{"title":"Spatio-Temporal Dynamics of Landuse/Land Cover Around NTPC\nUsing High Resolution Satellite Imagery","authors":"","doi":"10.46243/jst.2021.v6.i1.pp101-109","DOIUrl":null,"url":null,"abstract":"Land is becoming scarce resource due to population growth and industrialization. Rapid growth of\nhuman activities can also be attributed as one of the reasons. Thus, it becomes an important task to regulate land\nresource for sustainable development and environmental protection. LULC change studies have become a central\ncomponent in current strategies for managing and planning land resources and monitoring environmental changes.\nIn this paper an attempt has been made to bring out spatio-temporal dynamics of LULC patterns of NTPCRamagundam and its surrounding environment by using multi-temporal satellite data of Landsat-4, IRS P6 LISS-III\nand IRS 2 LISS-IV and GIS techniques for the years 1984, 2005, 2011, 2015, 2018. The methodology includes base\nmap preparation having features like Road (SH), Rail, Canal, River, Stream, Tanks, Forest boundary and other\nadministrative boundaries from SOI topo sheet and the features digitized are updated on satellite images.\nInterpretation of study area for LULC feature extraction on satellite imageries of respective years is carried with\nNrsc’s standard LULC classification system. Change detection statistics can be generated out of 5 LULC thematic\nlayers obtained and analysed specially with respect to NTPC environs. Results from this study shows the percentage\nof geographical area occupied by built-up land, agricultural land, forests, wasteland and waterbodies of level-I\nLULC features were 10.27%, 60.68%, 6.61%, 11.81%, 10.63% respectively in 1984 and were changed into 21.41%,\n48.51%, 5.97%, 12.77%, 11.34% respectively in 2018. This analysis shows a rapid growth in built-up land and fall\nin agricultural land between 1984 and 2018. There is a considerable change in the remaining features from 1984\nand 2018.","PeriodicalId":23534,"journal":{"name":"Volume 5, Issue 4","volume":"78 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Volume 5, Issue 4","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.46243/jst.2021.v6.i1.pp101-109","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Land is becoming scarce resource due to population growth and industrialization. Rapid growth of
human activities can also be attributed as one of the reasons. Thus, it becomes an important task to regulate land
resource for sustainable development and environmental protection. LULC change studies have become a central
component in current strategies for managing and planning land resources and monitoring environmental changes.
In this paper an attempt has been made to bring out spatio-temporal dynamics of LULC patterns of NTPCRamagundam and its surrounding environment by using multi-temporal satellite data of Landsat-4, IRS P6 LISS-III
and IRS 2 LISS-IV and GIS techniques for the years 1984, 2005, 2011, 2015, 2018. The methodology includes base
map preparation having features like Road (SH), Rail, Canal, River, Stream, Tanks, Forest boundary and other
administrative boundaries from SOI topo sheet and the features digitized are updated on satellite images.
Interpretation of study area for LULC feature extraction on satellite imageries of respective years is carried with
Nrsc’s standard LULC classification system. Change detection statistics can be generated out of 5 LULC thematic
layers obtained and analysed specially with respect to NTPC environs. Results from this study shows the percentage
of geographical area occupied by built-up land, agricultural land, forests, wasteland and waterbodies of level-I
LULC features were 10.27%, 60.68%, 6.61%, 11.81%, 10.63% respectively in 1984 and were changed into 21.41%,
48.51%, 5.97%, 12.77%, 11.34% respectively in 2018. This analysis shows a rapid growth in built-up land and fall
in agricultural land between 1984 and 2018. There is a considerable change in the remaining features from 1984
and 2018.