The Correlation Among Land Cover Spectral Indices and Surface Temperature Using Remote Sensing Techniques

Abstract

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.

Detection of Spectral Reflective Changes for Temporal Resolution of Land Cover (LC) for Two Different Seasons in central Iraq

“…Remote sensing and geographic information systems are important technologies that analyze photographs to provide environmental data for a variety of urban applications [4,5]. Multiple indicators were employed in the study, including the (NDVI) ,(Normalized Difference Vegetation Index), the (NDWI), (Normalized Difference Water Index), the (SAVI), (Soil Adjusted Vegetation Index), and the( NDBI), (Normalized Difference Built-UP Index) [6]. The importance and capabilities of GIS and RS as effective and powerful instruments in assessing degradation and monitoring land changes have been demonstrated, as has the development of geographic systems and modern technology, including the importance and capabilities of GIS and RS as effective and powerful instruments in assessing degradation and monitoring land changes [7].…”