A Study of the Impact of the Climate and Land-use/Land-cover (LULC) Changes on the UAE Mangrove Forests over the Period 1990-2020

Abstract

Mangroves are integral part of coastal ecosystem, demonstrating resiliency against adverse anthropogenic and environmental effects. They provide blue carbon stock and security against coastal erosion and act as a nutrient source for many aquatic inhabitants along with providing raw materials for human consumption. However, mangroves continue to perish due to climate factors and land-use/land-cover (LULC) changes. Past research has indicated some environmental factors influencing the growth and sustenance of mangrove forests. This thesis aims at studying the impact of the climate and LULC changes on the UAE mangrove forests during the period 1990-2020. The studied climate change related factors include surface temperature, sea-level rise, salinity, and coastal inundation. LULC changes were assessed by creating LULC maps over the period of study through supervised classifications of Landsat images. Then, remote sensing techniques and supervised machine learning methods were utilized to derive the climatic factors. The correlations between mangrove and these factors were investigated. Finally, forest-based classification and regression analysis was conducted to study the impact of land surface temperature, vegetation extent, slope, and salinity on mangrove biomass. It was found that Land Surface Temperature is closely related to mangrove and that mangrove biomass was highest in the land surface temperature range 30-35 °C. LULC changes showed a positive correlation with total vegetation cover (i.e., including mangrove) in terms of area. Results have not shown clear correlation between tidal inundation and mangrove. Furthermore, results showed that mangrove biomass was negatively affected by sea-level rise. In the study area, analysis showed that mangroves tended to thrive in flat slope (e.g., around 2%). The analysis results showed a general positive relationship between mangrove and salinity corresponding to increase in mangrove biomass, however site-specific analysis showed an increase in mangrove density with decrease in salinity. A model with coefficient of determination is 0.85 is developed in this thesis for the relationship between land surface temperature, slope, salinity, and mangroves using random forest classification and regression analysis.