Mapping Environmental Impacts in North-Western Algeria Through Multivariate Spatio-Temporal Analysis Using Remote Sensing and GIS

Abstract

The interactions between the normalised difference vegetation index (NDVI), the normalised difference built-up index (NDBI), and land surface temperature (LST) are complex. The assessment of land use/land cover (LULC) changes in the North-western region of Algeria between 1995 and 2021 confirms the direct influence of these factors on surface thermal processes. The use of new information technologies, particularly remote sensing coupled with GIS, favourably contributes to the processing of a large volume of data and to the use of specific methods aimed at confirming and/or disproving the hypotheses put forward. The application of LULC classification methods clearly highlights the magnitude of transformations, predominantly in favour of intensified urbanisation over the past two decades. Indeed, agricultural lands have experienced a reduction of 17.45%, while urbanised areas have nearly doubled. This phenomenon can, in part, be attributed to the mass migration of populations from inland areas to the coast, not only due to climate change: secondary for political problems between 1990 and 2001. Similarly, barren lands have increased by 10.45%. These changes have real implications for ecosystems (mainly loss of biodiversity) and the climate (pollution, GHG emissions, and rising ambient temperatures). The estimation of average LST from multiple satellite scenes reveals an increasing trend, rising from 36.6 °C in 1995 to 40.35 °C in 2021. The direct relationship between LST and NDVI and between LST and NDBI confirms the close association between land use change and increasing surface temperatures. The Pearson coefficient between LST and NDVI showed a negative correlation, ranging between -0.52 and -0.47, while it was positively correlated between LST and NDBI, with values around 0.66. The emergence of hotspots in the region, confirmed by the results of analysis employing the Getis-Ord G* method, is marked by clearly increasing spatial envelopes. This phenomenon is associated with a distinct reduction in vegetation cover density, coupled with an increased vulnerability to drought conditions. These initial results argue in favour of preserving green and blue networks and, more largely, ecosystems.