The study describes the land use and land cover dynamics in Kamrup district of Assam from 1991 to 2011 using remote sensing and Geographical Information System (GIS). Satellite remote sensing and GIS acts as an effective approach for analyzing the direction, rate and spatial pattern of land use dynamics. Landsat-TM and ETM+ for the period 1991, 2001 and 2011 were used to prepare the land use/land cover (LULC) map for different periods. The methodology employed consists of an object-oriented classification approach for LULC mapping and a post-classification change-detection technique for quantifying the changes for twelve major land use and land cover types. The results indicated that severe land cover changes have occurred in built-up (+ 45.82%), wetlands (−39.45%), croplands (+ 4.16%) and forest cover (−3.09%) areas. Most of the areas have been compensated to expansion in areas under built-up and cultivated lands. Keywords: Change detection, change matrix, land-use, land-cover, accuracy assessment
{"title":"Study on Land Use/Land Cover Change Dynamics through Remote Sensing and GIS – A Case Study of Kamrup District, North East India","authors":"J. Deka, O. Tripathi, M. Khan","doi":"10.37591/.V5I1.455","DOIUrl":"https://doi.org/10.37591/.V5I1.455","url":null,"abstract":"The study describes the land use and land cover dynamics in Kamrup district of Assam from 1991 to 2011 using remote sensing and Geographical Information System (GIS). Satellite remote sensing and GIS acts as an effective approach for analyzing the direction, rate and spatial pattern of land use dynamics. Landsat-TM and ETM+ for the period 1991, 2001 and 2011 were used to prepare the land use/land cover (LULC) map for different periods. The methodology employed consists of an object-oriented classification approach for LULC mapping and a post-classification change-detection technique for quantifying the changes for twelve major land use and land cover types. The results indicated that severe land cover changes have occurred in built-up (+ 45.82%), wetlands (−39.45%), croplands (+ 4.16%) and forest cover (−3.09%) areas. Most of the areas have been compensated to expansion in areas under built-up and cultivated lands. Keywords: Change detection, change matrix, land-use, land-cover, accuracy assessment","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127883523","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Vanum Govindu, G. HaftayHailu, Yohannes, Yechale Kebede Bizuneh
In all urban centers of the Tigray region, Ethiopia in general, there is inefficient urban land utilization. Inefficient buildable urban land development and management is manifested in the form of vacant, partially utilized and underutilized lands. Most of these lands are exposed to urban sprawl, squatting and land speculation. Moreover, there is inadequate infrastructure provision, under regulation, and shortage of buildable lands; speculation and tenure insecurity are the problems of urban land utilization. Urban land utilization in Mekelle city in general and AdiHaki Dejen area in particular, is inefficient land development and management, lack of infrastructure provision and under regulation. Therefore, the objective the study was to understand the causes and effects of partially utilized and underutilized lands which results in poor land utilization and development in AdiHaki Dejen area. To do so, the research started by assessing and analyzing the current status of urban land utilization using primary and secondary data sources. ArcGIS was used to analyze the BAR, ILVR, building height, and use change and proximity of linear infrastructure. Then, ArcGIS SQL was used to identify the partially utilized lands, and then Improvement to Land Value Ratio (ILR) was used to analyze the underutilized parcels. Similarly, the spatial proximity of physical infrastructure to the parcels was analyzed using ArcGIS. The study shows that there are 441 (509,233 m2) parcels with 202 m2 and above identified parcels as partially vacant lands, because of the existing structures on the parcels are small enough to divide or sub divided to hold one or more additional housing units. Moreover, 616 (419781 m2) parcels were underutilized parcels with their Improvement to Land Value Ratio (ILR) below ‘1’, leading to low property improvement to land value. This indicates low real property investment per capita and/or low land consumption per square meter of land. Generally, the study concludes that the main problems of the study area are inefficient land utilization and management, inadequate infrastructure provision and under regulation. This result were used as base line for urban planners, land use planners and managers to use the application of ArcGIS in urban land use planning and utilization for economically efficient land development and management. Keywords: Urban land utilization, partially utilized lands, underutilized lands, improvement land value and spatial analysis Cite this Article Vanum Govindu, Haftay Hailu G/Yohannes, Yechale Kebede Bizuneh. Assessing Urban Land Utilization Using Geographical Information System. Journal of Remote Sensing & GIS. 2019; 10(1): 9–23p.
{"title":"Assessing Urban Land Utilization Using Geographical Information System","authors":"Vanum Govindu, G. HaftayHailu, Yohannes, Yechale Kebede Bizuneh","doi":"10.37591/.V10I1.305","DOIUrl":"https://doi.org/10.37591/.V10I1.305","url":null,"abstract":"In all urban centers of the Tigray region, Ethiopia in general, there is inefficient urban land utilization. Inefficient buildable urban land development and management is manifested in the form of vacant, partially utilized and underutilized lands. Most of these lands are exposed to urban sprawl, squatting and land speculation. Moreover, there is inadequate infrastructure provision, under regulation, and shortage of buildable lands; speculation and tenure insecurity are the problems of urban land utilization. Urban land utilization in Mekelle city in general and AdiHaki Dejen area in particular, is inefficient land development and management, lack of infrastructure provision and under regulation. Therefore, the objective the study was to understand the causes and effects of partially utilized and underutilized lands which results in poor land utilization and development in AdiHaki Dejen area. To do so, the research started by assessing and analyzing the current status of urban land utilization using primary and secondary data sources. ArcGIS was used to analyze the BAR, ILVR, building height, and use change and proximity of linear infrastructure. Then, ArcGIS SQL was used to identify the partially utilized lands, and then Improvement to Land Value Ratio (ILR) was used to analyze the underutilized parcels. Similarly, the spatial proximity of physical infrastructure to the parcels was analyzed using ArcGIS. The study shows that there are 441 (509,233 m2) parcels with 202 m2 and above identified parcels as partially vacant lands, because of the existing structures on the parcels are small enough to divide or sub divided to hold one or more additional housing units. Moreover, 616 (419781 m2) parcels were underutilized parcels with their Improvement to Land Value Ratio (ILR) below ‘1’, leading to low property improvement to land value. This indicates low real property investment per capita and/or low land consumption per square meter of land. Generally, the study concludes that the main problems of the study area are inefficient land utilization and management, inadequate infrastructure provision and under regulation. This result were used as base line for urban planners, land use planners and managers to use the application of ArcGIS in urban land use planning and utilization for economically efficient land development and management. Keywords: Urban land utilization, partially utilized lands, underutilized lands, improvement land value and spatial analysis Cite this Article Vanum Govindu, Haftay Hailu G/Yohannes, Yechale Kebede Bizuneh. Assessing Urban Land Utilization Using Geographical Information System. Journal of Remote Sensing & GIS. 2019; 10(1): 9–23p.","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127413677","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rapid urbanization and changing land use have resulted in changes in the quality and quantity of urban runoff. A correlation between changes in land use and characteristics of urban runoff has been established. Therefore, there is a need to evolve a suitable dynamic system for stormwater management of rapidly growing urban areas. This paper demonstrates the use of remote sensing combined with GIS to model and manage stormwater in a rapidly growing urban area. The land use and land cover information was derived from satellite images and the data thus derived were incorporated in the GIS spatial database to develop a land use map of the study area. Interactive maps were prepared by integrating the land use coverage, catchment coverage and runoff water-quality coverage attributes. Using the maps, the critical areas with respect to urban stormwater pollution can be identified and the best management practices (BMPs) for tackling stormwater pollution from urban areas can be proposed. The maps so generated shall be potential tools for urban planning and environmental management. Keywords: storm water, urbanization, remote sensing, GIS, land use planning, best management practices
{"title":"GIS Based Storm Water Management System for Rapidly Growing Urban Areas: A Case Study","authors":"S. Sood, Vibhor Sood, S. John","doi":"10.37591/.V4I3.446","DOIUrl":"https://doi.org/10.37591/.V4I3.446","url":null,"abstract":"Rapid urbanization and changing land use have resulted in changes in the quality and quantity of urban runoff. A correlation between changes in land use and characteristics of urban runoff has been established. Therefore, there is a need to evolve a suitable dynamic system for stormwater management of rapidly growing urban areas. This paper demonstrates the use of remote sensing combined with GIS to model and manage stormwater in a rapidly growing urban area. The land use and land cover information was derived from satellite images and the data thus derived were incorporated in the GIS spatial database to develop a land use map of the study area. Interactive maps were prepared by integrating the land use coverage, catchment coverage and runoff water-quality coverage attributes. Using the maps, the critical areas with respect to urban stormwater pollution can be identified and the best management practices (BMPs) for tackling stormwater pollution from urban areas can be proposed. The maps so generated shall be potential tools for urban planning and environmental management. Keywords: storm water, urbanization, remote sensing, GIS, land use planning, best management practices","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129626667","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Feature level fusion approach is utilized in this paper to classify remote sensing images. Texture features are extracted from panchromatic images using mixed Gabor filter (GB), fast gray level co-occurrence matrix (GLCM) and linear binary pattern (LBP). The resultant texture features are classified using nearest neighbor (k-NN) classification method. Spectral features are extracted from the MS image and segmented using over segmented k-means algorithm with novel initialization (OSKNI). Finally the segmented MS image and grid classified PAN image are fused to get the final classified result. To evaluate the performance of the proposed method we used kappa statistics like, Users Accuracy (UA), Producer’s accuracy (PA), Overall classification accuracy (OCA), Expected Classification Accuracy (ECA) and KHAT values. Keywords: Texture, spectral, panchromatic, multispectral, segmentation Cite this Article Shashidhar Sonnad, Lalitha YS. A Novel Feature Level Fusion method for Classification of Remote Sensing Images. Journal of Remote Sensing & GIS. 2019; 10(1): 58–65p.
{"title":"A Novel Feature Level Fusion Method for Classification of Remote Sensing Images","authors":"Shashidhar Sonnad, Y. Lalitha","doi":"10.37591/.V10I1.281","DOIUrl":"https://doi.org/10.37591/.V10I1.281","url":null,"abstract":"Feature level fusion approach is utilized in this paper to classify remote sensing images. Texture features are extracted from panchromatic images using mixed Gabor filter (GB), fast gray level co-occurrence matrix (GLCM) and linear binary pattern (LBP). The resultant texture features are classified using nearest neighbor (k-NN) classification method. Spectral features are extracted from the MS image and segmented using over segmented k-means algorithm with novel initialization (OSKNI). Finally the segmented MS image and grid classified PAN image are fused to get the final classified result. To evaluate the performance of the proposed method we used kappa statistics like, Users Accuracy (UA), Producer’s accuracy (PA), Overall classification accuracy (OCA), Expected Classification Accuracy (ECA) and KHAT values. Keywords: Texture, spectral, panchromatic, multispectral, segmentation Cite this Article Shashidhar Sonnad, Lalitha YS. A Novel Feature Level Fusion method for Classification of Remote Sensing Images. Journal of Remote Sensing & GIS. 2019; 10(1): 58–65p.","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123453445","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Snow and glaciers in the North-Eastern Himalayas are primary water resources for various rivers originating in the eastern side of the Himalayan range. Global warming and changes in the climate system are believed to play a pivotal role in the changes of snow cover over the North-Eastern Himalayas. The analysis of data from remote sensing sensors can provide useful inputs to studies related to snow cover monitoring and impact assessment. In this work, level 3 monthly snow cover data derived from Moderate Resolution Imaging Spectroradiometer (MODIS) sensor (on board Terra) at a spatial resolution of 0.05°×0.05° has been used to study the changes in snow cover during the time period 2000–2018 over the North-East Himalayas (25–40°N and 88–105°E). We have divided the entire region equally into five different elevation zones named as, Zone 1 (1000–2000 m), Zone 2 (2000–3000 m), Zone 3 (3000–4000 m), Zone 4 (4000–5000 m) and Zone 5 (5000–6000 m). Analysis of snow cover trend lines shows an overall decreasing trend over the study area for the different elevation zones during the winter months (December, January and February) except for a few areas where we observed increasing trends also. Keywords: Snow cover, North-East Himalaya, MODIS, trends , on board Terra Cite this Article Soubhik Biswas, Manu Mehta, Arka Ghosh. On Trends in Snow Cover during the Winter Season over the North-Eastern Himalayas (2000–2018). Journal of Remote Sensing & GIS. 2019; 10(1): 1–8p.
{"title":"On Trends in Snow Cover during the Winter Season Over The North – Eastern Himalayas (2000 – 2018)","authors":"Soubhik Biswas, Manu Mehta, Arka Ghosh","doi":"10.37591/.V10I1.259","DOIUrl":"https://doi.org/10.37591/.V10I1.259","url":null,"abstract":"Snow and glaciers in the North-Eastern Himalayas are primary water resources for various rivers originating in the eastern side of the Himalayan range. Global warming and changes in the climate system are believed to play a pivotal role in the changes of snow cover over the North-Eastern Himalayas. The analysis of data from remote sensing sensors can provide useful inputs to studies related to snow cover monitoring and impact assessment. In this work, level 3 monthly snow cover data derived from Moderate Resolution Imaging Spectroradiometer (MODIS) sensor (on board Terra) at a spatial resolution of 0.05°×0.05° has been used to study the changes in snow cover during the time period 2000–2018 over the North-East Himalayas (25–40°N and 88–105°E). We have divided the entire region equally into five different elevation zones named as, Zone 1 (1000–2000 m), Zone 2 (2000–3000 m), Zone 3 (3000–4000 m), Zone 4 (4000–5000 m) and Zone 5 (5000–6000 m). Analysis of snow cover trend lines shows an overall decreasing trend over the study area for the different elevation zones during the winter months (December, January and February) except for a few areas where we observed increasing trends also. Keywords: Snow cover, North-East Himalaya, MODIS, trends , on board Terra Cite this Article Soubhik Biswas, Manu Mehta, Arka Ghosh. On Trends in Snow Cover during the Winter Season over the North-Eastern Himalayas (2000–2018). Journal of Remote Sensing & GIS. 2019; 10(1): 1–8p.","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132643550","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Assessment, development, and management of watershed strategy require exact calculations reports of present and past land use/cover data and its change determine the ecological and hydrological process taking place in a watershed. In this study, we have to adopt supervised classification with maximum likelihood algorithm in ERDAS imagine to notice land use/cover changes (LU/LCC) analyzed in Mandavi river basin, Kadapa district, Andhra Pradesh, India using multispectral satellite data gained from Landsat satellite series for the years 2006 and 2018. These satellite data is intended for land use/cover through supervised classification in ERDAS 2014, software. In the result, we could identify six land use/land cover (LU/LC) classes, namely agricultural land, built-up land, fallow land, forest land, river and water bodies. The results shown that during the 2006 and 2018, built-up land fallow land have been increased about 0.84% (such as 12.30 km 2 ) and 2.92% (42.82 km 2 ), respectively, whereas the area under other land categories such as agricultural land, forest land, river and water bodies have decreased about 1.86% (27.30 km 2 ), 1.34 (19.66 km 2 ), 0.26 (3.87 km 2 ) and 0.29 (4.28 km 2 ), respectively. Finally, accuracy assessment has been carried out and their result shows that overall accuracy of classified images of the year 2006 and 2018 are 86.62% and 91.85% respectively. The overall Kappa coefficient values of classified images of the year 2006 and 2018 are 0.8343 and 0.8987. Hence, these values indicate that acceptable accuracy of the classified LU/LC features. Keywords: Supervised classification, land use/cover, change detection, accuracy assessment, RS and GIS Cite this Article R. Siddi Raju, G. Sudarsana Raju, M. Rajasekhar. Land Use/Land Cover Change Detection Analysis Using Supervised Classification, Remote Sensing and GIS In Mandavi River Basin, YSR Kadapa District, Andhra Pradesh, India. Journal of Remote Sensing & GIS. 2018; 9(3): 46–54p.
流域战略的评估、发展和管理需要精确的计算，现在和过去土地利用/覆盖数据的报告及其变化决定了流域发生的生态和水文过程。在本研究中，我们采用ERDAS想象中的最大似然监督分类算法，对印度安得拉邦Kadapa地区Mandavi河流域的土地利用/覆盖变化(LU/LCC)进行了分析，使用了2006年和2018年Landsat卫星系列的多光谱卫星数据。这些卫星数据旨在通过ERDAS 2014软件中的监督分类用于土地利用/覆盖。结果表明，土地利用/覆被(LU/LC)可划分为6类，即农用地、建设用地、休耕地、林地、河流和水体。结果表明:2006年和2018年，建成区和休耕地面积分别增加了0.84% (12.30 km 2)和2.92% (42.82 km 2)，而农用地、林地、河流和水体等其他土地类型面积分别减少了1.86% (27.30 km 2)、1.34 km 2 (19.66 km 2)、0.26 km 2 (3.87 km 2)和0.29 km 2 (4.28 km 2)。最后进行了准确率评估，结果表明，2006年和2018年分类图像的总体准确率分别为86.62%和91.85%。2006年和2018年分类图像的Kappa系数总体值分别为0.8343和0.8987。因此，这些值表明分类的LU/LC特征具有可接受的准确性。关键词:监督分类，土地利用/覆被，变化检测，精度评估，RS和GIS基于监督分类、遥感和GIS的印度安得拉邦Kadapa地区Mandavi河流域土地利用/覆被变化检测分析遥感与地理信息系统学报。2018;9 (3): 46-54p。
{"title":"Land Use/Land Cover Change Detection Analysis Using Supervised Classification, Remote Sensing and GIS In Mandavi River Basin, YSR Kadapa District, Andhra Pradesh, India","authors":"R. Raju, G. Raju, M. Rajasekhar","doi":"10.37591/.V9I3.249","DOIUrl":"https://doi.org/10.37591/.V9I3.249","url":null,"abstract":"Assessment, development, and management of watershed strategy require exact calculations reports of present and past land use/cover data and its change determine the ecological and hydrological process taking place in a watershed. In this study, we have to adopt supervised classification with maximum likelihood algorithm in ERDAS imagine to notice land use/cover changes (LU/LCC) analyzed in Mandavi river basin, Kadapa district, Andhra Pradesh, India using multispectral satellite data gained from Landsat satellite series for the years 2006 and 2018. These satellite data is intended for land use/cover through supervised classification in ERDAS 2014, software. In the result, we could identify six land use/land cover (LU/LC) classes, namely agricultural land, built-up land, fallow land, forest land, river and water bodies. The results shown that during the 2006 and 2018, built-up land fallow land have been increased about 0.84% (such as 12.30 km 2 ) and 2.92% (42.82 km 2 ), respectively, whereas the area under other land categories such as agricultural land, forest land, river and water bodies have decreased about 1.86% (27.30 km 2 ), 1.34 (19.66 km 2 ), 0.26 (3.87 km 2 ) and 0.29 (4.28 km 2 ), respectively. Finally, accuracy assessment has been carried out and their result shows that overall accuracy of classified images of the year 2006 and 2018 are 86.62% and 91.85% respectively. The overall Kappa coefficient values of classified images of the year 2006 and 2018 are 0.8343 and 0.8987. Hence, these values indicate that acceptable accuracy of the classified LU/LC features. Keywords: Supervised classification, land use/cover, change detection, accuracy assessment, RS and GIS Cite this Article R. Siddi Raju, G. Sudarsana Raju, M. Rajasekhar. Land Use/Land Cover Change Detection Analysis Using Supervised Classification, Remote Sensing and GIS In Mandavi River Basin, YSR Kadapa District, Andhra Pradesh, India. Journal of Remote Sensing & GIS. 2018; 9(3): 46–54p.","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129448372","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Ramachandra, K. Raghubabu, B. Kumar, P. S. Reddy
Identification and mapping of structural criteria of a region reveals information about the occurrence of ore deposits of igneous and metamorphic origin. Remote Sensing and GIS data helps in detection of such structural features, like faults, lineament, folds, etc. These are important guides for exploration of ore mineral and groundwater. Kadapa district hosts important ore minerals of igneous and metamorphic origin like Barytes, asbestos, gold, galena, steatite etc. Barytes is exploited in the district since a long past. Present study is taken up to prepare structural map along the existing Barytes mines in the district using geospatial techniques like Remote Sensing and GIS, with an intension to identify new Barytes mineralized locations through these structural guides. The structural data of any region provides a quick payback with faster, more accurate mineral identification for gold, silver, diamonds, iron, nickel, copper, uranium, aluminum, Barytes, and also provide rock and mineral relationship in search for ore deposits during exploration. Structural criteria, is an important measure in mineral exploration of certain mineral deposits that are confined by geographic, geological and tectonic features. Mainly the occurrence of ore deposits is dependent on neighboring lithology and structural deformation of the location area. Endogenous mineral deposits like tin, muscovite, lithium, tungsten, gold, beryl, gemstones etc. are associated with intermediate and acid rocks like syenite; granite, granodiorite. etc., and deposits of copper, nickel, cobalt, silver, arsenic and apatite are formed in basic rocks like gabbro, norite, diorite, etc. Due to false nature of ore bodies and their varied controls of mineralization the techniques used for mineral exploration such as remote sensing followed by ground and airborne geophysical surveys, stream sediment, litho-geochemical surveys and core drilling have been used for regional and detailed surveys. The aspect that indicate the mineralisation are known as localizers. If these indicators can be identified on satellite data/imagery then the mineral explorations can be much faster with increased efficiency. Keywords: Multispectral, LISS-III Satellite Imagery, SOI Toposheet remote sensing, GIS Cite this Article Ramachandra M., Raghu Babu K., Pradeep Kumar B. et al. Recognition and Mapping of Structural Guides for Barytes Mineral Exploration in Parts of Kadapa District using Remote Sensing and GIS. Journal of Remote Sensing & GIS . 2018; 9(3): 30–36p.
{"title":"Recognition and Mapping of Structural Guides for Barytes Mineral Exploration in Parts of Kadapa District using Remote Sensing and GIS","authors":"M. Ramachandra, K. Raghubabu, B. Kumar, P. S. Reddy","doi":"10.37591/.V9I3.201","DOIUrl":"https://doi.org/10.37591/.V9I3.201","url":null,"abstract":"Identification and mapping of structural criteria of a region reveals information about the occurrence of ore deposits of igneous and metamorphic origin. Remote Sensing and GIS data helps in detection of such structural features, like faults, lineament, folds, etc. These are important guides for exploration of ore mineral and groundwater. Kadapa district hosts important ore minerals of igneous and metamorphic origin like Barytes, asbestos, gold, galena, steatite etc. Barytes is exploited in the district since a long past. Present study is taken up to prepare structural map along the existing Barytes mines in the district using geospatial techniques like Remote Sensing and GIS, with an intension to identify new Barytes mineralized locations through these structural guides. The structural data of any region provides a quick payback with faster, more accurate mineral identification for gold, silver, diamonds, iron, nickel, copper, uranium, aluminum, Barytes, and also provide rock and mineral relationship in search for ore deposits during exploration. Structural criteria, is an important measure in mineral exploration of certain mineral deposits that are confined by geographic, geological and tectonic features. Mainly the occurrence of ore deposits is dependent on neighboring lithology and structural deformation of the location area. Endogenous mineral deposits like tin, muscovite, lithium, tungsten, gold, beryl, gemstones etc. are associated with intermediate and acid rocks like syenite; granite, granodiorite. etc., and deposits of copper, nickel, cobalt, silver, arsenic and apatite are formed in basic rocks like gabbro, norite, diorite, etc. Due to false nature of ore bodies and their varied controls of mineralization the techniques used for mineral exploration such as remote sensing followed by ground and airborne geophysical surveys, stream sediment, litho-geochemical surveys and core drilling have been used for regional and detailed surveys. The aspect that indicate the mineralisation are known as localizers. If these indicators can be identified on satellite data/imagery then the mineral explorations can be much faster with increased efficiency. Keywords: Multispectral, LISS-III Satellite Imagery, SOI Toposheet remote sensing, GIS Cite this Article Ramachandra M., Raghu Babu K., Pradeep Kumar B. et al. Recognition and Mapping of Structural Guides for Barytes Mineral Exploration in Parts of Kadapa District using Remote Sensing and GIS. Journal of Remote Sensing & GIS . 2018; 9(3): 30–36p.","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130740615","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Land, sometimes referred to as dry land, is the solid surface of Earth that is not permanently covered by water. The study describes the land use and land cover (LULC) dynamics in Bokaro district at Jharkhand from 1991 to 2011 using Remote Sensing and Geographical Information System (GIS). Whatever, human activities is invented or generated begins from LAND. Therefore, its uses and disintegration by human throughout the period of time is very essential to be known. A city grows not only by population but also by change in its spatial dimensions. The present study investigated the change detection of Bokaro district, Jharkhand, India using LANDSAT satellite data for the year 1991, 2001 and 2011. Topo sheet and high resolution images from Google earth were also used for the study. The process used for the study is known as image processing under which supervised classification method was used using different classes for the study area. The results indicated that there is a drastic increase in agriculture and habitation whereas forest, water and fallow land reduced within the district boundary limit. Migration is still continuing in the district and afforestation/human activities done throughout the period effecting in the reduction of water. Keywords: Change detection, land use and land cover, LANDSAT, Geographical Information System (GIS), remote sensing Cite this Article Modi AK, Das P, Panda D. Land Use/Land Cover Change Dynamic of Bokaro District, East India Using Remote Sensing and GIS Techniques. Journal of Remote Sensing & GIS . 2018; 9(3): 16–22p.
陆地，有时被称为旱地，是地球上不被水永久覆盖的固体表面。利用遥感和地理信息系统(GIS)对1991 - 2011年贾坎德邦Bokaro地区土地利用和土地覆盖(LULC)动态进行了研究。无论如何，人类活动是由土地发明或产生的。因此，了解它在一段时间内被人类使用和分解的过程是非常必要的。一个城市的增长不仅靠人口，而且靠其空间尺度的变化。本研究利用1991年、2001年和2011年的LANDSAT卫星数据调查了印度贾坎德邦Bokaro地区的变化检测。Topo sheet和Google earth的高分辨率图像也被用于研究。研究中使用的过程称为图像处理，其中使用监督分类方法对研究区域使用不同的类别。结果表明:在区域边界范围内，农业和居住面积急剧增加，森林、水域和休闲土地面积减少;该地区的移徙仍在继续，整个期间进行的植树造林/人类活动影响到水的减少。关键词:变化检测，土地利用和土地覆盖，LANDSAT，地理信息系统(GIS)，遥感引用本文Modi AK, Das P, Panda D.基于遥感和GIS技术的东印度Bokaro地区土地利用/土地覆盖变化动态遥感与地理信息系统学报。2018;9 (3): 16-22p。
{"title":"Land Use/Land Cover Change Dynamic of Bokaro District, East India Using Remote Sensing and GIS Techniques","authors":"Ashish Modi, P. Das, D. Panda","doi":"10.37591/.V9I3.212","DOIUrl":"https://doi.org/10.37591/.V9I3.212","url":null,"abstract":"Land, sometimes referred to as dry land, is the solid surface of Earth that is not permanently covered by water. The study describes the land use and land cover (LULC) dynamics in Bokaro district at Jharkhand from 1991 to 2011 using Remote Sensing and Geographical Information System (GIS). Whatever, human activities is invented or generated begins from LAND. Therefore, its uses and disintegration by human throughout the period of time is very essential to be known. A city grows not only by population but also by change in its spatial dimensions. The present study investigated the change detection of Bokaro district, Jharkhand, India using LANDSAT satellite data for the year 1991, 2001 and 2011. Topo sheet and high resolution images from Google earth were also used for the study. The process used for the study is known as image processing under which supervised classification method was used using different classes for the study area. The results indicated that there is a drastic increase in agriculture and habitation whereas forest, water and fallow land reduced within the district boundary limit. Migration is still continuing in the district and afforestation/human activities done throughout the period effecting in the reduction of water. Keywords: Change detection, land use and land cover, LANDSAT, Geographical Information System (GIS), remote sensing Cite this Article Modi AK, Das P, Panda D. Land Use/Land Cover Change Dynamic of Bokaro District, East India Using Remote Sensing and GIS Techniques. Journal of Remote Sensing & GIS . 2018; 9(3): 16–22p.","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"196 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121436213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-10-12DOI: 10.4172/2469-4134-C1-010
pVictor Puchkov Nikolaevichp
{"title":"Applications of GIS and remote sensing in lansdlide hazard assessment","authors":"pVictor Puchkov Nikolaevichp","doi":"10.4172/2469-4134-C1-010","DOIUrl":"https://doi.org/10.4172/2469-4134-C1-010","url":null,"abstract":"","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130162133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Rajasekhar, G. SudarsanaRaju, R. Siddiraju, A. Padmavathi, B. BalaramNaik
Digital change detection techniques by using multi-temporal satellite imagery helps in understanding landscape dynamics. The present study illustrates the spatio-temporal dynamics of Land use/cover of around Chennur, Kadapa District, Andhra Pradesh India. Landsat satellite imageries of two different time periods, i.e., Landsat Thematic Mapper (TM) were acquired by earth explorer site and quantify the changes in the study area 2005-2006 to 20015-16 over a period of 10 years. Supervised classification methodology has been employed using maximum likelihood techniques in ERDAS 2014 Software. The images of the study area were categorized into five different classes, namely Forest, Agriculture, Wastelands, Built-up and waterbodies. The results indicate that during the last 10 years, Waste Land and Built-up land have been increased by 3.86% (3.79 Sq km) and 2.98% (2.93 Sq km) while Agriculture, Forest and Waterbodies have decreased by 5.17% (5.08 Sq km), 0.45% (0.44 Sq km) and 1.22% (1.20 Sq km), respectively.
{"title":"Landuse and Landcover analysis using Remote Sensing and GIS: A case study in parts of Kadapa District, Andhra Pradesh, India.","authors":"M. Rajasekhar, G. SudarsanaRaju, R. Siddiraju, A. Padmavathi, B. BalaramNaik","doi":"10.37591/.V9I3.187","DOIUrl":"https://doi.org/10.37591/.V9I3.187","url":null,"abstract":"Digital change detection techniques by using multi-temporal satellite imagery helps in understanding landscape dynamics. The present study illustrates the spatio-temporal dynamics of Land use/cover of around Chennur, Kadapa District, Andhra Pradesh India. Landsat satellite imageries of two different time periods, i.e., Landsat Thematic Mapper (TM) were acquired by earth explorer site and quantify the changes in the study area 2005-2006 to 20015-16 over a period of 10 years. Supervised classification methodology has been employed using maximum likelihood techniques in ERDAS 2014 Software. The images of the study area were categorized into five different classes, namely Forest, Agriculture, Wastelands, Built-up and waterbodies. The results indicate that during the last 10 years, Waste Land and Built-up land have been increased by 3.86% (3.79 Sq km) and 2.98% (2.93 Sq km) while Agriculture, Forest and Waterbodies have decreased by 5.17% (5.08 Sq km), 0.45% (0.44 Sq km) and 1.22% (1.20 Sq km), respectively.","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125941089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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