4.5 Article

Assessment of land surface temperature dynamics over the Bharathapuzha River Basin, India

期刊

ACTA GEOPHYSICA
卷 69, 期 3, 页码 855-876

出版社

SPRINGER INTERNATIONAL PUBLISHING AG
DOI: 10.1007/s11600-021-00593-7

关键词

Land use-land cover change; Landsat; MODIS; Principal component analysis; Multichannel singular spectrum analysis

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Anthropogenic interventions have altered the natural environment and one of the main drivers of change is land use-land cover (LULC). This study analyzed the impact of LULC dynamics on land surface temperature (LST) in the Bharathapuzha river basin in Kerala, India from 1990 to 2017, showing a close relationship between LST and changes in LULC.
Anthropogenic interventions have altered the natural environment and affected many of its physical, chemical, and biological characteristics. Changes in land use-land cover (LULC) are one of the main drivers that alter the hydrologic cycle and cause significant impacts on local, regional, and even the global climate system. It is now widely recognised and accepted that climate change is one of the gravest problems that our planet Earth is facing at present. This study analyses the impact of LULC dynamics on the spatial and temporal variation of land surface temperature (LST) in an inter-state river basin, which also happens to be the largest river basin in the state of Kerala, India, viz. the Bharathapuzha river basin, during the period 1990-2017. LST time-series analysis (derived from Landsat) revealed that 98% of the river basin experienced LST less than 298 K in January 1990. Over time, along with changes in LULC, LST also increased; in 2017, about 7.82% of the river basin experienced LST greater than 312 K. A notable change in LULC that occurred during this period was the drastic increase in areas with high albedo. The seasonal curves of LST derived from MODIS data are strong evidence of the devastating impacts of change in LULC on LST and, in turn, on climate change. The major spatial and temporal components of change in LST in the study region were identified by principal component analysis (PCA). The results of this spatiotemporal analysis spread over a period of 28 years can be used for formulating sustainable development policies and mitigation strategies against extreme climatic events in the river basin.

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