Over the past few decades, there have been growing instances of human intervention in the Earth’s natural landscape. This has led to rapid changes in land use land cover (LULC) and has attracted people from various fields of study to come and investigate it. Through Remote Sensing and Geographic Information System (GIS) applications, LULC change over 24 years (1995–2019) for the district of Sonbhadra has been studied. The main intention behind the present study is to assess the LULC changes that have taken place over the years (1995–2019) and their impact on Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST). For the present study, data were obtained from satellite images of LANDSAT 5 (TM) and LANDSAT 8 (OLI). A supervised classification technique in ERDAS IMAGINE 2014 has been applied to generate the LULC maps. ArcGIS 10.4 was used to obtain NDVI and LST maps. It was found that LST and NDVI had a negative correlation. The study findings also show an increase in agricultural lands and built-up land with population pressure and development as the main causes responsible. To find out the validity of the classification accuracy, an assessment was carried out. For 1995, overall accuracy was 76% and for 2019 it was 80.64%. The current study revealed that the three variables, i.e. LULC, NDVI and LST are interlinked.

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Detection of Land Use and Land Cover Changes and Its Impact on Vegetation and Temperature in Sonbhadra District

  • Tanveer Warid Rahman

摘要

Over the past few decades, there have been growing instances of human intervention in the Earth’s natural landscape. This has led to rapid changes in land use land cover (LULC) and has attracted people from various fields of study to come and investigate it. Through Remote Sensing and Geographic Information System (GIS) applications, LULC change over 24 years (1995–2019) for the district of Sonbhadra has been studied. The main intention behind the present study is to assess the LULC changes that have taken place over the years (1995–2019) and their impact on Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST). For the present study, data were obtained from satellite images of LANDSAT 5 (TM) and LANDSAT 8 (OLI). A supervised classification technique in ERDAS IMAGINE 2014 has been applied to generate the LULC maps. ArcGIS 10.4 was used to obtain NDVI and LST maps. It was found that LST and NDVI had a negative correlation. The study findings also show an increase in agricultural lands and built-up land with population pressure and development as the main causes responsible. To find out the validity of the classification accuracy, an assessment was carried out. For 1995, overall accuracy was 76% and for 2019 it was 80.64%. The current study revealed that the three variables, i.e. LULC, NDVI and LST are interlinked.