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Land Use/Land Cover Change and Environmental Impact Analysis of Ramgarh-Naudiha Region in Uttar Pradesh, India through Geospatial Technology


Affiliations
1 CSIR-Recruitment and Assessment Board, CSIR Complex, Library Avenue, New Delhi 110 012, India
2 Amity Institute of Global Warming and Ecological Studies, Amity University, Noida 201 301, Uttar Pradesh, India
3 Amity Institute of Geo-Informatics and Remote Sensing, Amity University, Noida 201 301, Uttar Pradesh, India
4 CSIR-Central Glass & Ceramic Research Institute, Khurja Centre 203 131, Uttar Pradesh, India
5 Department of Chemistry, West Bengal State University, Berunanpukuria, Kolkata 700 126, West Bengal, India
 

Rapidly changing LULC scenario with growing population is of great concern in the modern world. The present study was undertaken to evaluate the changes in LULC pattern in Ramgarh-Naudiha region of Sonbhadra district, UP, over 20 years during 1998-2018 using datasets from the Landsat Thematic Mapper (TM) 5 and Landsat 8 (OLI/TIRS) satellites. LULC map for the chosen period has been generated by unsupervised classification with maximum likelihood algorithm. Results indicate that the study area is vulnerable to such LULC changes due to its sensitive geographic location. It is found that the major changes did happen in agriculture, forest, wasteland and water bodies. Agriculture and Forest areas have decreased by ~2 and 6.56% respectively in the study period. The wastelands had increased fast from 5.08% in 1998 to 18.87% in 2018 at the cost of the forest cover and agricultural land respectively. In 1998, water bodies were 7.49%, whereas, it has decreased to 2.04% in 2018. On the contrary, urban fringe area has grown from 0.33% in 1998 to 0.49% in 2018 especially due to population growth. The present study concludes that this LULC analysis will increase awareness and help in taking necessary action in appropriate land use planning and management.

Keywords

GIS, Land Use and Land Cover, NDVI, Remote Sensing, Unsupervised Classification.
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  • Land Use/Land Cover Change and Environmental Impact Analysis of Ramgarh-Naudiha Region in Uttar Pradesh, India through Geospatial Technology

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Authors

Debiprasad Karmakar
CSIR-Recruitment and Assessment Board, CSIR Complex, Library Avenue, New Delhi 110 012, India
Vartika Singh
Amity Institute of Global Warming and Ecological Studies, Amity University, Noida 201 301, Uttar Pradesh, India
Raghvendra Singh
Amity Institute of Geo-Informatics and Remote Sensing, Amity University, Noida 201 301, Uttar Pradesh, India
Lalit Kumar Sharma
CSIR-Central Glass & Ceramic Research Institute, Khurja Centre 203 131, Uttar Pradesh, India
Swapankumar Ghosh
Department of Chemistry, West Bengal State University, Berunanpukuria, Kolkata 700 126, West Bengal, India

Abstract


Rapidly changing LULC scenario with growing population is of great concern in the modern world. The present study was undertaken to evaluate the changes in LULC pattern in Ramgarh-Naudiha region of Sonbhadra district, UP, over 20 years during 1998-2018 using datasets from the Landsat Thematic Mapper (TM) 5 and Landsat 8 (OLI/TIRS) satellites. LULC map for the chosen period has been generated by unsupervised classification with maximum likelihood algorithm. Results indicate that the study area is vulnerable to such LULC changes due to its sensitive geographic location. It is found that the major changes did happen in agriculture, forest, wasteland and water bodies. Agriculture and Forest areas have decreased by ~2 and 6.56% respectively in the study period. The wastelands had increased fast from 5.08% in 1998 to 18.87% in 2018 at the cost of the forest cover and agricultural land respectively. In 1998, water bodies were 7.49%, whereas, it has decreased to 2.04% in 2018. On the contrary, urban fringe area has grown from 0.33% in 1998 to 0.49% in 2018 especially due to population growth. The present study concludes that this LULC analysis will increase awareness and help in taking necessary action in appropriate land use planning and management.

Keywords


GIS, Land Use and Land Cover, NDVI, Remote Sensing, Unsupervised Classification.

References