Integration of remote sensing and GIS in the identification of the vegetation covers degradation of the korifla basin (NW of Central Morocco) between 1990 and 2018

Abstract

To characterize the evolution of the vegetation cover in the Korifla basin between 1990 and 2018, and subsequently to reconstitute, understand and explain the climatic and anthropogenic phenomena causing these changes, we adopted a methodological approach combining remote sensing techniques, geographic information systems (GIS) and statistical processing. This work consists of multitemporal satellite images at high and low spatial resolution. After the preprocessing and processing operations of these images and the calculation of the spectral indices NDWI (Normalies difference water index), NDVI (Normalies difference vegetation Index) and BI (Brilliance Index), we have developed multi-temporal maps of the vegetation, water and soil. The establishment and processing of land cover maps (LCM) through the use of the “change detection” application has allowed us to quantify the changes in vegetation cover during the last 28 years in the Korifla basin. As a result, the NDVI maps show that the vegetation cover of the Korifla basin suffered a degradation between the 1990s and 2010 against a regeneration between 2010 and 2018. This last increase is not detectable by the SVM method. As for the “change detection” technique, it confirms the regression of the areas of plant cover between 1990 and 2010 followed by an increase between 2010 and 2015 and relayed by a new regression of these areas between 2015 and 2018.

Impact of climate and demographic changes on the vegetation of the M’goun Geopark UNESCO of Morocco (1984-2021)

“…Using the change detection technique in the northwestern region of Central Morocco confirms a decline in plant cover between 1990 and 2010, followed by an increase between 2010 and 2015, and then followed by another decline in these areas between 2015 and 2018 (Lahcen et al, 2022).…”

Impact of climate change on surface water resources in arid zones - the case of the Ykem watershed in the central plateau of Morocco

“…The methodology is based on geospatialization tools [4], mainly remote sensing techniques that use publicly available data from Landsat and Sentinel satellite images. Second, data collected is analyzed by a GIS geographic information system [5], which quantifies spatio-temporal variations in water resources [6] using the Land Use index. Finally, mapping the results is done for interpretation.…”