelating multiple data layers and is one of the most important GIS functions. Neighbourhood operations consider characteristics of surrounding areas, such as through buffering or interpolation. Overall, the document outlines the key spatial analysis techniques that GIS provides for examining geographic data patterns and relationships.
This study analyzed land use and land cover changes around a mined area in Kannur district, Kerala, India between 2000 and 2017 using satellite imagery. Support vector machine classification identified five land cover classes: vegetation, barren land, built up area, mining area, and waterbodies. In 2000, vegetation covered 51.34% of the area, followed by barren land at 31.75%. By 2017, vegetation increased to 58.46% while barren land decreased to 19.98%. The mining area saw little change, increasing vertically within the same area. Comparing land cover changes over time can help sustainable environmental management near mined regions.
Combination of Geographic Information System, Fuzzy Set Theory And Analytic H...IRJESJOURNAL
ABSTRACT :- In Hung Ha district, planning new industrial zones along with enlarging the existing ones are the key policies of the authorities. Locations, however, of the planned industrial zones are facing protests of surrounding residential areas because of environmental impacts. The purpose of this research is to assist Hung Ha government in assessing the suitability of planned locations of industrial zones by utilizing the combinations of Geographic Information System (GIS) technology, Analytic Hierarchy Process (AHP) technique and Fuzzy set theory. Firstly, opinions were surveyed from people residing near planned locations for determining which problems were complained mostly, and subsequently consulted suggestions from the authorities to form affected factors table. Secondly, AHP was applied for calculating weights of criteria and factors, and Fuzzy set theory was employed for obtaining continuous score of relevant degree from 0 to 1. GIS technology was applied throughout the paper from standardizing input spatial data to overlapping layers. The assessment results revealed that all 18 planned industrial zones in the researched district were not rational because of close to residential areas or water sources.
This document describes a practical demonstration on using GIS for land suitability mapping for precision farming. The goals of the demonstration are to identify areas suitable, moderately suitable, and highly suitable for crop production based on soil characteristics. The demonstration will use ArcGIS to interpolate soil property rasters from sample data, reclassify the rasters into classes, overlay the reclassified rasters to combine criteria, and label the final overlay classes as the soil suitability map.
USING THE ANALYTIC HIERARCHY PROCESS AND GIS FOR DECISION MAKING IN RURAL HIG...IAEME Publication
Rural highway route location is a very complex case, requiring significant time and effort from the planners. This study presented the route location method by applying Analytic Hierarchy Process (AHP) and Geographical Information System (GIS). The location of the study is confined to south Mosul city in Iraq of the area (198km2). The researcher is behind defining the route which connects Baghdad-Mosul and Mosul-Kirkuk roadways. This route is considered the suggested turn to Mosul city. A variety of data set from different sources and at different scales are managed.
Spatial analysis for the assessment of the environmental changes in the lands...Universität Salzburg
Presented research is focused on the spatial analysis aimed at the assessment of the environmental changes in the landscapes of Izmir surroundings, Turkey. Methods include Landsat TM images classification using Erdas Imagine, clustering segmentation and classification, verification via the Google Earth and GIS Mapping. Tme span is 13-years (1987-2000). Images were taken from the Global Land Cover Facility (GLCF) Earth Science Data Interface. The selected area of Izmir has the most diverse landscape structure and high heterogeneity of the land cover types. Accuracy results computed. Kappa statistics for the image 2000: 0.7843, for the image 1987: 0.7923. The classification of the image 1987: accuracy 81.25%, 2000: 80,47%. The results indicate changes in land cover types affected by human activities, i.e. increased agricultural areas. Results include following findings. 1987: croplands (wheat) covered 71% of the today’s area (2000): 2382 vs. 3345 ha. Increase in barley cropland areas is noticeable as well: 1149 ha in 1987 vs. 4423 ha in 2000. Sparsely vegetated areas now also occupy more areas : 5914 ha in 2000 against 859 ha in 1987. Natural vegetation, decreased, which can be explained by the expansion of the agricultural lands. 1987: coppice areas covered 5500 ha while later on there are only 700 ha in this land type.
This document discusses key properties of spatial data including projection, accuracy, scale, and resolution. It defines projection as the conversion of 3D earth coordinates to a 2D map representation using mathematical formulas. Accuracy refers to how closely a map matches real-world values, which can be measured horizontally, vertically, or relatively. Scale compares distances on a map to actual distances on earth. Resolution is the smallest feature that can be recognized on a map.
This document provides an overview of geographic information system (GIS) analysis functions. It discusses several types of analysis that GIS is used for, including selection and measurement, overlay analysis, neighbourhood operations, and connectivity analysis. Overlay analysis allows for spatially interrelating multiple data layers and is one of the most important GIS functions. Neighbourhood operations consider characteristics of surrounding areas, such as through buffering or interpolation. Overall, the document outlines the key spatial analysis techniques that GIS provides for examining geographic data patterns and relationships.
This study analyzed land use and land cover changes around a mined area in Kannur district, Kerala, India between 2000 and 2017 using satellite imagery. Support vector machine classification identified five land cover classes: vegetation, barren land, built up area, mining area, and waterbodies. In 2000, vegetation covered 51.34% of the area, followed by barren land at 31.75%. By 2017, vegetation increased to 58.46% while barren land decreased to 19.98%. The mining area saw little change, increasing vertically within the same area. Comparing land cover changes over time can help sustainable environmental management near mined regions.
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.
Performance of RGB and L Base Supervised Classification Technique Using Multi...IJERA Editor
In the present growth of sensor technology is to improve the new chance and applications in GIS. This enhances the technology law a new method that should not focus on real time available products, but it must automatically lead to new ones. The aim of the paper is to make a maximum use of remote sensing data and GIS techniques to access land use and land cover classification in the Kiliyar sub basin sector in palar river of northen part of Tamil Nadu.IRS P6 LISS III is merged data to perform the classification using ERDAS Imaging. The RGB and L base supervised classification was based up on a Multispectral analysis, land use and land cover information‟s (maps and existing reports), which involves advanced technology and complex data processing to find detailed imagery in the study region. Ground surface reflects more radar energy emitted by the sensor from the study region, which makes it easy to distinguish between the water body, hilly, agriculture, settlement and wetland.
The document describes the development of a soil suitability map for geotechnical applications in South Chennai, India using a GIS approach. Borehole data was collected and analyzed to create maps of parameters like N-value, groundwater table, and bearing capacity. A geotechnical database was developed using Microsoft Access to organize the soil data. Statistical analysis was conducted to quantify spatial variability in soil properties. Regression analysis was used to develop relationships between N-value and other geotechnical parameters. The database and maps created can provide guidance on spatial continuity of soil properties in South Chennai and support planning and site investigation work.
The document compares the use of ordinary least squares (OLS) regression and geographically weighted regression (GWR) to model and estimate electricity distribution patterns using land use and demographic data. OLS regression provided moderately good results with an R2 value of 31.9% but showed spatial autocorrelation. GWR accounted for spatial non-stationarity and provided better results with an R2 of 51.65%. GWR also had a lower Akaike information criterion score, indicating it was a better model. The study area of Manali, India was classified into land use types from satellite imagery and population growth was also considered. GWR was found to provide a more effective model for estimating patterns of low tension electricity distribution networks
An overlay operation is much more than a simple merging of linework; all the attributes of the features taking part in the overlay are carried through. In general, there are two methods for performing overlay analysis—feature overlay (overlaying points, lines, or polygons) and raster overlay. Some types of overlay analysis lend themselves to one or the other of these methods. Overlay analysis to find locations meeting certain criteria is often best done using raster overlay (although you can do it with feature data). Of course, this also depends on whether your data is already stored as features or raster. It may be worthwhile to convert the data from one format to the other to perform the analysis.
Weighted Overlay
Overlays several raster files using a common measurement scale and weights each according to its importance.
The weighted overlay table allows the calculation of a multiple criteria analysis between several raster files.
Raster- The raster of the criteria being weighted.
Influence- The influence of the raster compared to the other criteria as a percentage of 100.
Field- The field of the criteria raster to use for weighting.
Remap- The scaled weights for the criterion.
In addition to numerical values for the scaled weights in Remap, the following options are available:
Restricted- Assigns the restricted value (the minimum value of the evaluation scale set, minus one) to cells in the output, regardless of whether other input raster files have a different scale value set for that cell.
No data - Assigns No Data to cells in the output, regardless of whether other input raster files have a different scale value set for that cell.
THIS PRESENTATION IS TO HELP YOU PERFORM THE TASK STEP BY STEP.
A Classification Urban Precinct Ventilation Zones using Key Indicators of Spa...Manat Srivanit
Session 6-Urban Planning and Development
2021 4th International Conference on Civil Engineering and Architecture (Virtual Conference): July 10-12, 2021; Seoul, South Korea
IRJET- Land Cover Index Classification using Satellite Images with Different ...IRJET Journal
This document presents a study on land cover index classification of satellite images of the Ayeyarwaddy Delta region of Myanmar. The study uses Google Earth satellite images from 2004-2014. The images are classified into three indices: buildings, vegetation, and roads. Three image enhancement methods are applied prior to classification - V-channel enhancement, histogram equalization, and adaptive histogram equalization. K-means clustering is then used to classify the enhanced images into the three indices in CIE L*a*b* color space. The classification results of each enhancement method are evaluated and compared using mean squared error and peak signal-to-noise ratio. According to the results, V-channel enhancement provides the best classification results compared to
This document describes a study that used multi-criteria decision analysis (MCDA) to select suitable sites for nuclear power plants in Egypt. Six constraints and twenty-two factors related to safety, environment, and socioeconomics were considered. Three MCDA models were applied: 1) binary overlay to identify candidate areas by eliminating constrained lands, 2) weighted linear combination to produce potential site maps based on factor weights, and 3) analytic hierarchy process to rank four candidate sites on the northwest and Red Sea coasts. The study found El Dabaa site to be most suitable followed by East El Negila site.
Landuse landcover and ndvi analysis for halia catchmentIAEME Publication
This document summarizes a study analyzing land use/land cover changes and normalized difference vegetation index (NDVI) for the Halia catchment area in India over several decades using remote sensing data. Medium to high resolution Landsat satellite imagery from 1975, 1989, and 2001 was processed to create land use/land cover maps and NDVI maps for the area. The objective was to examine changes in cropped area and land use/land cover patterns over time and understand the implications for the local environment.
IRJET-Evaluation of the Back Propagation Neural Network for Gravity Mapping IRJET Journal
This document evaluates the ability of back propagation neural networks (BPN) to produce gravity maps. The study trained a BPN model with 646 patterns from a gravity map and satellite image of Khartoum City. The trained model was tested on the training patterns and 162 new patterns. The results showed that the BPN model was unable to produce an accurate gravity map. Therefore, the BPN architecture is not suitable for this application of artificial intelligence in gravity mapping.
A comparison of Land Cover Change in Kaski District, NepalBijesh Mishra
Kaski, one the major cities of Nepal, major tourism place and regional headquarter of Western Development
region, attracts large population from surrounding resulting 36.4% increase in population proportion and thus, land cover
is rapidly changing in the area. The research intended to find land cover change over nine years from 2000 to 2009 as well
as possible reason for the land cover change. Landsat images were obtained from USGS Glovis, National boundary data
was clipped and dissolved selecting study area, and demographic data were obtained from Central Bureau of Statistics,
Nepal for the research. Data was analyzed using Supervised Classification method with maximum likelihood parameter.
From the result, it is concluded that the urban area has increased by 47.86% in study area with the decrease in forest area
by 26.25%. The possible reason for the land cover change can be attributed to rapid increase in population growth and
rapid urbanization. Also, decrease in water resource and barren land can also be accounted to rapid urbanization and
rapid change in land use pattern though research provides sufficient room for further research in this area of study
Accuracy enhancement of srtm and aster dems using weight estimation regressio...eSAT Publishing House
This document assesses the accuracy of SRTM and ASTER DEMs in Egypt by comparing DEM elevations to GPS ground control points (GCPs) in two study areas with different topography: a flat delta region and a hilly desert region. Root mean square errors (RMSEs) for SRTM ranged from 15.6m in the delta to 7.9m in the desert, and for ASTER ranged from 13.2m in the delta to 12.4m in the desert. A new approach using weight estimation regression models with topographic indices and aspects as predictors improved accuracy, reducing standard errors of estimates.
Hydrological mapping of the vegetation using remote sensing productsNycoSat
This document presents a new method for hydrological mapping of vegetation using remote sensing products. The method is based on the Forest Canopy Density model and uses vegetation indexes like Advanced Vegetation Index, Bare Soil Index, and Shadow Index calculated from Landsat TM satellite imagery. These indexes are classified and combined to categorize vegetation into hydrological classes. The method was tested in Upper Tărlung Watershed and showed high correlation with traditional methods, providing an accurate and up-to-date alternative for hydrological mapping.
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.
Application of GIS in Mine Contamination and Associated Environmental ImpactsArsalan Syed, PMP
This document discusses the application of GIS and remote sensing methods to measure environmental impacts from mining contamination. It outlines two case studies where GIS was used: 1) A study in Turkey that generated DEM and flow accumulation maps from ASTER satellite imagery to identify trace element contamination patterns from an abandoned coal mine. Higher concentrations were found along flow pathways downstream from contamination sources. 2) A study with the Navajo tribe that created water hauling and soil restriction maps using GIS to develop an effective risk communication strategy about uranium exposures from abandoned mines. The maps aided risk understanding but language barriers remained a limitation. In conclusion, remote sensing and GIS provide low-cost alternatives for mapping contamination to inform remediation efforts.
Classification accuracy analyses using Shannon’s EntropyIJERA Editor
There are many methods for determining the Classification Accuracy. In this paper significance of Entropy of
training signatures in Classification has been shown. Entropy of training signatures of the raw digital image
represents the heterogeneity of the brightness values of the pixels in different bands. This implies that an image
comprising a homogeneous lu/lc category will be associated with nearly the same reflectance values that would
result in the occurrence of a very low entropy value. On the other hand an image characterized by the
occurrence of diverse lu/lc categories will consist of largely differing reflectance values due to which the
entropy of such image would be relatively high. This concept leads to analyses of classification accuracy.
Although Entropy has been used many times in RS and GIS but its use in determination of classification
accuracy is new approach.
Estimation of Spatial Variability of Land Surface Temperature using Landsat 8...theijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
Assessment of Urban Green Space Structures and Its Effect on Land Surface Tem...Manat Srivanit
Presentation in the 2019 2nd International Conference on Civil Engineering and Architecture on September 21-23, 2019, Seoul National University, South Korea
This document summarizes hyperspectral image classification. It begins by introducing hyperspectral imagery, noting that these images contain narrow spectral bands over a continuous spectral range, capturing characteristics of electromagnetic radiation. The document then discusses supervised and unsupervised classification techniques. Supervised classification involves identifying training samples to develop statistical characterizations of information classes. Unsupervised classification partitions images into homogeneous spectral clusters. The document focuses on supervised classification and discusses support vector machines, a commonly used algorithm that maps data into a higher dimensional space to perform linear classification.
A aula de Língua Portuguesa irá analisar a obra "O Tempo e o Vento" do escritor gaúcho Érico Veríssimo, identificando variações linguísticas regionais e socioculturais e comparando trechos do texto com partes do filme para entender melhor o vocabulário e contexto histórico e geográfico retratados.
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.
Performance of RGB and L Base Supervised Classification Technique Using Multi...IJERA Editor
In the present growth of sensor technology is to improve the new chance and applications in GIS. This enhances the technology law a new method that should not focus on real time available products, but it must automatically lead to new ones. The aim of the paper is to make a maximum use of remote sensing data and GIS techniques to access land use and land cover classification in the Kiliyar sub basin sector in palar river of northen part of Tamil Nadu.IRS P6 LISS III is merged data to perform the classification using ERDAS Imaging. The RGB and L base supervised classification was based up on a Multispectral analysis, land use and land cover information‟s (maps and existing reports), which involves advanced technology and complex data processing to find detailed imagery in the study region. Ground surface reflects more radar energy emitted by the sensor from the study region, which makes it easy to distinguish between the water body, hilly, agriculture, settlement and wetland.
The document describes the development of a soil suitability map for geotechnical applications in South Chennai, India using a GIS approach. Borehole data was collected and analyzed to create maps of parameters like N-value, groundwater table, and bearing capacity. A geotechnical database was developed using Microsoft Access to organize the soil data. Statistical analysis was conducted to quantify spatial variability in soil properties. Regression analysis was used to develop relationships between N-value and other geotechnical parameters. The database and maps created can provide guidance on spatial continuity of soil properties in South Chennai and support planning and site investigation work.
The document compares the use of ordinary least squares (OLS) regression and geographically weighted regression (GWR) to model and estimate electricity distribution patterns using land use and demographic data. OLS regression provided moderately good results with an R2 value of 31.9% but showed spatial autocorrelation. GWR accounted for spatial non-stationarity and provided better results with an R2 of 51.65%. GWR also had a lower Akaike information criterion score, indicating it was a better model. The study area of Manali, India was classified into land use types from satellite imagery and population growth was also considered. GWR was found to provide a more effective model for estimating patterns of low tension electricity distribution networks
An overlay operation is much more than a simple merging of linework; all the attributes of the features taking part in the overlay are carried through. In general, there are two methods for performing overlay analysis—feature overlay (overlaying points, lines, or polygons) and raster overlay. Some types of overlay analysis lend themselves to one or the other of these methods. Overlay analysis to find locations meeting certain criteria is often best done using raster overlay (although you can do it with feature data). Of course, this also depends on whether your data is already stored as features or raster. It may be worthwhile to convert the data from one format to the other to perform the analysis.
Weighted Overlay
Overlays several raster files using a common measurement scale and weights each according to its importance.
The weighted overlay table allows the calculation of a multiple criteria analysis between several raster files.
Raster- The raster of the criteria being weighted.
Influence- The influence of the raster compared to the other criteria as a percentage of 100.
Field- The field of the criteria raster to use for weighting.
Remap- The scaled weights for the criterion.
In addition to numerical values for the scaled weights in Remap, the following options are available:
Restricted- Assigns the restricted value (the minimum value of the evaluation scale set, minus one) to cells in the output, regardless of whether other input raster files have a different scale value set for that cell.
No data - Assigns No Data to cells in the output, regardless of whether other input raster files have a different scale value set for that cell.
THIS PRESENTATION IS TO HELP YOU PERFORM THE TASK STEP BY STEP.
A Classification Urban Precinct Ventilation Zones using Key Indicators of Spa...Manat Srivanit
Session 6-Urban Planning and Development
2021 4th International Conference on Civil Engineering and Architecture (Virtual Conference): July 10-12, 2021; Seoul, South Korea
IRJET- Land Cover Index Classification using Satellite Images with Different ...IRJET Journal
This document presents a study on land cover index classification of satellite images of the Ayeyarwaddy Delta region of Myanmar. The study uses Google Earth satellite images from 2004-2014. The images are classified into three indices: buildings, vegetation, and roads. Three image enhancement methods are applied prior to classification - V-channel enhancement, histogram equalization, and adaptive histogram equalization. K-means clustering is then used to classify the enhanced images into the three indices in CIE L*a*b* color space. The classification results of each enhancement method are evaluated and compared using mean squared error and peak signal-to-noise ratio. According to the results, V-channel enhancement provides the best classification results compared to
This document describes a study that used multi-criteria decision analysis (MCDA) to select suitable sites for nuclear power plants in Egypt. Six constraints and twenty-two factors related to safety, environment, and socioeconomics were considered. Three MCDA models were applied: 1) binary overlay to identify candidate areas by eliminating constrained lands, 2) weighted linear combination to produce potential site maps based on factor weights, and 3) analytic hierarchy process to rank four candidate sites on the northwest and Red Sea coasts. The study found El Dabaa site to be most suitable followed by East El Negila site.
Landuse landcover and ndvi analysis for halia catchmentIAEME Publication
This document summarizes a study analyzing land use/land cover changes and normalized difference vegetation index (NDVI) for the Halia catchment area in India over several decades using remote sensing data. Medium to high resolution Landsat satellite imagery from 1975, 1989, and 2001 was processed to create land use/land cover maps and NDVI maps for the area. The objective was to examine changes in cropped area and land use/land cover patterns over time and understand the implications for the local environment.
IRJET-Evaluation of the Back Propagation Neural Network for Gravity Mapping IRJET Journal
This document evaluates the ability of back propagation neural networks (BPN) to produce gravity maps. The study trained a BPN model with 646 patterns from a gravity map and satellite image of Khartoum City. The trained model was tested on the training patterns and 162 new patterns. The results showed that the BPN model was unable to produce an accurate gravity map. Therefore, the BPN architecture is not suitable for this application of artificial intelligence in gravity mapping.
A comparison of Land Cover Change in Kaski District, NepalBijesh Mishra
Kaski, one the major cities of Nepal, major tourism place and regional headquarter of Western Development
region, attracts large population from surrounding resulting 36.4% increase in population proportion and thus, land cover
is rapidly changing in the area. The research intended to find land cover change over nine years from 2000 to 2009 as well
as possible reason for the land cover change. Landsat images were obtained from USGS Glovis, National boundary data
was clipped and dissolved selecting study area, and demographic data were obtained from Central Bureau of Statistics,
Nepal for the research. Data was analyzed using Supervised Classification method with maximum likelihood parameter.
From the result, it is concluded that the urban area has increased by 47.86% in study area with the decrease in forest area
by 26.25%. The possible reason for the land cover change can be attributed to rapid increase in population growth and
rapid urbanization. Also, decrease in water resource and barren land can also be accounted to rapid urbanization and
rapid change in land use pattern though research provides sufficient room for further research in this area of study
Accuracy enhancement of srtm and aster dems using weight estimation regressio...eSAT Publishing House
This document assesses the accuracy of SRTM and ASTER DEMs in Egypt by comparing DEM elevations to GPS ground control points (GCPs) in two study areas with different topography: a flat delta region and a hilly desert region. Root mean square errors (RMSEs) for SRTM ranged from 15.6m in the delta to 7.9m in the desert, and for ASTER ranged from 13.2m in the delta to 12.4m in the desert. A new approach using weight estimation regression models with topographic indices and aspects as predictors improved accuracy, reducing standard errors of estimates.
Hydrological mapping of the vegetation using remote sensing productsNycoSat
This document presents a new method for hydrological mapping of vegetation using remote sensing products. The method is based on the Forest Canopy Density model and uses vegetation indexes like Advanced Vegetation Index, Bare Soil Index, and Shadow Index calculated from Landsat TM satellite imagery. These indexes are classified and combined to categorize vegetation into hydrological classes. The method was tested in Upper Tărlung Watershed and showed high correlation with traditional methods, providing an accurate and up-to-date alternative for hydrological mapping.
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.
Application of GIS in Mine Contamination and Associated Environmental ImpactsArsalan Syed, PMP
This document discusses the application of GIS and remote sensing methods to measure environmental impacts from mining contamination. It outlines two case studies where GIS was used: 1) A study in Turkey that generated DEM and flow accumulation maps from ASTER satellite imagery to identify trace element contamination patterns from an abandoned coal mine. Higher concentrations were found along flow pathways downstream from contamination sources. 2) A study with the Navajo tribe that created water hauling and soil restriction maps using GIS to develop an effective risk communication strategy about uranium exposures from abandoned mines. The maps aided risk understanding but language barriers remained a limitation. In conclusion, remote sensing and GIS provide low-cost alternatives for mapping contamination to inform remediation efforts.
Classification accuracy analyses using Shannon’s EntropyIJERA Editor
There are many methods for determining the Classification Accuracy. In this paper significance of Entropy of
training signatures in Classification has been shown. Entropy of training signatures of the raw digital image
represents the heterogeneity of the brightness values of the pixels in different bands. This implies that an image
comprising a homogeneous lu/lc category will be associated with nearly the same reflectance values that would
result in the occurrence of a very low entropy value. On the other hand an image characterized by the
occurrence of diverse lu/lc categories will consist of largely differing reflectance values due to which the
entropy of such image would be relatively high. This concept leads to analyses of classification accuracy.
Although Entropy has been used many times in RS and GIS but its use in determination of classification
accuracy is new approach.
Estimation of Spatial Variability of Land Surface Temperature using Landsat 8...theijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
Assessment of Urban Green Space Structures and Its Effect on Land Surface Tem...Manat Srivanit
Presentation in the 2019 2nd International Conference on Civil Engineering and Architecture on September 21-23, 2019, Seoul National University, South Korea
This document summarizes hyperspectral image classification. It begins by introducing hyperspectral imagery, noting that these images contain narrow spectral bands over a continuous spectral range, capturing characteristics of electromagnetic radiation. The document then discusses supervised and unsupervised classification techniques. Supervised classification involves identifying training samples to develop statistical characterizations of information classes. Unsupervised classification partitions images into homogeneous spectral clusters. The document focuses on supervised classification and discusses support vector machines, a commonly used algorithm that maps data into a higher dimensional space to perform linear classification.
A aula de Língua Portuguesa irá analisar a obra "O Tempo e o Vento" do escritor gaúcho Érico Veríssimo, identificando variações linguísticas regionais e socioculturais e comparando trechos do texto com partes do filme para entender melhor o vocabulário e contexto histórico e geográfico retratados.
Jamie Tan is a Malaysian professional with over 10 years of experience in banking, manufacturing quality systems, and research. She holds a Master's degree in Management from Universiti Sains Malaysia and a Bachelor's degree in bio-resource technology. Her key skills include data analysis, Microsoft Office proficiency, and fluency in English, Chinese, and Malay. In her spare time she enjoys reading, cooking, and playing squash.
O documento descreve uma parceria público-privada proposta entre a prefeitura de Caruaru e uma empresa privada para melhorar a eficiência energética da iluminação pública municipal. A prefeitura pretende delegar à empresa privada a gestão da iluminação pública e energia elétrica, com investimentos de R$70 milhões para substituir as lâmpadas por LEDs mais econômicos.
El documento describe el proceso de consulta a los pueblos indígenas establecido por el gobierno peruano para proyectos mineros y energéticos. Señala que las entidades del sector energía y minas deben consultar a los pueblos indígenas que puedan ser afectados directamente por nuevos proyectos, de acuerdo con el Convenio 169 de la OIT y la legislación peruana. El proceso incluye identificar a los pueblos afectados, informarles sobre los proyectos propuestos, y realizar consultas para lleg
Este relatório analisa as menções à presidente Dilma Rousseff no Twitter entre 7 e 13 de fevereiro de 2014. Foram monitorados os termos "Dilma cuba", "fidel dilma" e "porto dilma cuba", mas nenhum tweet foi classificado como positivo, negativo ou importante para esses termos.
Expositores: Chacaltana, César; Valdivia, Waldir; Morales, María / XV Congreso Peruano de Geología
01/01/2010
/ Resumen y Objetivos En secuencias clásticas de la Fm. Los Choros, expuestas en la Cuenca Pisco sector oriental (localidad de Ullujalla, departamento de Ica), se han encontrado foraminíferos grandes de la familia LEPIDOCYCLINIDAE, los cuales constituyen importantes marcadores bioestratigráficos
El documento describe el Sistema de Información Geológico y Catastral Minero (GEOCATMIN) del Instituto Geológico Minero y Metalúrgico del Perú (INGEMMET). GEOCATMIN proporciona información geológica y sobre derechos mineros a través de un visor web interoperable. El sistema almacena datos geocientíficos y sobre evaluación de derechos mineros en una base de datos corporativa. El visor web ofrece nuevas funcionalidades como indicadores y ha registrado más de 27 millones de interacciones desde mayo de
O poema reflete sobre como o tempo passa rapidamente e como as oportunidades na vida são perdidas quando não aproveitadas no momento. O autor sugere que as pessoas não devem deixar de fazer o que gostam ou estar com quem amam por medo de falta de tempo, já que este é um recurso que nunca retorna.
Ronak Patel is seeking a career opportunity with a leading corporate company. He has over 3 years of experience working as a contract engineer for maintenance at United Phosphorus Limited in Gujarat, India. His responsibilities there include preventative maintenance, breakdown handling, daily operations, troubleshooting, and managing equipment such as reactors, pumps, dryers, filters, heat exchangers, tanks, and more. Ronak holds a B.Tech in Mechanical Engineering and is proficient in English, Hindi, and Gujarati.
This document provides a research proposal to analyze citizen perception of participation in governance of urban water supply systems in Bangalore, India. The study will explore how the Bangalore Water Supply and Sewerage Board (BWSSB) allows citizen participation and the role of information and communication technologies (ICT) in improving participation. It reviews literature on the importance of citizen involvement in decision making for equitable and sustainable water systems. The conceptual framework assesses current conditions, explores areas of citizen participation and ICT applications used, analyzes generated data, and proposes verifying participation through a cyclic approach to address changing urban dynamics.
Multi-Criteria Decision Making in Hotel Site Selection inventionjournals
In the Multi Criteria Decision-Making (MCDM) context, the selection is facilitated by evaluating each choice on the set of criteria. The criteria must be measurable and their outcomes must be measured for every decision alternative. In This Paper the decision making process frame work was developed to provide Hotel site suitability map. Road, river , built up areas n and the Available area were prepared as layers in ArcGIS 10.2 to create suitability model for development area. The results of this analysis indicated that 41% of the study area is considered as the most suitable place for hotel site selection, 33% of the area as moderately suitable and 21% percent as marginally suitable. A portion of 5% was found to be not suitable areas for hotel site selection
MULTICRITERIA DECISION AIDED SYSTEM FOR RANKING INDUSTRIAL ZONES (RPRO4SIGZI) cscpconf
Integration of Geographic Information Systems (GIS) and multi-criteria decision analysis (MCDA) is a privileged and indispensable way to evolve GIS into real decision support systems. RPRO4SIGZI, the system proposed in this paper allows, from a detailed study of geographical, environmental and socioe-conomic criteria to cooperate GIS and multi-criteria decision analysis method for spatial choosing of the right site for installing industrial projects. The result obtained by RPRO (Ranking PROMETHEE) for ranking industrial zones in western Algeria is refined by a viewing SIGZI (Geographic Information System for Industrial Zones). The RPRO unit rank industrial zones using the outranking PROMETHEE II method issue from European school and SIGZI module to the visualization of these zones on the map. RPRO4SIGZI system was designed for the evaluation of a new methodology of multi-criteria analysis guided by data mining. The objective is to show how data mining is used to model the preferences of the decision maker tainted with subjectivity and hesitance to generate suitable performance tables. Only RPRO4SIGZI system is presented in this paper.
IJCER (www.ijceronline.com) International Journal of computational Engineerin...ijceronline
The document summarizes research on using analytical hierarchy process (AHP) to evaluate environmental factors for determining residential land use suitability. AHP was used to determine weights for various environmental criteria like water availability, flood risk, air pollution, water quality, and distance from waste sites. Spatial data and maps of these factors were analyzed and overlaid based on the AHP weights to produce a final residential land suitability map for the study area of Pimpri-Chinchwad, India. The methodology involved structuring the decision problem hierarchically, making pairwise comparisons to obtain weights, and aggregating weighted criteria maps to determine overall suitability.
Plant location selection by using MCDM methodsIJERA Editor
Plant location selection has a critical impact on the performance of manufacturing companies. The cost associated with acquiring the land and facility construction makes the location selection a long-term investment decision. The preeminent location is that which results in higher economic benefits through increased productivity and good distribution network. Both potential qualitative and quantitative criteria’s are to be considered for selecting the proper plant location from a given set of alternatives. Consequently, from the literature survey, it is found that the Multi criteria decision-making (MCDM) is found to be an effective approach to solve the location selection problems. In the present research, an integrated decision-making methodology is designed which employs the two well-known decision making techniques, namely Analytical hierarchy process (AHP), and Preference ranking organization method for enrichment evaluations (PROMETHEE-II) in order to make the best use of information available, either implicitly or explicitly. It is analyze the structure for the solution of plant location problems and to obtain weights of the selected criteria’s. PROMETHEE-II is employed to solve decision-making problems with multiple conflicting criteria and alternatives.
A Combined Entropy-FR Weightage Formulation Model for Delineation of Groundwa...IRJET Journal
This document presents a study that develops a combined entropy-frequency ratio (FR) weightage formulation model to delineate groundwater potential zones. Digital elevation models and satellite imagery are used to prepare thematic maps of factors like slope and rainfall. These maps are divided into classes and their pixel counts are calculated to determine area percentages. Frequency ratios are then calculated comparing area percentages of each class to the total area. Entropy and information coefficients are also calculated. Finally, weights are assigned to each class for each thematic map by combining the entropy and FR values using the proposed entropy-FR model. This provides objective weights to replace subjective weights. The weighted thematic maps are then overlaid to produce a composite groundwater potential zones map. The
A Review Of Different Approaches Of Land Cover MappingJose Katab
This document reviews different approaches for land cover mapping, including artificial neural networks (ANNs), fuzzy logic, supervised/unsupervised classification, and maximum likelihood. It discusses how each approach has been applied in previous studies for land cover classification using remote sensing data. The document also examines common problems in remote sensing image classification, such as mixed pixels, and different methods that have been proposed and used to address these issues, such as maximum likelihood classification and fuzzy classifiers. Overall, the review analyzes and compares algorithms for land cover classification and evaluates methods for overcoming problems encountered during the classification process.
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.
Selection of wastewater treatment process based on analytical hierarchy processIAEME Publication
This document summarizes a study that used the analytical hierarchy process (AHP) to select the best wastewater treatment process for urban areas in Karnataka, India. The study considered 4 treatment processes (activated sludge process, extended aeration, sequential batch reactor, up-flow anaerobic sludge blanket reactor) based on technical, economic, and environmental criteria. Pairwise comparisons between alternatives were conducted based on sub-criteria like performance, cost, odor and sludge generation. AHP was used to assign weights to criteria and synthesize priorities to determine the optimal process based on the decision factors.
A hybrid approach for analysis of dynamic changes in spatial dataijdms
Any geographic location undergoes changes over a period of time. These changes can be observed by
naked eye, only if they are huge in number spread over a small area. However, when the changes are small
and spread over a large area, it is very difficult to observe or extract the changes. Presently, there are few
methods available for tackling these types of problems, such as GRID, DBSCAN etc. However, these
existing mechanisms are not adequate for finding an accurate changes or observation which is essential
with respect to most important geometrical changes such as deforestations and land grabbing etc.,. This
paper proposes new mechanism to solve the above problem. In this proposed method, spatial image
changes are compared over a period of time taken by the satellite. Partitioning the satellite image in to
grids, employed in the proposed hybrid method, provides finer details of the image which are responsible
for improving the precision of clustering compared to whole image manipulation, used in DBSCAN, at a
time .The simplicity of DBSCAN explored while processing portioned grid portion.
The document analyzes and compares the C4.5 and K-nearest neighbor (KNN) algorithms for clustering data and determining priority development areas in Papua Province, Indonesia. It first discusses Klassen typology for classifying areas based on economic growth and per capita income. It then provides an overview of the C4.5 and KNN algorithms, including pseudo code for analyzing their time complexities using the Big O notation. The study applies these algorithms to PDRB and economic growth data from 29 regencies in Papua from 2006-2012 to determine priority development areas, running the algorithms multiple times on different sized data sets to analyze running time.
Application Of Analytic Hierarchy Process And Artificial Neural Network In Bi...IJARIDEA Journal
Abstract— An appropriate decision to bid initiates all bid preparation steps. Selective bidding will reduce the number of proposals to be submitted by the contractor and saves tender preparation time which can be utilized for refining the estimated cost. Usually in industrial engineering applications final decision will be based on the evaluation of many alternatives. This will be a very difficult problem when the criteria are expressed in different units or the pertinent data are not easily quantifiable. This paper emphasizes on the use of Analytic Hierarchy Process(AHP) for analyzing the risk degree of each factor, so that decision the can be taken accordingly in deciding an appropriate bid.AHP helps to decide the best solution from various selection criteria.The study also focuses on suggesting a much broader applicability of AHP and ANN techniques on decisions of bidding.
Keywords— Analytic Hierarchy Process(AHP), Artificial Neural Network(ANN), Consistency Index(CI),
Consistency Ratio(CR), Random Index(RI), Risk degree.
1) The document discusses predicting soil fertility using machine learning techniques such as decision trees, artificial neural networks, support vector machines, and k-nearest neighbors.
2) It analyzes soil data from Haryana, India to determine the most important properties for defining soil fertility and properties that are highly correlated. Conductivity, water holding capacity, and potassium were found to be most important based on a decision tree analysis.
3) Support vector machines using a radial basis kernel performed best with 80% accuracy compared to 63% for decision trees, 55% for artificial neural networks, and 70% for k-nearest neighbors.
Comparison among Height Observation of GPS, Total Station and Level and their...IRJET Journal
This document compares the accuracy of GPS, total station, and level instruments for measuring elevation in mining works by using GIS technology. Statistical analysis showed the level measurements had the lowest variation while GPS had the highest. Topographic maps were created from observations from each instrument, showing they produced similar overall elevation patterns. The document concludes that while GPS and total station measurements have some error, their accuracy is sufficient for mining works. GIS allows easy analysis and use of elevation data from any of the three instruments.
Accuracy Assessment of Land Use/Land Cover Classification using multi tempora...IRJET Journal
This document analyzes land use/land cover (LULC) changes in Varanasi city, India over a 20 year period from 2000 to 2020 using multi-temporal satellite imagery. Landsat images from 2000, 2010, and 2020 were classified into six LULC classes - water bodies, sandbars, fallow land, built up area, vegetation, and crop land. The results show significant increases in built up area and fallow land, with corresponding decreases in vegetation and crop land. Accuracy assessment using confusion matrices found overall classification accuracies of 93.94%, 91.66%, and 89.47% for the 2000, 2010, and 2020 images respectively. The study demonstrates the use of GIS and remote sensing
Land use/land cover classification using machine learning modelsIJECEIAES
An ensemble model has been proposed in this work by combining the extreme gradient boosting classification (XGBoost) model with support vector machine (SVM) for land use and land cover classification (LULCC). We have used the multispectral Landsat-8 operational land imager sensor (OLI) data with six spectral bands in the electromagnetic spectrum (EM). The area of study is the administrative boundary of the twin cities of Odisha. Data collected in 2020 is classified into seven land use classes/labels: river, canal, pond, forest, urban, agricultural land, and sand. Comparative assessments of the results of ten machine learning models are accomplished by computing the overall accuracy, kappa coefficient, producer accuracy and user accuracy. An ensemble classifier model makes the classification more precise than the other state-of-the-art machine learning classifiers.
A Review on Associative Classification Data Mining Approach in Agricultural S...Editor IJMTER
Data mining in agriculture is a very recent research topic. It consists in the
application of data mining techniques to agriculture. Recent technologies are nowadays able to
provide a lot of information on agricultural-related activities, which can then be analyzed in
order to find important information. A related, but not equivalent term is precision agriculture.
This research aimed to assess the various classification techniques of data mining and apply
them to a soil science database to establish if meaningful relationships can be found. A large
data set of soil database is extracted from the Soil Science & Agricultural department, Bhopal
M.P and National Informatics Centre, The application of data mining techniques has never
been conducted for Bhopal soil data sets. The research compares the different classifiers and
the outcome of this research could improve the management and systems of soil uses
throughout a large number of fields that include agriculture, horticulture, environmental and
land use management.
IRJET- Agricultural Crop Classification Models in Data Mining TechniquesIRJET Journal
This document discusses using Naive Bayes classification to classify agricultural crop types using Landsat satellite imagery data. The researchers analyzed Landsat data using Naive Bayes and evaluated the accuracy of crop classification using various performance metrics. On the training dataset, Naive Bayes correctly classified 211 instances and incorrectly classified 238 instances. On the testing dataset, it correctly classified 49 instances and incorrectly classified 45 instances. The researchers concluded Naive Bayes can achieve reasonably high accuracy for crop classification but plan to compare its performance to other algorithms in future work.
Soil Characterization and Classification: A Hybrid Approach of Computer Visio...IJECEIAES
This paper presents soil characterization and classification using computer vision & sensor network approach. Gravity Analog Soil Moisture Sensor with arduino-uno and image processing is considered for classification and characterization of soils. For the data sets, Amhara regions and Addis Ababa city of Ethiopia are considered for this study. In this research paper the total of 6 group of soil and each having 90 images are used. That is, form these 540 images were captured. Once the dataset is collected, pre-processing and noise filtering steps are performed to achieve the goal of the study through MATLAB, 2013. Classification and characterization is performed through BPNN (Back-propagation neural network), the neural network consists of 7 inputs feature vectors and 6 neurons in its output layer to classify soils. 89.7% accuracy is achieved when back-propagation neural network (BPNN) is used.
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
Main news related to the CCS TSI 2023 (2023/1695)Jakub Marek
An English 🇬🇧 translation of a presentation to the speech I gave about the main changes brought by CCS TSI 2023 at the biggest Czech conference on Communications and signalling systems on Railways, which was held in Clarion Hotel Olomouc from 7th to 9th November 2023 (konferenceszt.cz). Attended by around 500 participants and 200 on-line followers.
The original Czech 🇨🇿 version of the presentation can be found here: https://www.slideshare.net/slideshow/hlavni-novinky-souvisejici-s-ccs-tsi-2023-2023-1695/269688092 .
The videorecording (in Czech) from the presentation is available here: https://youtu.be/WzjJWm4IyPk?si=SImb06tuXGb30BEH .
Monitoring and Managing Anomaly Detection on OpenShift.pdfTosin Akinosho
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
HCL Notes and Domino License Cost Reduction in the World of DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
Skybuffer SAM4U tool for SAP license adoptionTatiana Kojar
Manage and optimize your license adoption and consumption with SAM4U, an SAP free customer software asset management tool.
SAM4U, an SAP complimentary software asset management tool for customers, delivers a detailed and well-structured overview of license inventory and usage with a user-friendly interface. We offer a hosted, cost-effective, and performance-optimized SAM4U setup in the Skybuffer Cloud environment. You retain ownership of the system and data, while we manage the ABAP 7.58 infrastructure, ensuring fixed Total Cost of Ownership (TCO) and exceptional services through the SAP Fiori interface.
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
Digital Marketing Trends in 2024 | Guide for Staying AheadWask
https://www.wask.co/ebooks/digital-marketing-trends-in-2024
Feeling lost in the digital marketing whirlwind of 2024? Technology is changing, consumer habits are evolving, and staying ahead of the curve feels like a never-ending pursuit. This e-book is your compass. Dive into actionable insights to handle the complexities of modern marketing. From hyper-personalization to the power of user-generated content, learn how to build long-term relationships with your audience and unlock the secrets to success in the ever-shifting digital landscape.
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdfChart Kalyan
A Mix Chart displays historical data of numbers in a graphical or tabular form. The Kalyan Rajdhani Mix Chart specifically shows the results of a sequence of numbers over different periods.
Building Production Ready Search Pipelines with Spark and MilvusZilliz
Spark is the widely used ETL tool for processing, indexing and ingesting data to serving stack for search. Milvus is the production-ready open-source vector database. In this talk we will show how to use Spark to process unstructured data to extract vector representations, and push the vectors to Milvus vector database for search serving.
Generating privacy-protected synthetic data using Secludy and MilvusZilliz
During this demo, the founders of Secludy will demonstrate how their system utilizes Milvus to store and manipulate embeddings for generating privacy-protected synthetic data. Their approach not only maintains the confidentiality of the original data but also enhances the utility and scalability of LLMs under privacy constraints. Attendees, including machine learning engineers, data scientists, and data managers, will witness first-hand how Secludy's integration with Milvus empowers organizations to harness the power of LLMs securely and efficiently.
5th LF Energy Power Grid Model Meet-up SlidesDanBrown980551
5th Power Grid Model Meet-up
It is with great pleasure that we extend to you an invitation to the 5th Power Grid Model Meet-up, scheduled for 6th June 2024. This event will adopt a hybrid format, allowing participants to join us either through an online Mircosoft Teams session or in person at TU/e located at Den Dolech 2, Eindhoven, Netherlands. The meet-up will be hosted by Eindhoven University of Technology (TU/e), a research university specializing in engineering science & technology.
Power Grid Model
The global energy transition is placing new and unprecedented demands on Distribution System Operators (DSOs). Alongside upgrades to grid capacity, processes such as digitization, capacity optimization, and congestion management are becoming vital for delivering reliable services.
Power Grid Model is an open source project from Linux Foundation Energy and provides a calculation engine that is increasingly essential for DSOs. It offers a standards-based foundation enabling real-time power systems analysis, simulations of electrical power grids, and sophisticated what-if analysis. In addition, it enables in-depth studies and analysis of the electrical power grid’s behavior and performance. This comprehensive model incorporates essential factors such as power generation capacity, electrical losses, voltage levels, power flows, and system stability.
Power Grid Model is currently being applied in a wide variety of use cases, including grid planning, expansion, reliability, and congestion studies. It can also help in analyzing the impact of renewable energy integration, assessing the effects of disturbances or faults, and developing strategies for grid control and optimization.
What to expect
For the upcoming meetup we are organizing, we have an exciting lineup of activities planned:
-Insightful presentations covering two practical applications of the Power Grid Model.
-An update on the latest advancements in Power Grid -Model technology during the first and second quarters of 2024.
-An interactive brainstorming session to discuss and propose new feature requests.
-An opportunity to connect with fellow Power Grid Model enthusiasts and users.
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
AI 101: An Introduction to the Basics and Impact of Artificial IntelligenceIndexBug
Imagine a world where machines not only perform tasks but also learn, adapt, and make decisions. This is the promise of Artificial Intelligence (AI), a technology that's not just enhancing our lives but revolutionizing entire industries.
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Mv2522052211
1. V.D.Patil, R.N.Sankhua, R.K.Jain / International Journal of Engineering Research and
Applications (IJERA) ISSN: 2248-9622 www.ijera.com
Vol. 2, Issue 5, September- October 2012, pp.2205-2211
Multi-Criteria Decision Analysis For Residential Land Use
Suitability Using Socio-Economic Responses Through AHP
V.D.Patil*,R.N.Sankhua**,R.K.Jain***
*
(Associate Professor,National Institute of Technical Teachers’Training&Research,Extension,Center,Pune)
**
(Director, NWA, Pune-24)
***
(Principal, Dr D.Y Patil Institute of Technology and Engineering,Pimri, Pune- 18)
ABSTRACT
Analytic Hierarchy Process (AHP) has different requirements/criteria [2]. Research in this
emerged as one of the most important structured area is very important to achieve cost effective and
techniquein the field of complex decision analysis. sustainable development of land use in general and
In this paper, an endeavor has been made using residential land use planning in particular.
AHP for land use suitability of real estates in
conjunction with Erosion Response using spatial II. THE STUDY AREA
technique for Pimpri-Chinchwad-Municipal As emerged from the defined objectives of
Corporation (PCMC) area. This is just an the research, the study area has been chosen which
amalgamation of a heuristic algorithm that encompasses the extent of latitude from
provides good approximate, but not necessarily 18°34'3.417"N to 18°43'22.033"N latitude and
optimal solution to a given model in the area longitude 73°42'38.595"E to 73°56'2.726"E . The
under consideration. To derive ratio scales from area lies within the domain of PCMC area of
paired comparisons in employing such an Maharashtra, India, as depicted in Figure 1.The area
algorithm, one may be able to precisely measure is situated in the climate zone of hills and plain, it is
the ‘goodness’ of the approximation. In the influenced by common effects of
present envisaged study, the factors like Price,
Land Use, Land cover, Facilities available and
Population Density affecting in the process are
analytically and logically encompassed to make a
gainful research through a scientifically proven
method, which has been depicted in this present
paper in a sequential manner.
Keywords: Multi Criteria Decision Analysis
(MCDA), Analytical Hierarchy Process
(AHP),socio-economic factors, land-use
suitability.
I. INTRODUCTION
Land suitability assessment is similar to
choosing an appropriate location and the goal of this
study is to map a suitability index for the entire
study area. It is a fundamental work and an
important tool for overall land use planning, which
requires a scientific approach to guide development,
avoid errors in decision-making and over-
investment. For sustainable utilization of land
resources [3],[15]map overlays are used to define
homogeneous zones, and then classification
techniques are applied to assess the residential land
suitability level of each zone. These classification
techniques have been based on Boolean and fuzzy
theory or artificial neural networks. The processes of
land useinvolved evaluation and grouping of specific Figure.1 The study area
areas of land in terms of their suitability for a tropical monsoon climatic belt with the
defined use. The principles of sustainable three distinct seasons. The annual average
development make land-use suitability analysis temperature is about 250C. The average annual
increasingly complex due to consideration of rainfall is about 600-700 mm, but is irregularly
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2. V.D.Patil, R.N.Sankhua, R.K.Jain / International Journal of Engineering Research and
Applications (IJERA) ISSN: 2248-9622 www.ijera.com
Vol. 2, Issue 5, September- October 2012, pp.2205-2211
distributed. The maximum rainfall is observed in 4.1 SELECTING CRITERIA
June-September. PCMC a twin city of Pune is one of In this study criteria were selected using the
the fast growing medium size cities of Maharashtra literature reviews of internal andexternal references,
with a population of about 1.7 millions as per census interviewing with experts (questionnaires) and
of 2011and sprawling over an area of 174 sq. km. availability of data.
III. EARLIER RESEARCH 4.2WEIGHING OF CRITERIA (SCALE FOR
The Analytic Hierarchical Process (AHP) is PAIR WISE COMPARISON)
one of the methodological approaches that may be For determining the relative importance of
applied to resolve highly complex decision making the criteria thepair-wise comparison matrix using
problems involving multiple situations, criteria and Saaty'snine-pointweighing scale has been applied. In
factors [14]. Thomas L. Saaty (1970), constructs a AHP, all identified factors are compared against
ratio scale associated with the priorities for the each other in a pair wise comparison matrix which is
various items to be compared. In his initial a measure of relative importance/preference among
formulationofAHP, Saaty proposed a four-step the factors. Therefore, numerical values expressing
methodology comprising modeling, valuation, the relative preference of a factor against another.
prioritization and synthesis. At the modeling stage, a Saaty (1977) suggested a scale for comparison
hierarchy representing relevant aspects of the consisting of values ranging from 1 to 9 which
problem (criteria, sub-criteria, attributes and describe the intensity of importance, by which a
alternatives) has been constructed. The goal value of 1 expresses equal importance and a value of
concerned in the problem is placed at the top of this 9 is given to those factors having an extreme
hierarchy. Other relevant aspects (criteria, sub- importance over another factor. As shown in Table 1
criteria, attributes, etc.) are placed at remaining [7]. Then by using the information from table 1, the
levels [1]. In the AHP method, obtaining the weights factors were pair wise compared.In order to compare
or priority vector of the alternatives or the criteria is criteria with each other, all values need to be
required. For this purpose Saaty (1980) has transformed to the same unit of measurement scale
developed the Comparison Method (PCM), which is (from 0 to 1), whereas the various input maps have
explained in detail in next part of the work. This different measurement units (e.g. distance maps,
study focuses on the utility of the AHP as a model temperature etc.).
for capturing expert knowledge on environmental
systems where data may be lacking. The AHP TABLE 1: Nine-point weighing scale for pair-wise
method commonly used in multi-criteria decision comparison
making exercises was found to be a useful method to Descriptions of Preference Scale
determine the weights, compared with other methods
used for determining weights. When applying AHP, i) Equally 1
constraints are compared with each other to ii) Equally to moderately 2
determine the relative importance of each variable in
accomplishing the overall goal. iii) Moderately 3
iv) Moderately to strongly 4
IV. DATA USED AND METHODOLOGY
v) Strongly 5
The Linear Imaging Self Scanner (LISS III)
digital data having spatial resolution of 23.5 m for vi) Strongly to very Strongly 6
April, 2008 and May, 2008 have been taken in vii) Very Strongly 7
conjunction with Aster Digital Elevation Model
(DEM) data of 30 m resolution downloaded from viii) Very Strongly to extremely 8
Aster GDEM website. Analog and other ancillary ix) Extremely 9
data were collected from Survey of India
Toposheets47/F/14 and 47/F/10 of 1:50000 scales
for the area under PCMC.The entire methodology of After standardization all criteria and sub
the present work is focused on theapplication of criteria were weighted using pair wise comparison
AHP and GIS for land use suitability analysis for method. An example of main criteria and sub criteria
residential land uses. The principal steps involved in weighing is given in Table 2 and 3respectively.
the methodologyareas follows:
i) Raster map creation
ii) Geo-referencing
iii) Extraction of study area
iv) Preparation of various raster layers
v) AHP and GIS analysis
The three main AHP criteria of selection, weighing
and overly are described below.
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3. V.D.Patil, R.N.Sankhua, R.K.Jain / International Journal of Engineering Research and
Applications (IJERA) ISSN: 2248-9622 www.ijera.com
Vol. 2, Issue 5, September- October 2012, pp.2205-2211
TABLE 2: Weighing matrix for main criteria Where,SI is the Suitability Index of each cells;N is
Criteria Sub- Standards Weigh the number of main criteria; RI,A1, RI, A2 …RN,AN
criteria Adopted t are the relative importance of the main criteria A1,
A2 …AN, respectively; m, i and j are the number of
SocioEconomi PriceFacto < 2250 9 sub criteria directly connected to the main criteria
c Parameters r 2250-4500 5 A1, A2 …AN, respectively.
4500-6750 2 RIB, RIC and RID are the relative importance of sub
6750-9000 1 criteria B, C and D directly connected to the main
> 9000 1 criteria A1, A2 …AN, respectively.
LU/LC Scrub 9 RIKB, RIKC and RIKD are the relative importance
Vegetation 5 of indicators category k of sub criteria B, C and D
Agricultur 3 and main criteria A1, A2 …AN,respectively.
e
Harvested 2 4.4 CALCULATION OF SCORE VALUE FOR
EACH CRITERION
Settlement 1
The suitability value for price factor, land
Available 5 9
use land cover, facilities available, population
Facility 4 5 density,inPimpri-Chinchwad area and the criterion
3 3 for each land mapping unit is determined through the
2 1 maximum limitation method that affects the land
1 1 use. The above four representative natural physical
Population < 5000 9 characteristics are used in socio-economic response
Density 5000- 5 model constitute the sub-criteria under
10000 socioeconomic criteria. Before applying weighted
10000- 3 linear combination equation to calculated suitability
15000 index, these calculated scores are standardized to the
15000- 2 measured scale 9 (very high suitability), 7 (High), 5
20000 (medium), and 1 (Low). All of the classifications
>20000 1 and ranking values in spatial analysis are obtained
according to some studies of Al-Shalabi et al.
It could be seen that for preventing bias thought (2006), Kordi (2008) and based on visiting the study
criteriaweighting the Consistency Ratio was used . area.
𝜆 𝑚𝑎𝑥 − 𝑛
𝐶. 𝐼. = (1)
𝑛−2 4.5 PREPARING OF LAND SUITABILITY
𝐶.𝐼.
𝐶. 𝑅. = 𝑅.𝐼.(2) MAPS
After weighting the criteria, as regards the
Where; n = Number of Items Being Compared inthe relative importance of each criterion as well as
Matrix suitability index, all the criterion maps were overlaid
λmax= Largest Eigen Value and final rangeland suitability map was prepared.
RI = Random Consistency Index Suitability maps resulting from Multi-Criteria
Evaluation (MCE) and multi-objective land
4.3 OVERLYING allocation have shown different classes for which the
After weighing of criteria regarding their degree of sensitivity to accept new building for
importance for land suitability analysis, all criteria example estates and urban settlements vary from
maps were overlaid using suitability index. extremely prone areas to weakly prone.
Based on relative weights of the suitability
Suitability Index, 𝑆𝐼 = 𝑅𝐼 ∗ 𝐴1 ∗ 𝛴𝑅𝐼. 𝐵𝑖 ∗ factors for development, suitability ranges were
identified as shown in Table 10. Figure 2 depicts the
𝑅𝐼 .𝐾𝐵𝑖
final map (suitability map), which divided to 5 best
+ 𝑅𝐼 ∗ 𝐴2 ∗ 𝛴𝑅𝐼. 𝐶𝑦
areas in increasing order: area 1, 2, 3, 4 and 5.
∗ 𝑅𝐼 . 𝐾𝐶𝑦
According to this map, there are 5 colours (classes):
+ 𝑅𝐼 ∗ 𝐴𝑁 ∗ 𝛴𝑅𝐼. 𝐷𝑧 ∗ 𝑅𝐼 . 𝐾𝐷𝑧
dark Blue, Blue,Green, Yellow and Red.
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5. V.D.Patil, R.N.Sankhua, R.K.Jain / International Journal of Engineering Research and
Applications (IJERA) ISSN: 2248-9622 www.ijera.com
Vol. 2, Issue 5, September- October 2012, pp.2205-2211
TABLE 6: Suitability according to Facilities Available –Garden (Normalized matrix)
Garden <1400 1400-2800 2800-4200 4200-5600 >5600 Sum PV Score
<1400 0.56 0.64 0.52 0.43 0.36 2.51 0.50 9.00
1400-2800 0.19 0.21 0.31 0.31 0.28 1.30 0.26 4.66
2800-4200 0.11 0.07 0.10 0.18 0.20 0.67 0.13 2.40
4200-5600 0.08 0.04 0.03 0.06 0.12 0.34 0.07 1.21
>5600 0.06 0.03 0.02 0.02 0.04 0.17 0.03 0.62
TABLE 7: Suitability according to Facilities Available –Landmark (Normalized matrix)
Landmarks <750 750-1500 1500-2250 2250-3000 >3000 Sum PV Score
<750 0.56 0.63 0.52 0.46 0.41 2.57 0.51 9.00
750-1500 0.19 0.21 0.31 0.26 0.23 1.20 0.24 4.18
1500-2250 0.11 0.07 0.10 0.20 0.18 0.66 0.13 2.32
2250-3000 0.08 0.05 0.03 0.07 0.14 0.37 0.07 1.29
>3000 0.06 0.04 0.03 0.02 0.05 0.20 0.04 0.69
TABLE 8:Suitability according to Facilities Available –Fire station (Normalized matrix)
Fire-station <2500 2500-5000 5000-7500 7500-10000 >10000 Sum PV Score
<2500 0.53 0.64 0.47 0.39 0.32 2.34 0.47 9.00
2500-5000 0.18 0.21 0.35 0.32 0.32 1.38 0.28 5.31
5000-7500 0.13 0.07 0.12 0.19 0.23 0.74 0.15 2.85
7500-10000 0.09 0.04 0.04 0.06 0.09 0.33 0.07 1.25
>10000 0.08 0.03 0.02 0.03 0.05 0.21 0.04 0.80
TABLE 9: Suitability according to Facilities Available –Criteria (Normalized matrix)
H S G L F Sum PV Score
Hospital (H) 0.50 0.54 0.52 0.39 0.33 2.30 0.46 9.00
School (S) 0.25 0.27 0.31 0.33 0.29 1.46 0.29 5.71
Garden (G) 0.10 0.09 0.10 0.20 0.21 0.70 0.14 2.74
LandMarks (L) 0.08 0.05 0.03 0.07 0.13 0.36 0.07 1.42
Fire Station (F) 0.06 0.04 0.02 0.02 0.04 0.19 0.04 0.73
TABLE 10:
Sr No Level Rank
1 Highly Suitable 5
2 Suitable 4
3 Moderately suitable 3
4 Slightly suitable 2
5 Unsuitable 1
TABLE 11: Suitability according to Price factor (Normalized matrix)
Class 0 - 2250 2250 - 4500 4500 - 6750 6750 - 9000 > 9000 Sum PV Score
0 - 2250 0.56 0.64 0.52 0.43 0.36 2.51 0.50 9.00
2250 - 4500 0.19 0.21 0.31 0.31 0.28 1.30 0.26 4.66
4500 - 6750 0.11 0.07 0.10 0.18 0.20 0.67 0.13 2.40
6750 - 9000 0.08 0.04 0.03 0.06 0.12 0.34 0.07 1.21
> 9000 0.06 0.03 0.02 0.02 0.04 0.17 0.03 0.62
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6. V.D.Patil, R.N.Sankhua, R.K.Jain / International Journal of Engineering Research and
Applications (IJERA) ISSN: 2248-9622 www.ijera.com
Vol. 2, Issue 5, September- October 2012, pp.2205-2211
TABLE 12: Suitability according to Landuse/Land Cover (Normalized matrix)
Class Scrub Vege. Agri. Har Sett Sum PV Score
Scrub 0.53 0.63 0.47 0.38 0.41 2.41 0.48 9.00
Veg 0.18 0.21 0.35 0.30 0.23 1.26 0.25 4.72
Agri 0.13 0.07 0.12 0.23 0.18 0.72 0.14 2.71
Har. 0.11 0.05 0.04 0.08 0.14 0.41 0.08 1.53
Sett. 0.06 0.04 0.03 0.03 0.05 0.20 0.04 0.75
TABLE 13: Suitability according to Facilities Available (Normalized matrix)
Class 5 4 3 2 1 Sum PV Score
5 0.51 0.54 0.52 0.43 0.36 2.37 0.47 9.00
4 0.26 0.27 0.31 0.31 0.28 1.43 0.29 5.43
3 0.10 0.09 0.10 0.18 0.20 0.68 0.14 2.59
2 0.07 0.05 0.03 0.06 0.12 0.34 0.07 1.31
1 0.06 0.04 0.02 0.02 0.04 0.18 0.04 0.67
TABLE 14: Suitability according to Population Density (Normalized matrix)
Class < 5 5-10 10-15 15-20 >20 Sum PV Score
<5 0.51 0.63 0.47 0.38 0.32 2.30 0.46 9.00
5-10 0.17 0.21 0.35 0.30 0.26 1.29 0.26 5.07
10-15 0.13 0.07 0.12 0.23 0.21 0.75 0.15 2.94
15-20 0.10 0.05 0.04 0.08 0.16 0.43 0.09 1.67
>20 0.09 0.04 0.03 0.03 0.05 0.23 0.05 0.92
TABLE 15: Final Suitability according to all Socio Economic factors (Normalized matrix)
Class P L F P Total PV Score
Price 0.52 0.57 0.48 0.40 1.97 0.49 9.00
LU/LC 0.26 0.28 0.36 0.33 1.24 0.31 5.66
Facility 0.13 0.09 0.12 0.20 0.54 0.14 2.49
Popu. 0.09 0.06 0.04 0.07 0.25 0.06 1.14
Figure 2 Final Suitability Map
The following results emerged out of the present i) The Study area has been classified in to
study: nine ranges using supervisedalgorithm and different
suitability classes are obtained
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7. V.D.Patil, R.N.Sankhua, R.K.Jain / International Journal of Engineering Research and
Applications (IJERA) ISSN: 2248-9622 www.ijera.com
Vol. 2, Issue 5, September- October 2012, pp.2205-2211
ii) NDVI layer was assigned to the area, classification methods in land suitability
whichdemonstrated the vegetation classes. analysis by using geographical information
iii) Price, land use, land cover, facilities systems. J. Environ. Planning., V.4, No. 24,
available and population density (5classes each) pp. 497–516.
were derived from the digital image illustrating [4] J. Chen, Y. & Wu, J.P. (2009). Cellular
thesuitability of the area. automata and GIS based land use suitability
iv) AHP used hierarchical structuresfor nine simulation for irrigated agriculture. 18th
scales with the Socio-economic criteria, and were World IMACS / MODSIM Congress,
devised for the designof AHP applicability for Cairns, Australia 13-.
residential land use suitability. The AHP was [5] Kordi, M. (2008). Comparison of fuzzy and
devised for allthe sub criteria, evaluating their crisp analytic hierarchy process (AHP)
relative scores for attribute classes toget the land use methods for spatial multicriteria decision
suitability model forPCMC area using socio analysis in GIS. Master. Thesis, University
economic parameters as mentioned above. of Gavle.
[6] M. Bagheri, Z. Z. Ibrahim, W. N. A.
V. CONCLUSION Sulaiman and N. Vaghefi (2011)
The analysis of this study mainly focused Integration of Analytical Hierarchy Process
on highly suitable areas as these areas have highest and Spatial Suitability Analysis for Land
potential for construction purposes i.e. residential Use Planning in Coastal Area, published
land use. AHP model has been to land use suitability in,”The proceedings of the first Iranian
analysis based on five criteria layers. The Analytic Students Scientific Conference in Malaysia.
Hierarchy Process (AHP) method has been foundas [7] Marinoni, O., (2004). Implementation of
a useful method to determine the weights, as the analytical hierarchy process with VBA
compare to other methods used for determining in ArcGIS, J ComputGeosci, 30(6): 637–
weights. The sensitivity utility of this model helped 646
to analyze the decision before making the final [8] Saaty, T. L. (1980). The analytic hierarchy
choice. The AHP method could deal with process. Polytechnic University of
inconsistent judgments and can provide a tool to Hochiminh city, Vietnam McGraw-Hill,
measure the inconsistency of the judgment taken by New York.
the respondents. This assessment can be useful in [9] Saaty, T. L. (1988). Multi criteria Decision
decision-making process for land use planning and Making: The Analytical Hierarchy Process.
can also help in sustainable urban development of RWS Publications, Pittsburgh, PA.
PCMC area. It is very important for planners to [10] Saaty, T. L. (1990). An exposition on the
decide whether land should be developed AHP in reply to the paper ‘remarks on the
immediately or to be conserved for future analytic hierarchy process. Manag. Sci., 36,
development. This model can help to prepare the 259–268,
strategic urban land development framework and the [11] Saaty, T. L. (1994). Highlights and critical
short-term land use policies can be formulated. The points in the theory an application of the
approach, therefore, can helpthe planners and policy analytic hierarchy process. Eur. J. Oper.
makers to monitorthe urban land development for Res., 74, 426–447.
formulating urban growth policies and strategies for [12] Saaty, T. L. (1995). Decision Making for
a city. Leaders: The Analytic Hierarchy Process
for Decisions in a Complex World. 3d ed.
VI. REFERENCES RWS Publications, Pittsburgh, PA.
[1] Altuzarra, A., María, J. & Jiménez, M. [13] Saaty, T.L., (1977). A scaling method for
Salvador, M. (2007). A Bayesian priorities in hierarchical structures. J. Math
priorization procedure for AHP-group Psycho., 15: 231-281
decision making. EurJOper Res., v.182, [14] Saaty, T.L., (1980). The Analytic Hierarchy
No(1), pp. 367-382. Process. McGraw-Hill, New York., pp. 20-
[2] Duc, T.T. (2006). Using GIS and AHP 25.
technique for land-use suitability analysis. [15] Wang, F. (1994). The use of artificial
International Symposium on neural networks in a geographical
Geoinformatics for Spatial Infrastructure information system for agricultural land-
Development in Earth and Allied Sciences. suitability assessment. Environment and
[3] Hall, G.B. Wang, F. Subaryono. (1992). planning A., No.26, pp. 265– 284.
Comparison of Boolean and fuzzy
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