This document summarizes a study that compares the accuracy of single band and band ratio methods for shallow water depth mapping using Worldview-3 satellite imagery of the Karimunjawa Islands, Indonesia. Depth data was collected via field surveys and corrected for tides. The study found that the band ratio method, specifically the blue/green ratio, produced more accurate depth estimates with a root mean square error of 1.669 meters compared to 2.373 meters for the best single band method. Therefore, the band ratio method is concluded to provide better shallow water depth estimates than the single band method for this study area and image dataset.
Using Remote Sensing Techniques For Monitoring Ecological Changes In Lakes: C...IJERA Editor
The ability to use remote sensing in studying lake ecology lies in the capability of satellite sensors to measure
the spectral reflectance of constituents in water bodies. This reflectance can be used to determine the
concentration of the constituents of the water column through mathematical relationships. This work identified a
simple linear equation for estimating suspended matter in Lake Naivasha with reflectance in Landsat7 ETM+
image. A R² = 0.94, n = 6 for suspended matter was obtained. Archive of Landsat imagery was used to
produce maps of suspended matter concentrations in the lake. The suspended matter concentrations at five
different locations in the lake over 30 year’s period were then estimated. It was therefore concluded that the
ecological changes Lake Naivasha is experiencing is the result of the high water abstraction and the effect of
climate change.
An Automated Approach of Shoreline Detection Applied to Digital Videos using ...Dwi Putra Asana
Abstract: This study aims to detect a shoreline location and its changes automatically in the temporal resolution.
This approach is implemented on the coastal video monitoring system applications. The proposed method applied
data mining by using two main systems-a training system using classification and shoreline detection systems with
Self-Organizing Map (SOM) and K-Nearest Neighbor (K-NN) algorithms. The training system performs feature
texture extraction using agray-level co-occurrence matrix and the results are stored to classification process. The
detection system has five processing stages: contrast stretching preprocessing and morphological contrast
enhancement, SOM clustering, morphological operations, feature extraction and K-NN classification and detection
shoreline. Preprocessing was used to improve the video image contrast and reliability. SOM algorithm in
segmenting objects in the onshore video images. Morphological operations were applied to eliminate noise on the
objects that were not needed in the spatial domain. The segmentation results of video frames classified by K-NN.
The aim is to provide the class labels on each region segmentation results, namely, sea label, land label and sky
label. The determination of the shoreline is done by scanning the neighboring pixels from the edge of land class
label after binary image transformation. The shoreline change detection was performed by comparing the position of
existing shoreline and shoreline position in the reference video frame. A Receiver Operating Characteristic (ROC)
curve was used to evaluate the performance of shoreline detection systems. The results showed that the combination
of SOM and K-NN was able to detect shoreline and its changes accurately
study and analysis of hy si data in 400 to 500IJAEMSJORNAL
The ability to extract information about world and present it in way that our visual perception can comprehend is ultimate goal of imaging science in remote sensing .Hyperspectral imaging system is most powerful tool in the field of remote sensing also called as imaging spectroscopy, It is new technique used by researcher to detect terrestrial, vegetation and mineral. This paper reports analysis of hyperspectral images. Firstly the hyperspectral image analyzed by using supervised classification of Amravati region from Maharashtra province of India. The report reveals spectral analysis of Amravati region. We acquired satellite imagery to perform the classification using maximum like hood classifier. Analysis is performing in ERDAS to determine the spectral reflectance against the no of band. The analytical outcome of paper is representing the soil, water, vegetation index of the region.
Water-Body Area Extraction From High Resolution Satellite Images-An Introduct...CSCJournals
Water resources play an important role in region planning, natural disaster, industrial and agricultural production and so on. Surveying of water-bodies and delineate its features properly is very first step for any planning, especially for places like India, where the land-cover is dominated by water-bodies. Recording images, such as from satellite, sometimes does not reflect the distinguished characteristics of water with non-water features, e.g. shadows of super structures. Image of water body is confused easily with the shadow of skyscraper, since calm water surface induces mirror reflection when it gives birth to echo wave. Over the past decade, a significant amount of research been conducted to extract the water body information from multi-resolution satellite image. The objective of this paper is to review methodologies applied for water body extraction using satellite remote sensing. First, studies on water body detection are treated. Methodological issues related to the use of these methods were summarized. Results from empirical studies, applying water-body extraction techniques are collected and discussed. Important issues for future research are also identified and discussed.
A Review of Change Detection Techniques of LandCover Using Remote Sensing Dataiosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
The study was carried out using the UAV for analyzing the characteristics of debris in order to present the methodology to estimate the quantitative amount of debris caught in small river facilities. A total of six small rivers that maintained the form of a natural river were selected for collecting UAV images, and the grouping of each target in the image was carried out using the object-based classification method, and based on the object-based classification result of the UAV images, the land cover classification for the status of factors causing the generation of debris for six target sections was carried out by applying the screen digitizing method. In addition, in order to verify the accuracy of the classification result, the error matrix was performed, securing the reliability of the result. The accuracy analysis result showed that for all six target sections, the overall accuracy was 93.95% and the Kappa coefficient was 0.93, showing an excellent result.
Supervised classification and improved filtering method for shoreline detection.Dr Amira Bibo
ABSTRACT
Shoreline monitoring is important to overcome the problems in the measurement of the shoreline. Recently,
many researchers have directed attention to methods of predicting shoreline changes by the use of
multispectral images. However, the images being captured tend to have several problems due to the weather.
Therefore, identification of multi class features which includes vegetation and shoreline using multispectral
satellite image is one of the challenges encountered in the detection of shoreline. An efficient framework
using the near infrared–histogram equalisation and improved filtering method is proposed to enhance the
detection of the shoreline in Tanjung Piai, Malaysia, by using SPOT-5 images. Sub-pixel edge detection andthe Wallis filter are used to compute the edge location with the subpixel accuracy and reduce the noise. Then,the image undergoes image classification process by using Support Vector Machine. The proposed method performed more effectively and reliable in preserving the missing line of the shoreline edge in the SPOT-5
images.
Using Remote Sensing Techniques For Monitoring Ecological Changes In Lakes: C...IJERA Editor
The ability to use remote sensing in studying lake ecology lies in the capability of satellite sensors to measure
the spectral reflectance of constituents in water bodies. This reflectance can be used to determine the
concentration of the constituents of the water column through mathematical relationships. This work identified a
simple linear equation for estimating suspended matter in Lake Naivasha with reflectance in Landsat7 ETM+
image. A R² = 0.94, n = 6 for suspended matter was obtained. Archive of Landsat imagery was used to
produce maps of suspended matter concentrations in the lake. The suspended matter concentrations at five
different locations in the lake over 30 year’s period were then estimated. It was therefore concluded that the
ecological changes Lake Naivasha is experiencing is the result of the high water abstraction and the effect of
climate change.
An Automated Approach of Shoreline Detection Applied to Digital Videos using ...Dwi Putra Asana
Abstract: This study aims to detect a shoreline location and its changes automatically in the temporal resolution.
This approach is implemented on the coastal video monitoring system applications. The proposed method applied
data mining by using two main systems-a training system using classification and shoreline detection systems with
Self-Organizing Map (SOM) and K-Nearest Neighbor (K-NN) algorithms. The training system performs feature
texture extraction using agray-level co-occurrence matrix and the results are stored to classification process. The
detection system has five processing stages: contrast stretching preprocessing and morphological contrast
enhancement, SOM clustering, morphological operations, feature extraction and K-NN classification and detection
shoreline. Preprocessing was used to improve the video image contrast and reliability. SOM algorithm in
segmenting objects in the onshore video images. Morphological operations were applied to eliminate noise on the
objects that were not needed in the spatial domain. The segmentation results of video frames classified by K-NN.
The aim is to provide the class labels on each region segmentation results, namely, sea label, land label and sky
label. The determination of the shoreline is done by scanning the neighboring pixels from the edge of land class
label after binary image transformation. The shoreline change detection was performed by comparing the position of
existing shoreline and shoreline position in the reference video frame. A Receiver Operating Characteristic (ROC)
curve was used to evaluate the performance of shoreline detection systems. The results showed that the combination
of SOM and K-NN was able to detect shoreline and its changes accurately
study and analysis of hy si data in 400 to 500IJAEMSJORNAL
The ability to extract information about world and present it in way that our visual perception can comprehend is ultimate goal of imaging science in remote sensing .Hyperspectral imaging system is most powerful tool in the field of remote sensing also called as imaging spectroscopy, It is new technique used by researcher to detect terrestrial, vegetation and mineral. This paper reports analysis of hyperspectral images. Firstly the hyperspectral image analyzed by using supervised classification of Amravati region from Maharashtra province of India. The report reveals spectral analysis of Amravati region. We acquired satellite imagery to perform the classification using maximum like hood classifier. Analysis is performing in ERDAS to determine the spectral reflectance against the no of band. The analytical outcome of paper is representing the soil, water, vegetation index of the region.
Water-Body Area Extraction From High Resolution Satellite Images-An Introduct...CSCJournals
Water resources play an important role in region planning, natural disaster, industrial and agricultural production and so on. Surveying of water-bodies and delineate its features properly is very first step for any planning, especially for places like India, where the land-cover is dominated by water-bodies. Recording images, such as from satellite, sometimes does not reflect the distinguished characteristics of water with non-water features, e.g. shadows of super structures. Image of water body is confused easily with the shadow of skyscraper, since calm water surface induces mirror reflection when it gives birth to echo wave. Over the past decade, a significant amount of research been conducted to extract the water body information from multi-resolution satellite image. The objective of this paper is to review methodologies applied for water body extraction using satellite remote sensing. First, studies on water body detection are treated. Methodological issues related to the use of these methods were summarized. Results from empirical studies, applying water-body extraction techniques are collected and discussed. Important issues for future research are also identified and discussed.
A Review of Change Detection Techniques of LandCover Using Remote Sensing Dataiosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
The study was carried out using the UAV for analyzing the characteristics of debris in order to present the methodology to estimate the quantitative amount of debris caught in small river facilities. A total of six small rivers that maintained the form of a natural river were selected for collecting UAV images, and the grouping of each target in the image was carried out using the object-based classification method, and based on the object-based classification result of the UAV images, the land cover classification for the status of factors causing the generation of debris for six target sections was carried out by applying the screen digitizing method. In addition, in order to verify the accuracy of the classification result, the error matrix was performed, securing the reliability of the result. The accuracy analysis result showed that for all six target sections, the overall accuracy was 93.95% and the Kappa coefficient was 0.93, showing an excellent result.
Supervised classification and improved filtering method for shoreline detection.Dr Amira Bibo
ABSTRACT
Shoreline monitoring is important to overcome the problems in the measurement of the shoreline. Recently,
many researchers have directed attention to methods of predicting shoreline changes by the use of
multispectral images. However, the images being captured tend to have several problems due to the weather.
Therefore, identification of multi class features which includes vegetation and shoreline using multispectral
satellite image is one of the challenges encountered in the detection of shoreline. An efficient framework
using the near infrared–histogram equalisation and improved filtering method is proposed to enhance the
detection of the shoreline in Tanjung Piai, Malaysia, by using SPOT-5 images. Sub-pixel edge detection andthe Wallis filter are used to compute the edge location with the subpixel accuracy and reduce the noise. Then,the image undergoes image classification process by using Support Vector Machine. The proposed method performed more effectively and reliable in preserving the missing line of the shoreline edge in the SPOT-5
images.
Seagrass Mapping and Monitoring Along the Coasts of Crete, GreeceUniversität Salzburg
This research proposal introduces MSc thesis research. Study object is seagrass Posidonia oceanic (P. oceanica) along the coast of Crete, Greece. The most important facts about seagrass: endemic Mediterranean seagrass, P. oceanica is a main species in marine coastal environment of Greece. P. oceanica is the largest, the most widespread, homogeneous, dense “mattes” forming meadows between 5-40 m in Mediterranean Sea. Seagrass is a component of coastal ecosystems of high importance for the marine life, playing important functions in the marine environment. Seagrasses are subjects to external factors and therefore have environmental vulnerability. The study area is located in General research area: Island of Crete, Greece. Seagrass sampling will be performed at three stations at a depth of 6-7 m: Heraklio, Agia Pelagia, Xerokampos, Crete Island, Greece. The general research objectives of the MSc research includes GIS and environmental analysis: 1) Mapping the extent of the spatial distribution of seagrass P. oceanica along the northern coast of Crete; 2) Monitoring environmental changes in seagrass meadows in the selected fieldwork sites (Agia Pelagia, Xerokampos) over the 10-year period (2000-2010). There are various multi-sources data proposed for using in spatial analysis. data of the previous measurements received during the last year fieldwork, to analyze whether P.oceanica is spectrally distinct from other sea floor types, using the differences in the spectral signatures on the graphs in a WASI, the Water Color Simulator software. Other data include satellite images from the open sources (Landsat TM), aerial images, Google Earth; underwater videographic measurements of 3 cameras Olympus ST 8000 made during the ship route (ca 20 total in the selected areas of the research places) resulting in series of consequent images, completely covering the area under the boat path; in-situ measurements of the seagrass in selected spots, using measurement frame and other devices for marine biological research for the validation of the results. Arc GIS vector layers of Crete island and surroundings (.shp files). Hypothesis testis is formulated for the proposed research, questions defined, methods prepared and planned. The research work is expected to have following results : Over the northern coasts of Crete: thematic maps showing seafloor types and seagrass P.oceanica spatial distribution along the coasts of Crete. Within the fieldwork locations, Ligaria beach: monitoring the environmental changes, based on the classification of the satellite and aerial imagery and fieldwork video camera footage. Within the fieldwork locations : maps of the sea floor cover types, based on the fieldwork measurements and UVM. Results of the WASI spectral analysis illustrating graphs of the spectral reflectance of different sea floor types (sand, P.oceanica, rocky, etc) at various depths (0.5-4 m), based on the results of 20.Precise, correct and up-to-date information about th
SBL offers a comprehensive range of geospatial services that address the varied needs of consumers, businesses, and government agencies.We have highly qualified team members to provide you with good services in terms of perfection, time, and cost.
DEVELOPING THE OPTIMIZED OCEAN CURRENT STRENGTHENING DESALINATION SEMI-PERMEA...ijbesjournal
Alongside improvements in desalination operation and development of new technologies, problems of weakened counter current and global warming have emerged. Therefore, our study suggests a new desalination model, based on the experimental Support Vector Machine (SVM) algorithm, for semipermeable membrane separation. First, the reverse osmosis (RO) process used semi-permeable membrane and osmotic pressure to remove the solutes dissolved in seawater and obtain pure freshwater. The desalination process also applied MSF and MED, which are the best technologies developed through elimination of various problems that were previously experienced. This research is directed towards suggesting a model that can effectively create the semi-permeable membrane used in the desalination process. To efficiently prevent a counter current and safely obtain the water resources, an innovative technology is suggested by applying Genetic Algorithm (GA) to the SVM model for the semi-p
Research Inventy : International Journal of Engineering and Science is published by the group of young academic and industrial researchers with 12 Issues per year. It is an online as well as print version open access journal that provides rapid publication (monthly) of articles in all areas of the subject such as: civil, mechanical, chemical, electronic and computer engineering as well as production and information technology. The Journal welcomes the submission of manuscripts that meet the general criteria of significance and scientific excellence. Papers will be published by rapid process within 20 days after acceptance and peer review process takes only 7 days. All articles published in Research Inventy will be peer-reviewed.
DUAL-CHANNEL MODEL FOR SHALLOW WATER DEPTH RETRIEVAL FROM WORLDVIEW-3 IMAGERY...Luhur Moekti Prayogo
This research aims to estimate shallow water depth using Worldview 3 satellite imagery and dual-channel models in Karimunjawa waters, Central Java – Indonesia. To build dual-channel models, we used spectral data that had been validated in the field. Twenty-three depth data were recorded synchronous to the spectral data used in forming the semianalytical dual-channel models. Twelve models were tested using 633 depth data with a non-linear model using multiple polynomial regression analysis degrees 1 and 2. This research has shown that the proposed model has been confirmed to improve depth accuracy. Models using blue and green channels of Worldview 3 image result in good accuracies especially for estimating depths with interval from 5 to 20 meters with RMSE of 1,592 meters (5–10 meters), 2,099 meters (10–15 meters), and 1,239 meters (15–20 meters). The wavelengths of two channels have a low absorption rate to penetrate deeper waters than other wavelengths. The research also finds out that there are still models that meet the IHO standard criteria.
Using Remote Sensing Techniques For Monitoring Ecological Changes In Lakes: C...IJERA Editor
The ability to use remote sensing in studying lake ecology lies in the capability of satellite sensors to measure
the spectral reflectance of constituents in water bodies. This reflectance can be used to determine the
concentration of the constituents of the water column through mathematical relationships. This work identified a
simple linear equation for estimating suspended matter in Lake Naivasha with reflectance in Landsat7 ETM+
image. A R² = 0.94, n = 6 for suspended matter was obtained. Archive of Landsat imagery was used to
produce maps of suspended matter concentrations in the lake. The suspended matter concentrations at five
different locations in the lake over 30 year’s period were then estimated. It was therefore concluded that the
ecological changes Lake Naivasha is experiencing is the result of the high water abstraction and the effect of
climate change.
Remote sensing data driven bathing water quality assessment using sentinel-3nooriasukmaningtyas
In this paper we are investigating the possibility of usage of remote sensing satellite data, more precisely sentinel-3 OLCI and SLSTR data, for assessment of bathing water quality. In this research we used data driven approach and analysis of data in order to pinpoint aspects of remote sensing data that can be useful for bathing water quality assessment. For this purpose we collected satellite images for period from start of June till end of September of 2019 and results of in-situ measurement for the same period . Results of in-situ measurement were correlated with satellite images bands and analyzed. We propose a simple method for rapid assessment of possible deterioration of bathing water quality to be used by public health authorities for better planning of in situ measurements. Results of implementation of predictive models based on k-nearest neighbour (KNN) and decision tree (DT) are described.
Seagrass Mapping and Monitoring Along the Coasts of Crete, GreeceUniversität Salzburg
This research proposal introduces MSc thesis research. Study object is seagrass Posidonia oceanic (P. oceanica) along the coast of Crete, Greece. The most important facts about seagrass: endemic Mediterranean seagrass, P. oceanica is a main species in marine coastal environment of Greece. P. oceanica is the largest, the most widespread, homogeneous, dense “mattes” forming meadows between 5-40 m in Mediterranean Sea. Seagrass is a component of coastal ecosystems of high importance for the marine life, playing important functions in the marine environment. Seagrasses are subjects to external factors and therefore have environmental vulnerability. The study area is located in General research area: Island of Crete, Greece. Seagrass sampling will be performed at three stations at a depth of 6-7 m: Heraklio, Agia Pelagia, Xerokampos, Crete Island, Greece. The general research objectives of the MSc research includes GIS and environmental analysis: 1) Mapping the extent of the spatial distribution of seagrass P. oceanica along the northern coast of Crete; 2) Monitoring environmental changes in seagrass meadows in the selected fieldwork sites (Agia Pelagia, Xerokampos) over the 10-year period (2000-2010). There are various multi-sources data proposed for using in spatial analysis. data of the previous measurements received during the last year fieldwork, to analyze whether P.oceanica is spectrally distinct from other sea floor types, using the differences in the spectral signatures on the graphs in a WASI, the Water Color Simulator software. Other data include satellite images from the open sources (Landsat TM), aerial images, Google Earth; underwater videographic measurements of 3 cameras Olympus ST 8000 made during the ship route (ca 20 total in the selected areas of the research places) resulting in series of consequent images, completely covering the area under the boat path; in-situ measurements of the seagrass in selected spots, using measurement frame and other devices for marine biological research for the validation of the results. Arc GIS vector layers of Crete island and surroundings (.shp files). Hypothesis testis is formulated for the proposed research, questions defined, methods prepared and planned. The research work is expected to have following results : Over the northern coasts of Crete: thematic maps showing seafloor types and seagrass P.oceanica spatial distribution along the coasts of Crete. Within the fieldwork locations, Ligaria beach: monitoring the environmental changes, based on the classification of the satellite and aerial imagery and fieldwork video camera footage. Within the fieldwork locations : maps of the sea floor cover types, based on the fieldwork measurements and UVM. Results of the WASI spectral analysis illustrating graphs of the spectral reflectance of different sea floor types (sand, P.oceanica, rocky, etc) at various depths (0.5-4 m), based on the results of 20.Precise, correct and up-to-date information about th
SBL offers a comprehensive range of geospatial services that address the varied needs of consumers, businesses, and government agencies.We have highly qualified team members to provide you with good services in terms of perfection, time, and cost.
DEVELOPING THE OPTIMIZED OCEAN CURRENT STRENGTHENING DESALINATION SEMI-PERMEA...ijbesjournal
Alongside improvements in desalination operation and development of new technologies, problems of weakened counter current and global warming have emerged. Therefore, our study suggests a new desalination model, based on the experimental Support Vector Machine (SVM) algorithm, for semipermeable membrane separation. First, the reverse osmosis (RO) process used semi-permeable membrane and osmotic pressure to remove the solutes dissolved in seawater and obtain pure freshwater. The desalination process also applied MSF and MED, which are the best technologies developed through elimination of various problems that were previously experienced. This research is directed towards suggesting a model that can effectively create the semi-permeable membrane used in the desalination process. To efficiently prevent a counter current and safely obtain the water resources, an innovative technology is suggested by applying Genetic Algorithm (GA) to the SVM model for the semi-p
Research Inventy : International Journal of Engineering and Science is published by the group of young academic and industrial researchers with 12 Issues per year. It is an online as well as print version open access journal that provides rapid publication (monthly) of articles in all areas of the subject such as: civil, mechanical, chemical, electronic and computer engineering as well as production and information technology. The Journal welcomes the submission of manuscripts that meet the general criteria of significance and scientific excellence. Papers will be published by rapid process within 20 days after acceptance and peer review process takes only 7 days. All articles published in Research Inventy will be peer-reviewed.
DUAL-CHANNEL MODEL FOR SHALLOW WATER DEPTH RETRIEVAL FROM WORLDVIEW-3 IMAGERY...Luhur Moekti Prayogo
This research aims to estimate shallow water depth using Worldview 3 satellite imagery and dual-channel models in Karimunjawa waters, Central Java – Indonesia. To build dual-channel models, we used spectral data that had been validated in the field. Twenty-three depth data were recorded synchronous to the spectral data used in forming the semianalytical dual-channel models. Twelve models were tested using 633 depth data with a non-linear model using multiple polynomial regression analysis degrees 1 and 2. This research has shown that the proposed model has been confirmed to improve depth accuracy. Models using blue and green channels of Worldview 3 image result in good accuracies especially for estimating depths with interval from 5 to 20 meters with RMSE of 1,592 meters (5–10 meters), 2,099 meters (10–15 meters), and 1,239 meters (15–20 meters). The wavelengths of two channels have a low absorption rate to penetrate deeper waters than other wavelengths. The research also finds out that there are still models that meet the IHO standard criteria.
Using Remote Sensing Techniques For Monitoring Ecological Changes In Lakes: C...IJERA Editor
The ability to use remote sensing in studying lake ecology lies in the capability of satellite sensors to measure
the spectral reflectance of constituents in water bodies. This reflectance can be used to determine the
concentration of the constituents of the water column through mathematical relationships. This work identified a
simple linear equation for estimating suspended matter in Lake Naivasha with reflectance in Landsat7 ETM+
image. A R² = 0.94, n = 6 for suspended matter was obtained. Archive of Landsat imagery was used to
produce maps of suspended matter concentrations in the lake. The suspended matter concentrations at five
different locations in the lake over 30 year’s period were then estimated. It was therefore concluded that the
ecological changes Lake Naivasha is experiencing is the result of the high water abstraction and the effect of
climate change.
Remote sensing data driven bathing water quality assessment using sentinel-3nooriasukmaningtyas
In this paper we are investigating the possibility of usage of remote sensing satellite data, more precisely sentinel-3 OLCI and SLSTR data, for assessment of bathing water quality. In this research we used data driven approach and analysis of data in order to pinpoint aspects of remote sensing data that can be useful for bathing water quality assessment. For this purpose we collected satellite images for period from start of June till end of September of 2019 and results of in-situ measurement for the same period . Results of in-situ measurement were correlated with satellite images bands and analyzed. We propose a simple method for rapid assessment of possible deterioration of bathing water quality to be used by public health authorities for better planning of in situ measurements. Results of implementation of predictive models based on k-nearest neighbour (KNN) and decision tree (DT) are described.
Mangrove Vegetation Mapping Using Sentinel-2A Imagery Based on Google Earth E...Luhur Moekti Prayogo
Mangroves are trees whose habitat is affected by tides, and their presence has decreased from year to year. Today, mapping technology has undergone many developments, including the availability of images of various resolutions and cloud-based image processing. One of the popular platforms today is the Google Earth Engine. Google Earth Engine is a cloud-based platform that makes it easy to access high-performance computing resources for extensive processing. The advantage of using Google Earth Engine is that users do not have to be IT experts without experts in application development, WEB programming, and HTML. This study aims to conduct a study on mangrove mapping in Gili Genting District with Sentinel-2A imagery using a Google Earth Engine. This location was chosen since there are still many mangroves, especially on the Gili Raja and Gili Genting Islands. From this research, it can be concluded that cloud computing-based Sentinel-2A image processing shows that the vegetation value of NDVI results ranges from -0.923208 to 0.75579. The classification results show that mangrove forests' overall presence on Gili Genting Island is more expansive than Gili Raja Island with 16.74 ha and 14.75 ha. The use of the Google Earth Engine platform simplifies the analysis process because image processing can be done once with various scripts so that analysis becomes faster.
Comparing canopy density measurement from UAV and hemispherical photography: ...IJECEIAES
UAV and hemispherical photography are common methods used in canopy density measurement. These two methods have opposite viewing angles where hemispherical photography measures canopy density upwardly, while UAV captures images downwardly. This study aims to analyze and compare both methods to be used as the input data for canopy density estimation when linked with a lower spatial resolution of remote sensing data i.e. Landsat image. We correlated the field data of canopy density with vegetation indices (NDVI, MSAVI, and AFRI) from Landsat-8. The canopy density values measured from UAV and hemispherical photography displayed a strong relationship with 0.706 coefficient of correlation. Further results showed that both measurements can be used in canopy density estimation using satellite imagery based on their high correlations with Landsat-based vegetation indices. The highest correlation from downward and upward measurement appeared when linked with NDVI with a correlation of 0.962 and 0.652, respectively. Downward measurement using UAV exhibited a higher relationship compared to hemispherical photography. The strong correlation between UAV data and Landsat data is because both are captured from the vertical direction, and 30 m pixel of Landsat is a downscaled image of the aerial photograph. Moreover, field data collection can be easily conducted by deploying drone to cover inaccessible sample plots.
Residual Analysis and Tidal Harmonic Components in Bangkalan Regency, East JavaLuhur Moekti Prayogo
Bangkalan Regency is one of Madura, East Java, where some of its areas are located in a coastal environment. The coastal environment can experience economic development due to the transportation aspect so that many industries have been established in that environment. Studies on oceanographic parameters are essential because management of coastal environments can not be separated from oceanographic information: The tides information about the tidal characteristics can be obtained after performing a harmonic analysis, which produces the value of harmonic components. This study analyses the residue and tidal harmonic components using the LP-Tides Matlab software in the Sepulu district, Bangkalan Regency, East Java. The data used are January 2021 data from the Geospatial Information Agency. This research shows that the main harmonic components generated include K2, M4, MS4, M2, S2, N2, K1, O1, and P1. The tidal type shows that the Sepulu district is a semi-diurnal type with a Formzahl number = 0.08566. The maximum observation and prediction data values for January 2021 in the Sepulu district are 978 and 1273.64 mm. The MSL value is 434 mm, with an average tidal residue value between the observation and predictive data = 166.01 mm. Then the calculation of the RMSE value and standard deviations are 12.88 and 125.90 mm
Automated Extraction of Shoreline in Tuban Regency, East Java from Google Ear...Luhur Moekti Prayogo
The edges generated using the Cannyalgorithm are practical in interpreting shorelines and making analysis faster. In the future,there is a need for more elaboration regarding the use of Google Earth imagery in shorelineanalysis, especially in geometric corrections (Georeference). This elaboration is essentialbecause it will affect the analysis results, especially the shoreline position.
BENTHIC DIVERSITY MAPPING AND ANALYSIS BASE ON REMOTE SENSING AND SEASCAPE EC...IAEME Publication
Mapping of coral reef ecosystem by using remote sensing either from satellite
platform has been acknowledging as an essential tool. Seascape ecology is the study
of seascape patterns, interaction among patches within a seascape mosaic and how
these patterns and interactions change over time. The objectives of this study are to
produce a benthic map, measure the benthic diversity matrix and to compare the
diversity matrix among different seascape area at Parang Islands shallow waters in
the eastern part of Karimunjawa National Park, Indonesia. The high-resolution
satellite image that has been used in this study was from GeoEye-1 to map the
benthic. Fragstats is used to measure and analyze the diversity metric values for the
benthic consist of live coral, DCA, seagrass, etc. This research produces benthic
ecosystem map consists of eight benthic classes. The diversity metric index shows that
the southern seascape region of this island has the highest diversity
Extraction of Water-body Area from High-resolution Landsat Imagery IJECEIAES
Extraction of water bodies from satellite imagery has been broadly explored in the current decade. So many techniques were involved in detecting of the surface water bodies from satellite data. To detect and extracting of surface water body changes in Nagarjuna Sagar Reservoir, Andhra Pradesh from the period 1989 to 2017, were calculated using Landsat-5 TM, and Landsat-8 OLI data. Unsupervised classification and spectral water indexing methods, including the Normalized Difference Vegetation Index (NDVI), Normalized Difference Moisture Index (NDMI), Normalized Difference Water Index (NDWI), and Modified Normalized Difference Water Index (MNDWI), were used to detect and extraction of the surface water body from satellite data. Instead of all index methods, the MNDWI was performed better results. The Reservoir water area was extracted using spectral water indexing methods (NDVI, NDWI, MNDWI, and NDMI) in 1989, 1997, 2007, and 2017. The shoreline shrunk in the twenty-eight-year duration of images. The Reservoir Nagarjuna Sagar lost nearly around one-fourth of its surface water area compared to 1989. However, the Reservoir has a critical position in recent years due to changes in surface water and getting higher mud and sand. Maximum water surface area of the Reservoir will lose if such decreasing tendency follows continuously.
Snow Cover Estimation from Resourcesat-1 AWiFS – Image Processing with an Aut...CSCJournals
Snow and glaciers cover large areas of Himalayas. The resulting runoff from snow and glacier melt provides nearly 30-50% of the total annual water outlay of most of the rivers in north India. Hence, there is a need for regular monitoring of the Himalayan snow cover area. The Normalized Difference Snow index (NDSI) technique for automated detection of snow cover from remotely sensed data has limitations in the detection of snow under shadow and exclusion of water. A new automated snow cover estimation algorithm to overcome the these limitations has been developed using the spectral information from all the spectral bands of Resourcesat-1 AWiFS sensor. The automated algorithm has been implemented in hierarchical logical steps. Algorithm has been validated by comparing the results obtained with Hall’s and Kulkarni’s methods and observed that the new algorithm performs better than other methods in the elimination of noise, while detecting the snow covered pixels in deep mountain shadows. Satisfactory results have been obtained when used with several temporal images of large image mosaics which has been presented in this study. This algorithm has been evaluated with Landsat ETM and IRS LISS III which has similar spectral bands with different spatial and radiometric resolutions and the algorithm has been found to be working satisfactorily. The algorithm has been found to be useful for regular periodic monitoring of snow cover area..
Automatic traffic light controller for emergency vehicle using peripheral int...IJECEIAES
Traffic lights play such important role in traffic management to control the traffic on the road. Situation at traffic light area is getting worse especially in the event of emergency cases. During traffic congestion, it is difficult for emergency vehicle to cross the road which involves many junctions. This situation leads to unsafe conditions which may cause accident. An Automatic Traffic Light Controller for Emergency Vehicle is designed and developed to help emergency vehicle crossing the road at traffic light junction during emergency situation. This project used Peripheral Interface Controller (PIC) to program a priority-based traffic light controller for emergency vehicle. During emergency cases, emergency vehicle like ambulance can trigger the traffic light signal to change from red to green in order to make clearance for its path automatically. Using Radio Frequency (RF) the traffic light operation will turn back to normal when the ambulance finishes crossing the road. Result showed the design is capable to response within the range of 55 meters. This project was successfully designed, implemented and tested.
Similar to Shallow Water Depth Mapping Using Single Band and Band Ratio on High-Resolution Imagery (20)
Pelatihan Pemanfaatan Teknologi AI dalam Pembuatan PTK bagi Guru SDN Karangas...Luhur Moekti Prayogo
The purpose of this study is to increase a solid understanding for teachers of SDN Karangasem, Jenu about the basic concepts of AI, including how AI works, the types of algorithms used and teachers can overcome their lack of knowledge in utilization in improving the quality of learning and preparing students to face an increasingly connected and technology-oriented world. The method used by an extension is to increase teacher understanding of the importance of PTK in improving the quality of education. And the implementation of socialization regarding the process and steps in making PTK with the help of AI technology through GPT Chat media. The results obtained that advances in Artificial Intelligence Technology help teachers to create a learning process that is more exciting/interesting and not boring with various applications available and eases the task of teachers in the evaluation or administration process.
Penginderaan Jauh - Prinsip Dasar Penginderaan Jauh (By. Pratiwi)Luhur Moekti Prayogo
Tugas 1 Mata Kuliah Penginderaan Jauh (3 SKS), Nama : Pratiwi, NIM : 1310210001, Dosen Pengampu: Luhur Moekti Prayogo, S.Si., M.Eng, Program Studi Ilmu Kelautan, Fakultas Perikanan dan Kelautan, Universitas PGRI Ronggolawe Tuban 2023
Penginderaan Jauh - Prinsip Dasar Penginderaan Jauh (By. Udis Sunardi)Luhur Moekti Prayogo
Tugas 1 Mata Kuliah Penginderaan Jauh (3 SKS), Nama : Udis Sunardi, NIM : 1310210011, Dosen Pengampu: Luhur Moekti Prayogo, S.Si., M.Eng, Program Studi Ilmu Kelautan, Fakultas Perikanan dan Kelautan, Universitas PGRI Ronggolawe Tuban 2023
Penginderaan Jauh - Prinsip Dasar Penginderaan Jauh (By. Saiful Mukminin)Luhur Moekti Prayogo
Tugas 1 Mata Kuliah Penginderaan Jauh (3 SKS), Nama : Saiful Mukminin, NIM : 1310210008, Dosen Pengampu: Luhur Moekti Prayogo, S.Si., M.Eng, Program Studi Ilmu Kelautan, Fakultas Perikanan dan Kelautan, Universitas PGRI Ronggolawe Tuban 2023
Penginderaan Jauh - Prinsip Dasar Penginderaan Jauh (By. Maryoko)Luhur Moekti Prayogo
Tugas 1 Mata Kuliah Penginderaan Jauh (3 SKS), Nama : Maryoko, NIM : 1310210015, Dosen Pengampu: Luhur Moekti Prayogo, S.Si., M.Eng, Program Studi Ilmu Kelautan, Fakultas Perikanan dan Kelautan, Universitas PGRI Ronggolawe Tuban 2023
Penginderaan Jauh - Prinsip Dasar Penginderaan Jauh (By. Fajar Kurniawan)Luhur Moekti Prayogo
Tugas 1 Mata Kuliah Penginderaan Jauh (3 SKS), Nama : Fajar Kurniawan, NIM : 1310210012, Dosen Pengampu: Luhur Moekti Prayogo, S.Si., M.Eng, Program Studi Ilmu Kelautan, Fakultas Perikanan dan Kelautan, Universitas PGRI Ronggolawe Tuban 2023
Penginderaan Jauh - Prinsip Dasar Penginderaan Jauh (By. Agus Vandiharjo)Luhur Moekti Prayogo
Tugas 1 Mata Kuliah Penginderaan Jauh (3 SKS), Nama : Agus Vandiharjo, NIM : 1310210009, Dosen Pengampu: Luhur Moekti Prayogo, S.Si., M.Eng, Program Studi Ilmu Kelautan, Fakultas Perikanan dan Kelautan, Universitas PGRI Ronggolawe Tuban 2023
Penetapan dan Penegasan Batas Laut - Sengketa Wilayah Kepulauan Spartly di La...Luhur Moekti Prayogo
Tugas 1 Mata Kuliah Penetapan dan Penegasan Batas Laut (3 SKS), Nama : Ristyan Tri Rahayu, NIM : 131021001, Dosen Pengampu: Luhur Moekti Prayogo, S.Si., M.Eng, Program Studi Ilmu Kelautan, Fakultas Perikanan dan Kelautan, Universitas PGRI Ronggolawe Tuban 2023
Penetapan dan Penegasan Batas Laut - Sengketa Wilayah Kepulauan Spartly di La...Luhur Moekti Prayogo
Tugas 1 Mata Kuliah Penetapan dan Penegasan Batas Laut (3 SKS), Nama : Saiful Mukminin, NIM : 1310210008, Dosen Pengampu: Luhur Moekti Prayogo, S.Si., M.Eng, Program Studi Ilmu Kelautan, Fakultas Perikanan dan Kelautan, Universitas PGRI Ronggolawe Tuban 2023
Penetapan dan Penegasan Batas Laut - Sengketa Wilayah Kepulauan Spartly di La...Luhur Moekti Prayogo
Tugas 1 Mata Kuliah Penetapan dan Penegasan Batas Laut (3 SKS), Nama : Pratiwi, NIM : 1310210001, Dosen Pengampu: Luhur Moekti Prayogo, S.Si., M.Eng, Program Studi Ilmu Kelautan, Fakultas Perikanan dan Kelautan, Universitas PGRI Ronggolawe Tuban 2023
Penetapan dan Penegasan Batas Laut - Sengketa Wilayah Kepulauan Spartly di La...Luhur Moekti Prayogo
Tugas 1 Mata Kuliah Penetapan dan Penegasan Batas Laut (3 SKS), Nama : Maryoko, NIM : 1310210015, Dosen Pengampu: Luhur Moekti Prayogo, S.Si., M.Eng, Program Studi Ilmu Kelautan, Fakultas Perikanan dan Kelautan, Universitas PGRI Ronggolawe Tuban 2023
Analisis Komponen Harmonik dan Elevasi Pasang Surut pada Alur Pelayaran Perai...Luhur Moekti Prayogo
Cilacap merupakan kabupaten yang mempunyai luas area mencapai 225.360,840 ha yang terletak pada wilayah Jawa Tengah bagian selatan. Kabupaten ini menghadap langsung dengan Samudera Indonesia disebelah selatannya. Karakteristik elevasi harmonik suatu wilayah perairan bermanfaat untuk mengetahui interaksi pembentuk pasang surut pada wilayah tertentu. Hal ini dibutuhkan untuk keperluan pengelolaan lingkungan lebih lanjut serta bangunan pantai dan kegiatan lain di wilayah pesisir. Penelitian ini dilakukan menggunakan data primer berupa data elevasi pasang surut yang terekam setiap jam selama satu 31 hari pada bulan Januari 2019. Analisis harmonik menggunakan T-Tide untuk mengekstrak komponen-komponen pasang surut. Komponen pasut yang dominan diantaranya Q1, O1, NO1, K1, N2, M2. Perairan cilacap memiliki tipe pasang surut yang diklasifikasikan sebagai pasang surut campuran condong harian ganda dengan nilai indeks Formzahl sebesar 0.531856. Elevasi muka air laut di Perairan Cilacap MSL yang menunjukan nilai rata-rata muka air laut sebesar 3.46m, HAT 4.74m, MHWL 4.3m, MLWL 2.62m dan LAT 2.18m.
Land Cover Classification Assessment Using Decision Trees and Maximum Likelih...Luhur Moekti Prayogo
Classification technique on remote sensing images is an effort taken to identify the class of each pixel based on the spectral characteristics of various channels. Traditional classifications such as Maximum Likelihood are based on statistical parameters such as standard deviation and mean, which have a probability model of each pixel in each class. While the object-based classification method, one of which is the Decision Trees, is based on rules for each class with mathematical functions. This study compares the Decision Trees and Maximum Likelihood algorithms for land cover classification in the Surabaya and Bangkalan areas using Landsat 8 data. This research begins with creating Regions of Interest (ROIs) and Rules on images with greater than and less than functions for Decision Trees. The ROIs test was carried out using the Separability Index and matching each class using the Confusion Matrix. The experimental results show that the accuracy value resulting from the Confusion Matrix calculation is 90.48%, with a Kappa Coefficient Value of 0.87. The Decision Trees method produces land cover nigher to the actual condition than the Maximum Likelihood method. The difference in the class distribution of the two ways is not significant. This study is limited because the validation uses manual interpretation results. Future research is expected to use the large-scale classification results from the relevant agencies to verify the classification results and use field data, larger samples of ROIs, and the use of high-resolution imagery in order to improve the classification results.
Tugas 1 Mata Kuliah Mitigasi Bencana Pesisir (3 SKS), Nama : Imam Asghoni Mahali, NIM : 1310190011, Dosen Pengampu: Luhur Moekti Prayogo, S.Si., M.Eng, Program Studi Ilmu Kelautan, Fakultas Perikanan dan Kelautan, Universitas PGRI Ronggolawe Tuban 2023
Mitigasi Bencana Pesisir - Pembuatan Bangunan Tahan Gempa (By. Nur Uswatun Ch...Luhur Moekti Prayogo
Tugas 1 Mata Kuliah Mitigasi Bencana Pesisir (3 SKS), Nama : Nur Uswatun Chasanah, NIM : 1310190015, Dosen Pengampu: Luhur Moekti Prayogo, S.Si., M.Eng, Program Studi Ilmu Kelautan, Fakultas Perikanan dan Kelautan, Universitas PGRI Ronggolawe Tuban 2023
Mitigasi Bencana Pesisir - Memberikan Penyuluhan dan Meningkatkan Kesadaran M...Luhur Moekti Prayogo
Tugas 1 Mata Kuliah Mitigasi Bencana Pesisir (3 SKS), Nama : Abdul Wahid, NIM : 1310190016, Dosen Pengampu: Luhur Moekti Prayogo, S.Si., M.Eng, Program Studi Ilmu Kelautan, Fakultas Perikanan dan Kelautan, Universitas PGRI Ronggolawe Tuban 2023
Mitigasi Bencana Pesisir - Bangunan Pelindung Pantai Sebagai Penanggulangan A...Luhur Moekti Prayogo
Tugas 1 Mata Kuliah Mitigasi Bencana Pesisir (3 SKS), Nama : Putri Widyawati Nur Adimah, NIM : 1310190004, Dosen Pengampu: Luhur Moekti Prayogo, S.Si., M.Eng, Program Studi Ilmu Kelautan, Fakultas Perikanan dan Kelautan, Universitas PGRI Ronggolawe Tuban 2023
Tugas 1 Mata Kuliah Mitigasi Bencana Pesisir (3 SKS), Nama : Dewi Anggraeni, NIM : 1310190001, Dosen Pengampu: Luhur Moekti Prayogo, S.Si., M.Eng, Program Studi Ilmu Kelautan, Fakultas Perikanan dan Kelautan, Universitas PGRI Ronggolawe Tuban 2023
Tugas 1 Mata Kuliah Mitigasi Bencana Pesisir (3 SKS), Nama : Putri Widyawati Nur Adimah, NIM : 1310190008, Dosen Pengampu: Luhur Moekti Prayogo, S.Si., M.Eng, Program Studi Ilmu Kelautan, Fakultas Perikanan dan Kelautan, Universitas PGRI Ronggolawe Tuban 2023
Tugas 1 Mata Kuliah Kenautikaan (3 SKS), Nama : Udis Sunardi, NIM : 13102290011, Dosen Pengampu: Luhur Moekti Prayogo, S.Si., M.Eng, Program Studi Ilmu Kelautan, Fakultas Perikanan dan Kelautan, Universitas PGRI Ronggolawe Tuban 2022
Cancer cell metabolism: special Reference to Lactate PathwayAADYARAJPANDEY1
Normal Cell Metabolism:
Cellular respiration describes the series of steps that cells use to break down sugar and other chemicals to get the energy we need to function.
Energy is stored in the bonds of glucose and when glucose is broken down, much of that energy is released.
Cell utilize energy in the form of ATP.
The first step of respiration is called glycolysis. In a series of steps, glycolysis breaks glucose into two smaller molecules - a chemical called pyruvate. A small amount of ATP is formed during this process.
Most healthy cells continue the breakdown in a second process, called the Kreb's cycle. The Kreb's cycle allows cells to “burn” the pyruvates made in glycolysis to get more ATP.
The last step in the breakdown of glucose is called oxidative phosphorylation (Ox-Phos).
It takes place in specialized cell structures called mitochondria. This process produces a large amount of ATP. Importantly, cells need oxygen to complete oxidative phosphorylation.
If a cell completes only glycolysis, only 2 molecules of ATP are made per glucose. However, if the cell completes the entire respiration process (glycolysis - Kreb's - oxidative phosphorylation), about 36 molecules of ATP are created, giving it much more energy to use.
IN CANCER CELL:
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
introduction to WARBERG PHENOMENA:
WARBURG EFFECT Usually, cancer cells are highly glycolytic (glucose addiction) and take up more glucose than do normal cells from outside.
Otto Heinrich Warburg (; 8 October 1883 – 1 August 1970) In 1931 was awarded the Nobel Prize in Physiology for his "discovery of the nature and mode of action of the respiratory enzyme.
WARNBURG EFFECT : cancer cells under aerobic (well-oxygenated) conditions to metabolize glucose to lactate (aerobic glycolysis) is known as the Warburg effect. Warburg made the observation that tumor slices consume glucose and secrete lactate at a higher rate than normal tissues.
The increased availability of biomedical data, particularly in the public domain, offers the opportunity to better understand human health and to develop effective therapeutics for a wide range of unmet medical needs. However, data scientists remain stymied by the fact that data remain hard to find and to productively reuse because data and their metadata i) are wholly inaccessible, ii) are in non-standard or incompatible representations, iii) do not conform to community standards, and iv) have unclear or highly restricted terms and conditions that preclude legitimate reuse. These limitations require a rethink on data can be made machine and AI-ready - the key motivation behind the FAIR Guiding Principles. Concurrently, while recent efforts have explored the use of deep learning to fuse disparate data into predictive models for a wide range of biomedical applications, these models often fail even when the correct answer is already known, and fail to explain individual predictions in terms that data scientists can appreciate. These limitations suggest that new methods to produce practical artificial intelligence are still needed.
In this talk, I will discuss our work in (1) building an integrative knowledge infrastructure to prepare FAIR and "AI-ready" data and services along with (2) neurosymbolic AI methods to improve the quality of predictions and to generate plausible explanations. Attention is given to standards, platforms, and methods to wrangle knowledge into simple, but effective semantic and latent representations, and to make these available into standards-compliant and discoverable interfaces that can be used in model building, validation, and explanation. Our work, and those of others in the field, creates a baseline for building trustworthy and easy to deploy AI models in biomedicine.
Bio
Dr. Michel Dumontier is the Distinguished Professor of Data Science at Maastricht University, founder and executive director of the Institute of Data Science, and co-founder of the FAIR (Findable, Accessible, Interoperable and Reusable) data principles. His research explores socio-technological approaches for responsible discovery science, which includes collaborative multi-modal knowledge graphs, privacy-preserving distributed data mining, and AI methods for drug discovery and personalized medicine. His work is supported through the Dutch National Research Agenda, the Netherlands Organisation for Scientific Research, Horizon Europe, the European Open Science Cloud, the US National Institutes of Health, and a Marie-Curie Innovative Training Network. He is the editor-in-chief for the journal Data Science and is internationally recognized for his contributions in bioinformatics, biomedical informatics, and semantic technologies including ontologies and linked data.
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
This pdf is about the Schizophrenia.
For more details visit on YouTube; @SELF-EXPLANATORY;
https://www.youtube.com/channel/UCAiarMZDNhe1A3Rnpr_WkzA/videos
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Shallow Water Depth Mapping Using Single Band and Band Ratio on High-Resolution Imagery
1. Shallow Water Depth Mapping Using Single Band and Band Ratio………….................................................................. (Prayogo & Basith)
651
SHALLOW WATER DEPTH MAPPING USING SINGLE BAND AND
BAND RATIO ON HIGH-RESOLUTION IMAGERY
(Pemetaan Kedalaman Perairan Dangkal Menggunakan Single Band dan Band Rasio Pada
Citra Resolusi Tinggi)
Luhur Moekti Prayogo, Abdul Basith
Department of Geodetic Engineering, Universitas Gadjah Mada, Yogyakarta, 55284, Indonesia
Jl. Grafika Bulaksumur No. 2, Senolowo, Sinduadi, Sleman, Daerah Istimewa Yogyakarta, 55281
E-mail: abd_basith@ugm.ac.id
ABSTRACT
One of the availabilities of remote sensing satellite imagery can be used as a provider of shallow sea
depth information using the Satellite-Derived Bathymetry (SDB) technique. This technique's main problem is
the variation in the bottom cover of waters such as coral reefs and seagrass, which distorts the spectral values.
The use of band ratios can normalize variations in bottom water cover. This study compares the single band
algorithm's accuracy with the band ratio depth data obtained by field survey around the port of Karimunjawa
Islands, Central Java. The image used in this study is high-resolution imagery, Worldview 3. Preprocessing
includes Sunglint correction to reduce the effect of sunglint in the waters and correction of depth data so that
the data are free from tides' influence. The bands used are red, green, blue, and Near-Infrared, which results
in 10 combinations. This study indicates that the band ratio method produces a smaller RMSE value than the
single band. The blue/green ratio makes the best depth values with an RMSE of 1.669 meters at a depth of
0-5 meters. In comparison, single-band use shows that the best estimation result is with an RMSE of 2.373
meters in the green band. This study shows that the band ratio method produces better depth estimates than
the single band method.
Keywords: satellite-derived bathymetry, single band, band ratio, Worldview 3, Karimunjawa
ABSTRAK
Ketersediaan citra satelit penginderaan jauh salah satunya dapat dimanfaatkan sebagai penyedia
informasi kedalaman laut dangkal menggunakan teknik Satellite-Derived Bathymetry (SDB). Permasalahan
utama dalam teknik ini adalah beragamnya tutupan dasar perairan seperti terumbu karang dan lamun
sehingga mendistorsi nilai spektral. Penggunaan band rasio memiliki kemampuan untuk menormalisasikan
variasi tutupan dasar perairan. Penelitian ini bertujuan untuk membandingkan akurasi yang dihasilkan
algoritma single band dengan band rasio. Data kedalaman diperoleh dengan survei lapangan di sekitar
pelabuhan Kepulauan Karimunjawa, Jawa Tengah. Citra yang digunakan dalam penelitian ini adalah citra
resolusi tinggi, Worldview 3. Preprocessing meliputi koreksi Sunglint untuk mengurangi efek kilap matahari
yang terjadi di perairan dan koreksi data kedalaman agar data terbebas dari pengaruh pasang surut air laut.
Band yang digunakan yaitu merah, hijau, biru, dan Near-Infrared yang menghasilkan 10 kombinasi. Hasil dari
penelitian ini menunjukkan bahwa metode band rasio menghasilkan nilai RMSE yang lebih kecil dibandingkan
dengan single band. Penggunaan band rasio biru/hijau menghasilkan nilai kedalaman terbaik dengan RMSE
sebesar 1,669 meter pada kedalaman 0-5 meter. Sedangkan penggunaan single band menunjukkan bahwa
hasil estimasi terbaik dengan RMSE sebesar 2,373 meter pada band hijau. Sehingga dari penelitian ini dapat
disimpulkan bahwa metode band rasio menghasilkan estimasi kedalaman lebih baik dibandingkan metode
single band.
Kata kunci: satellite-derived bathymetry, band tunggal, band rasio, Worldview 3, Karimunjawa
INTRODUCTION
Many industries are established in coastal areas because of easy sea transportation access,
which encourages economic growth (Hidayah et al., 2018). The existence of hydro-oceanographic
data, one of which is bathymetry, is an essential parameter in supporting transportation activities.
Conventional bathymetry measurement takes a relatively long time and is expensive, so it is
inefficient. New alternatives are needed in the provision of bathymetric data. The availability of
bathymetric data for all Indonesian coastal areas can be fulfilled, and indirectly, coastal areas'
2. Seminar Nasional Geomatika 2020: Informasi Geospasial untuk Inovasi Percepatan Pembangunan Berkelanjutan
652
economic development will increase. Technological advances are in line with advances in the remote
sensing, one of which is the SDB (Satellite-Derived Bathymetry) technique. The existence of images
of various resolutions and more complete image channels increase the SDB technique's accuracy.
This method is based on the principle of bands seen from satellites to estimate water depth. The
accuracy obtained by the SDB method ranges from 2-30 meters because it is influenced by the
spatial resolution ( Jégat et al., 2016). There are two popular methods in SDB studies, namely the
Analytical and Empirical methods. Based on Nuha (2019), the Analytical method is an SDB method
by extracting channels with high correlation by considering field parameters including brightness,
TSM (Total Suspended Matter). Simultaneously, the Empirical method is the extraction of the water
depth value by connecting the pixel value with the measured depth (Nuha, 2019).
Wicaksono (2015) research states that the Empirical method has a depth range influenced by
the depth data and the number of bands in the image used. However, the water conditions with
heterogeneous bottom cover and the single band will not be adequate, and the results will not be
optimal (Jupp, 1988; Wicaksono, 2015). Based on Hogrefe (2005); Stumpf (2003); Wicaksono
(2015) stated that the use of the band ratio could reduce the effect of reflection from aquatic objects
so that the resulting value is relatively constant even though the water object has a heterogeneous
base cover. SDB research using empirical methods has been carried out a lot but has not yet obtained
maximum results, as evidenced by the high RMSE value. Prayogo & Basith (2020) compare two
images in their research, namely Worldview 3 and Sentinel 2A to estimate shallow water depth in
the Karimunjawa Islands, Central Java. This study uses the Stumpf algorithm, where Worldview 3
imagery produces a better depth estimate than Sentinel 2A using the green/blue band ratio. The
RMSE value generated from the study was 1.53 meters.
Bergsma et al. (2019) produced an R2 value of 0.82 and RMSE 2.58 meters using Sentinel 2A
imagery. The methods used by Bergsma et al. (2019) are Radon Transform and Augmentation. The
research Manessa et al. (2018) using SOPT 6 high-resolution imagery produced the best accuracy
with an RMSE value of 1.09 meters and R2 of 0.45 in the Mejangan Islands. Furthermore, Bobsaid
et al. (2017) 's research resulted in an NMAE value of 25,777% using Landsat 8 imagery. While
using the Sentinel 2A imagery, the resulting NMAE value was 26,887%. Syaiful et al. (2019) research
resulted in an RMSE of 4.00 and a correlation of 0.6976 using the blue/green band ratio. Another
research was also conducted by Muzirafuti et al. (2020) with the Empirical method. This study uses
the Log-Band method on Quick Bird imagery. Meanwhile, the Object Base Image Analysis (OBIA)
method on the same image produces an RMSE value of 0.35 meters and a correlation of 0.91 meters.
The Empirical method was also carried out by Traganos et al. (2018), producing an RMSE value of
1.39 meters and R2 of 0.79 with Sentinel 2A imagery. In the same study, Traganos et al. (2018)
also used Google Earth imagery, which resulted in an RMSE of 1.67 meters and R2 of 0.9. Ledera et
al. (2019) has also conducted research using the HR400512 Electronic Nautical Chart (ENC) method
by adding vertical accuracy and position to Sentinel 2A, and Landsat 8 imageries carried out in
Hramina Bay.
Hence, this research aims to compare the performance of the single band and band ratio
methods on Worldview 3 imagery to provide depth data, especially in shallow waters using the
Empirical Method. This research is essential to do in order to determine the extent to which the use
of the single band and band ratio can produce a depth value that is close to the measured depth
value. The following is a map of the research location in Karimunjawa waters, Central Java:
3. Shallow Water Depth Mapping Using Single Band and Band Ratio………….................................................................. (Prayogo & Basith)
653
Figure 1. Research locations around Karimunjawa Port with Google Earth imagery.
This research was conducted in the Karimunjawa Islands with a geographical position of 5°
52'56.01" S and 110°25'52.62" E, precisely around the port in March 2019. The location selection
was based on the consideration of shallow water conditions due to the limitations of satellite image
sensors in penetrating water objects. This study uses Worldview 3 imagery level ORStandard2A that
has been geometrically corrected and radiometric AComp. In-situ depth data measurements used
the Bathy-2010 SyQwest Single Beam Echosounder (SBES), and the Geodetic GPS mounted on the
survey ship to obtain real-time position information. Meanwhile, a tide master is used to obtain tide
data. Data collection was carried out on March 20, 2019, s.d. March 23, 2019. Furthermore, data
processing in this study uses various kinds of software. First, ArcGIS was used to create and display
maps. The second is ENVI, which functions for image processing, and the third is Microsoft Excel
2013 for statistical analysis.
METHOD
This chapter describes the research methodology, including image preprocessing, statistical
analysis to determine the depth extraction model, and accuracy testing.
Sunglint Correction
Sunglint is a sun flash effect that occurs when sunlight hits a surface such as water or a smooth
surface like a mirror. This correction aims to eliminate the effect of sunshine due to the angle of the
rays' angle, which is the same as its reflection, causing white spots on water objects. Syaiful et al.
(2019) stated that this correction aims to eliminate water waves' effects. Hochberg et al. (2003);
Hedley et al. (2005) have refined the Sunglint correction algorithm as Equation 1.
R'
i=Ri-bi (RNIR-Min NIR)……………………………………………………………………………………….……(1)
where:
R'i = the i channel value after being reduced
Ri = the initial i channel value
bi = the amount of regression slope
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RNIR i :the channel value, and Min NIR is the minimum NIR channel value
Tide Correction
Tide correction aims to free the measured depth data from SBES recording from the influence
of tides. According to Setyawan et al. (2014), the algorithm for tide correction is as Equation 2.
D=dT-rt………………………………………………………………………………………………………..…………….(2)
where:
D = the measured depth
dT = the transducer corrected depth
rt = the tides' reduction value
Satellite Derived Bathymetry
The single band method uses the principle that the electromagnetic waves hitting the water
column will be attenuated. Bands with longer wavelengths are weakened more strongly than shorter
wavelengths (Bukata et al., 1995; Goodman et al., 2013; Wicaksono, 2015). Several parameters
that affect the single band method include selecting the band, the characteristics of the water column
attenuation and the variation in depth used (Wicaksono, 2015). The single band method produces
exponential modelling, so it is necessary to do linearization by modelling the log-transformed results
(Wicaksono, 2015).
The band ratio method in this study uses the Stumpf algorithm (Stumpf et al., 2003). The
principle of this method is to use a two-band ratio where if the ratio increases, the estimated depth
will also increase. If the depth continues to increase, the bands with a high absorption rate will
decrease (Irwanto, 2018). The equation of the Stumpf method is as Equation 3.
Z=m1 (
ln(nRw(λi))
ln(nRw(λj))
) -m0 ………………………………………………………………………………………………….(3)
where:
Z = the depth sought
m1 = the calibration coefficient
Rw (λij) = the reflectance of the extension of the wave
ln = the constant, and m0 is the depth correction (0)
The empirical method in the SDB technique utilizes the relationship between the measured
depth value and the spectral value from satellite images. Depth data were measured using SBES in
2019 along with tidal data for data correction. The amount of depth data used in this study was 218
data, with the following details:
Table 1. Number of depth samples.
Depth (meters) Number of Samples
0 – 5 25
5 – 10 31
10 – 15 82
15 – 20 50
20 - 25 30
The modelling stage begins with the Pearson product-moment correlation analysis to find the
value (r). The limit of significance value (r) on the number of samples (n) is used as a condition that
the correlation results can be continued for modelling using Regression analysis (Wicaksono, 2015).
This study uses a significance level of 95% so that a band with weak energy absorption will produce
5. Shallow Water Depth Mapping Using Single Band and Band Ratio………….................................................................. (Prayogo & Basith)
655
the best estimation model. The Resultant Regression function's value is used to convert the image
pixel value to the depth value (Wicaksono, 2015).
Accuracy Test
The SDB Empirical Model is formed from the relationship between the image pixel value and the
measured depth. The equation used in the Root Mean Square Error (RMSE) accuracy test is as
Equation 4 (Walpole, 1968; Manessa et al., 2017):
RMSE= √∑ (At-Ft)
2
n
t=1
n
………………………………………………………………………………………………..…….(4)
where:
Ft = the measured depth of the survey results with SBES
At = the estimated depth value from the extraction of the image pixel value
n = the number of measured depth points
RESULT AND DISCUSSION
This chapter describes the results and discussion, divided into two groups: Preprocessing and
Processing data.
Preprocessing Data
Depth data consist of position data and tide data. Depth data were measured using the Bathy-
2010 SyQwest Single-Beam Echosounder (SBES). The research location is located around the port
of Karimunjawa, Central Java. Real-time positioning using the Global Navigation Satellite System
(GNSS) with the Trimble NET R9 geodetic type placed on the ship. The following is the result of the
bathymetric route around the Karimunjawa Port, which is shown in the Worldview 3 imagery as
Figure 1.
This study uses depth data from 0 to 25 meters. The depth is grouped into five groups with
ranges of 0-5 meters, 5-10 meters, 10-15 meters, 15-20 meters, and 20-25 meters. Details of depth
data are 25 data (0-5 meters), 31 data (5-10 meters), 82 data (10-15 meters), 50 data (15-20
meters) and 30 data (20-25 meters). Then, the acquisition of field tide data in the Karimunjawa port
area uses the Tide Master tool installed at the port. Tide measurements were carried out for 2 x 24
hours. This instrument's principle is to automatically measure sea-level changes with sensors
connected to a computer device. The tide data are used to correct the SBES depth value resulting
from the results so that the depth value is free from tides' influence.
Figure 2. Ship trajectory for data acquisition using SBES.
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Finally, the correction made on image data are Sunglint correction. This correction is carried out
on Worldview 3 imagery to minimize sun flash in the water. The sunglint correction uses the RGB
ratios band with the Near-Infrared band. This correction begins with the creation of ROIs in the
areas affected by the sunglint effect. Then extract pixel values with ROIs and save in ASCII format.
Furthermore, the equation's value is applied to the image using ENVI software so that the sunglint
effect can be reduced.
Processing Data
Single Band
The first thing to do in the extraction of depth values is to make depth sampling in various
groups. Secondly, the depth sampling results are inputted in the ENVI software as vectors to be
converted as ROIs. Then the ROIs formed are converted into ASCII format. In principle, all bands
in the image can be used for depth estimation. However, only a few bands produce the best
correlation and small RMSE values. The single band method in this study uses four bands so that
there are four equations for the relationship between the depth and spectral values in the image.
The best correlation is the green band with an RMSE of 2.373 meters.
Band Ratio
Depth estimation using the band ratio method, the first is to make a depth sampling of each
group that functions as training data. The training data that have been inputted are then analyzed
to find a relationship between the partial value. This process is carried out on all band ratios formed
from the red, green, blue and Near-Infrared bands. This study's combination band ratio is
blue/green, blue/red, blue/Near-Infrared, green/red, green/Near-Infrared, and red/Near-Infrared.
Furthermore, the accuracy test is carried out by looking for the RMSE value generated from the
image extraction with measured depth. From the band ratio method used, the smallest RMSE is
obtained in the blue/green band ratio of 1.669 meters at a depth of 0-5 meters. The band ratio in
the Worldview 3 imagery results in a relatively small RMSE value compared to the single band. The
band ratio can reduce the bottom cover value of the waters to correlate the pixel value and the
measured depth. This study uses four bands, namely red, green, blue, and Near-Infrared. The four
bands produce six band ratios with different RMSE values.
Previous researchers have done SDB analysis using the Empirical method using the Stumpf
algorithm by comparing the Worldview 3 with Sentinel 2A. This study indicates that the green/blue
band ratio produces the best depth estimate with an RMSE of 1.526 meters (Prayogo & Basith,
2020). The RMSE value and the resulting band ratio differed between previous and present studies.
The formed model is influenced by the depth sample used (Prayogo & Basith, 2020).
CONCLUSION
From this research, the best equation for the single-band method is the green band with y: -
0.2633x + 2.3691. From this model, the green band produces the best estimation results with an
RMSE value of 2.373 meters at a depth of 0-5 meters. The best equation for the resulting band ratio
method is the blue/green band ratio with an RMSE of 1.669 meters at a depth of 0-5 meters. So it
can be concluded that the band ratio method produces a better depth estimate than the single-band
method.
ACKNOWLEDGEMENTS
The author would like to thank the Department of Geodesy Engineering and Universitas Gadjah
Mada for assisting in the form of funding for this research.
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