干旱区生态环境知识资源中心(Arid): Combination of remote-sensing spectral indices to classify the areas of land degradation in West Burdwan district, India

Arid

DOI	10.1007/s12665-022-10338-4
	Combination of remote-sensing spectral indices to classify the areas of land degradation in West Burdwan district, India
	Kabiraj, Sabyaschi; Duraisekaran, Elanchezhiyan; Ramaswamy, Malarvizhi
通讯作者	Kabiraj, S
来源期刊	ENVIRONMENTAL EARTH SCIENCES
ISSN	1866-6280
EISSN	1866-6299
出版年	2022
卷号	81 期号:7
英文摘要	Demarcating the extent of land degradation remains a major challenge worldwide. A combination of remote-sensing spectral indices and Land Degradation Index (LDI) were used for the delineation and classification of land degraded areas in West Burdwan district, West Bengal, India. Mining, brick and other industries were delineated using the maximum likelihood classification (MLC) algorithm of the supervised image classification method. Land Surface Temperature (LST), Normalized Difference Vegetation Index (NDVI), Soil Moisture Index (SMI), night-time LST and Evapotranspiration (ET) were used as indicators of land degradation and were derived from Landsat and Moderate Resolution Imaging Spectroradiometer satellite images for the years from 1990 to 2020. The result indicates an increase in industrial area from 2.06% to 7.62% of the district area from 1990 to 2020. Our pixel-based time-series analysis displays some considerable land degradation over the past 30 years, including (i) increasing daytime LST, (ii) declining vegetation, (iii) decreasing ET. However, no considerable change was found in night-time-LST and SMI. A strong positive correlation (adjusted R-2 > 0.5 and p < 0.05) was observed between mining area expansion and daytime LST and a negative correlation between mining area expansion and NDVI and ET respectively. LDI shows a total land degradation of 91.01 km(2) over the entire study region. Mining area expansion was found to be one of the major stressors to local environmental degradation. The results from this study may help the decision-makers and policymakers to provide a better management plan for sustainable land management in future.
英文关键词	Normalized Difference Vegetation Index Soil Moisture Index Land Degradation Index Geographical information system
类型	Article
语种	英语
收录类别	SCI-E ; SSCI
WOS记录号	WOS:000776945000001
WOS关键词	DIFFERENCE VEGETATION INDEX ; SURFACE TEMPERATURE ; SOIL-MOISTURE ; SEMIARID ENVIRONMENT ; MONITORING LAND ; DESERTIFICATION ; NDVI ; DYNAMICS ; REGION ; COVER
WOS类目	Environmental Sciences ; Geosciences, Multidisciplinary ; Water Resources
WOS研究方向	Environmental Sciences & Ecology ; Geology ; Water Resources
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/392443
推荐引用方式 GB/T 7714	Kabiraj, Sabyaschi,Duraisekaran, Elanchezhiyan,Ramaswamy, Malarvizhi. Combination of remote-sensing spectral indices to classify the areas of land degradation in West Burdwan district, India[J],2022,81(7).
APA	Kabiraj, Sabyaschi,Duraisekaran, Elanchezhiyan,&Ramaswamy, Malarvizhi.(2022).Combination of remote-sensing spectral indices to classify the areas of land degradation in West Burdwan district, India.ENVIRONMENTAL EARTH SCIENCES,81(7).
MLA	Kabiraj, Sabyaschi,et al."Combination of remote-sensing spectral indices to classify the areas of land degradation in West Burdwan district, India".ENVIRONMENTAL EARTH SCIENCES 81.7(2022).