Open AccessThe Correlation Among Land Cover Spectral Indices and Surface Temperature Using Remote Sensing Techniques
Author(s) -
Aysar Jameel Abdalkadhum,
Mohammed Mejbel Salih,
Oday Zakariya Jasim
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1090/1/012024
Subject(s) - land cover , correlation coefficient , normalized difference vegetation index , environmental science , remote sensing , cover (algebra) , land use , change detection , physical geography , hydrology (agriculture) , geography , geology , mathematics , statistics , ecology , climate change , oceanography , geotechnical engineering , engineering , biology , mechanical engineering
Land cover explains the physical nature of the Earth’s surface in a specific area. Land cover is a reflection of the Earth’s surface’s observable spatial cover comprising complex classes such as agricultural areas, built-up areas, barren lands, forests, water bodies, as well as wetlands. change detection and monitoring of the land cover assist decision-makers to understand the dynamics of the environmental change to assure sustainability development. Hence land cover feature classification has appeared as a serious research aspect and thus, an accurate methodology for land cover categorizing it became an urgent necessity at this time. This study focuses to find the association between surface temperature and the spectral indices of the land cover. The spectral indices of the land cover such as (NDVI, NDBI, NDBAI, and NDWI) were compared with land surface temperature (LST) and computed the correlation coefficient, just using three images on March 18, July 24 as well as 31 December in 2018, indicating a high positive correlation coefficient among (NDBI, NDBAI) and (LST) and recorded (by built-up areas R= 0.99, R= 0.97 and R= 0.98) ) and (with bare areas R= 0.94, R= 0.98 and R= 0.99), respectively. An inverse correlation coefficient among (NDVI, NDWI) and (LST) where the results recorded a correlation coefficient with (the agricultural areas R= - 0.97, R= - 0.96 and R= - 0.95) and the correlation coefficient with (water bodies R = - 0.93, R= - 0.90 and R= - 0.58) respectively.