Climate Change and Land Use Dynamics in Djirnda Commune (Fatick Region - Senegal): Remote Sensing Approach

Abstract

Climate change is one of the greatest challenges of our time. It is a real and rapid phenomenon which, perhaps, does not dramatically affect people today but will certainly have harmful effects on future generations. It has led to the weakening of ecosystems and accelerated the degradation of natural resources. This situation has prompted the scientific world to sound the alarm to warn of its environmental and socio-economic impacts. This study seeks to analyze the dynamics of land use in Djirnda municipality in climate change. A pixel-based classification approach and the maximum likelihood algorithm were retained. The data used concerns Landsat images from 1986, 2000 and 2015. The post-classification comparison method is used to detect changes in the classified images. The overall accuracy of the classifications gives satisfactory results with 90 % for 1986, 89 % for 2000 and 91 % for 2015 and a respective Kappa coefficient of 89 %, 85 % and 90 %. The results of land use dynamics revealed an increase in mangroves (1553.13 ha) and salt lands (957.15 ha), and a regression in water surface (- 458.64 ha) and mudflats (- 2051.64 ha).

Analyse De La Pluviométrie Dans Les Rivières Du Sud : Cas De La Basse Casamance (Sénégal) Au Rio Gêba En République De Guinée

“…Les hauteurs pluviométriques substantielles font que les effets de la baisse des précipitations sont moins ressentis [29]. Cependant, les dates de rupture relevées à Ziguinchor (2004) et Cap Skiring (1976) sont tardives différemment à la majorité des études réalisées en Afrique Occidentale et Sahelienne [3], [26], [30], [31], [32], [33], [34], [35], [36] La variabilité interannuelle des précipitations est, sans conteste, grande sur l'ensemble du continent africain. Elle se traduit par la récurrence de la sécheresse et la migration vers le sud des isohyètes entrainant une « sahélisation » des zones soudaniennes.…”

Determining Changes in Mangrove Cover Using Remote Sensing with Landsat Images: a Review

“…Supervised classification is the most used classification method with remotely detected mangrove areas, and the ML algorithm, based on Bayes's theorem, is one of the most used techniques in this type of study (Faye et al, 2022). The ML classifier assumes that the samples of each class follow a normal distribution and calculates the probabilities of all classes for each sample (Findi & Wantim, 2022).…”

“…Some researchers explain the distribution of mangroves through the analysis of gradients, salinity and pH, finding that mangroves are tolerant to salinity (Faye et al, 2022), so that the increase in saline intrusion acts as a feeder (Asmara et al, 2021) and will have a positive impact on the health of mangroves (Sakti et al, 2020).…”