Differentiating oil palm plantations from natural forest to improve land cover mapping in Ghana
Date of Award
Master of Science (MS)
Atmospheric and Earth Science
Land cover--Ghana--Remote sensing, Deforestation--Ghana, Oil palm
Tree crops like oil palm present a unique challenge in land cover mapping, as they are often misclassified as natural forest. The area cultivated with oil palm in Ghana has rapidly expanded since 2000, and production is expected to continue to increase. Sentinel-1 and Sentinel-2 satellite data was used to map mature, closed-canopy oil palm extent in 2019 around a known oil palm mill in a Ghana study area that includes both industrial plantations and smallholders. The combination of Sentinel-1 and Sentinel-2 inputs outperformed either input alone for mapping industrial oil palm. A separate accuracy assessment for this combined input approach demonstrated high accuracy in mapping smallholders as well. To validate these findings, results were compared with available production information and a global oil palm remote sensing product. The resulting map can inform sustainable oil palm efforts in Ghana, which is understudied in current oil palm remote sensing literature.
Abramowitz, Jacob C., "Differentiating oil palm plantations from natural forest to improve land cover mapping in Ghana" (2022). Theses. 375.