Principal Component Analysis and Sand Dune Detection Using Sentinel-2 Data Across Saudi Arabia

This dataset is derived from Sentinel-2 surface reflectance imagery collected between January 1, 2023, and July 3, 2023, covering various regions across Saudi Arabia. Cloud contamination is mitigated using a bitmasking approach to remove cirrus and cloud pixels. Selected spectral bands (B2, B4, B7, B8, B11, and B12) are processed to generate a median composite image, enabling detailed spectral analysis. Principal Component Analysis (PCA) is applied to extract key spectral variations, while the Normalized Difference Sand Index (NDESI) is calculated to detect and monitor sand dunes. The final dataset includes clipped and exported sand dune indices, providing valuable insights for environmental monitoring, desertification studies, and land surface analysis across Saudi Arabia.

Data and Resources

Additional Info

Field Value
Author Land degradation Department, NCVC KSA
Maintainer Land degradation Department, NCVC KSA
Last Updated March 18, 2025, 13:31 (UTC)
Created March 11, 2025, 10:10 (UTC)
Analysis Type Principal Component Analysis (PCA), Sand Dune Detection
Data Source Sentinel-2
Region Saudi Arabia
Time Period 2024-01-01 to 2024-12-01