Open AccessCorrelation analysis between biophysical indices and Land Surface Temperature using remote sensing and GIS in Guelma city (Algeria)
Author(s) -
Imen Guechi,
Halima Gherraz,
Djamel Alkama
Publication year - 2021
Publication title -
bulletin de la société royale des sciences de liège
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.13
H-Index - 11
ISSN - 1783-5720
DOI - 10.25518/0037-9565.10457
Subject(s) - normalized difference vegetation index , albedo (alchemy) , urbanization , environmental science , geography , physical geography , vegetation (pathology) , land cover , geospatial analysis , correlation coefficient , remote sensing , land use , climate change , ecology , statistics , mathematics , medicine , art , pathology , performance art , biology , art history
Urbanization is a phenomenon that is driven by humans. It has significantly influenced biodiversity, ecosystem processes and regional climate. This work explores the relationship between seven biophysical variables (NDVI, SAVI, Greenness, Albedo, DBI, NDBI, and NDBaI indices), and LST over a period of 30 years (1990–2020), based on remote sensing & GIS. A time-series of Landsat images TM, ETM+ and OLI/TIRS data as well as various geospatial approaches were used to facilitate the analysis. The findings have revealed that urban/built-up areas of Guelma city has increased by (20.76 km2), in contrast to the agricultural and forest areas, which have been reduced by (138.26 km2 and 2.7 km2). The average temperature of urban setting was (31,43 C°) in 1990, whereas, it reached (41,90 C°) in 2020. The lowest temperature values were observed in forest bodies with (26,55 C°) in 1990 and (37,78 C°) in 2020. There is a possible rise in LST over time scale owing to the substitution of green cover by urban soil areas. Generally, there was a noticeable increase in mean LST of 10,47 C° for urban areas. The coefficient of correlation between the biophysical indices and LST shows that a strong negative correlation exists between vegetation biophysical indices (NDVI, SAVI and Greenness) and LST. In addition to this, the urban biophysical indices (Albedo, DBI, NDBI, and NDBaI) can effectively retrieve the LST. They were positively correlated in all years. DBI and LST have the highest consistently rising positive relationship (R = 0,62).This investigation provides us with clear understanding of the impacts that the urbanization and biophysical indices have on LST.