Analysis of the spatial-temporal patterns of vegetation, precipitation, land surface temperature, and soil moisture across the Sahara-Sahel Great Green Wall region using remote sensing data.

Authors

  • Andy Deng International Baccalaureate Diploma Programme, Richard Montgomery High School, Rockville, MD
  • Xianjun Hao Department of Geography and Geoinformation Science, George Mason University, Fairfax, VA
  • Dr. John Qu Department of Geography and Geoinformation Science, George Mason University, Fairfax, VA

Abstract

The Great Green Wall initiative, starting in 2007 and in development up until now, aims to combat desertification and
enhance sustainability 8000 km across Africa’s Sahel-Sahara region encompassing 18 key countries associated with the initiative—Djibouti, Eritrea, Ethiopia, Sudan, Chad, Niger, Nigeria, Mali, Burkina Faso, Mauritania, and Senegal—that have all joined to combat land degradation and restore native plant life to the landscape (Schleeter et. al, 2023). This study aims to utilize satellite remote sensing data to analyze the temporal trends and spatial patterns of the driving forces sustaining life in the environmentally critical region. In terms of vegetation trends, the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) data products from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) measurements are key to benchmarking the change of green vegetation over time. Land surface temperature data also harvested from MODIS aims to document both the daytime and nighttime temperature of the study area, a vital indication of land fertility. Precipitation data harvested from the Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG) was analyzed alongside the European Space Agency’s (ESA) Soil Moisture and Ocean Salinity (SMOS) dataset in order to investigate the impact the Great Green Wall has on evapotranspiration levels. By employing the statistical analysis technique and identifying trends and correlations through regression models for these four key parameters, an assessment is made to help understand the effectiveness of the Great Green Wall initiative in meeting its development goals.

Published

2024-10-13

Issue

Section

College of Science: Department of Geography and Geoinformation Science