Correlation analysis between biophysical indices and Land Surface Temperature using remote sensing and GIS in Guelma city (Algeria)

Abstract

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.

Relationship of the Seasonal Vegetation Indices against the NDVI and LST in the Region of Kamuku Game Reserve and Kwiambana National Park, Nigeria

“…2021), who revealed a negative correlation between LST and NDVI. Furthermore, the negative correlation between LST and SAVI in the dry season was consistent with the findings of Guechi et al (2021). In addition, the negative correlation between LST and NDVI and EVI agrees with the findings by Alademomi et al (2020).…”

“…Previous studies on the correlation between LST and NDVI were primarily concerned with examining the influence of urbanization on anomalous heat (Urban Heat Island) in cities. Some of these studies can be found in Deng et al (2018), Guechi et al (2021), and Koko et al (2021). Furthermore, Macarof et al (2018) investigated the correlation between LST and NDVI, MSAVI, and EVI only in the warmth season.…”

Characterisation of Morphological Patterns for Land Surface Temperature Distribution in Urban Environments: An Approach to Identify Priority Areas

“…The study of the magnitude in which urban factors impact urban climate remains elusive and this type of study contributes to this gap in the field of knowledge [40,41]. To determine the extent to which biophysical characteristics could describe the distribution of LST, we proposed three different methods, aiming for a comprehensive study and comparative analysis.…”

Cereal Crop Identification Using Sentinel2 Time Series, Case of Sidi Bel Abbes Area

“…This practice is spread in the major part of agricultural land including cereal crops. The objective of this study is to identified the cereal areas in the department of Sidi bel Abbes during the growing season 2020-2021 using sentinel2A time series images (Guechi et al, 2021), then to catch the relationship of crop duration from different plots at local scale according to growing season of NDVI values (field observations, May 2021) (Maselli & Rembold, 2001;Chehat, 2007).…”