期刊
REMOTE SENSING
卷 15, 期 21, 页码 -出版社
MDPI
DOI: 10.3390/rs15215162
关键词
GEDI; plantation; LiDAR; Landsat; canopy height; tree crops
This study evaluated the performance of existing global canopy height map (CHM) products and a locally trained model using GEDI and optical satellite data in oil palm plantations in Nigeria. It found that existing CHMs performed poorly in the region, but the locally trained model performed well and reduced errors for short trees.
Canopy height data from the Global Ecosystem Dynamics Investigation (GEDI) mission has powered the development of global forest height products, but these data and products have not been validated in non-forest tree plantation settings. In this study, we collected field observations of the canopy heights throughout oil palm plantations in Nigeria and evaluated the performance of existing global canopy height map (CHM) products as well as a local model trained on the GEDI and various Landsat and Sentinel-2 feature combinations. We found that existing CHMs fared poorly in the region, with mean absolute errors (MAE) of 4.2-6.2 m. However, the locally trained models performed well (MAE = 2.5 m), indicating that using the GEDI and optical satellite data can still be effective, even in a region with relatively sparse GEDI coverage. In addition to improved overall performance, the local model was especially effective at reducing errors for short (<5 m) trees, where the global products struggle to capture the canopy height.
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