Spectral Mixture Analysis (SMA) Model for Extracting Urban Fractions from Landsat and Sentinel-2A Images in the Al-Ahsa Oasis, Eastern Region of Saudi Arabia

A rapid expansion of urban areas in the Al-Ahsa Oasis, Saudi Arabia, was quantified using spectral mixture analysis (SMA) with high precision (~95% to 100%), revealing a nearly 9% increase between 2010 and 2020. This study leveraged Landsat and Sentinel-2A satellite imagery from 1990 to 2020, employing principal component analysis (PCA) to refine endmembers for SMA modeling. The research highlights the effectiveness of SMA in mapping urban fractions in arid and semi-arid oases, where mixed-pixel problems are prevalent. Additionally, it discusses potential drivers behind this urban growth, providing critical insights for ecosystem management in vulnerable landscapes.

Salih, A. (2023). Spectral Mixture Analysis (SMA) Model for Extracting Urban Fractions from Landsat and Sentinel-2A Images in the Al-Ahsa Oasis, Eastern Region of Saudi Arabia. Land, 12(10), 1842. https://doi.org/10.3390/land12101842