Spatially-explicit mapping annual oil palm heights in peninsular Malaysia combining ICESat-2 and stand age data

Abstract

Oil palm is the most efficient oil-producing crop but its extension leads to increased deforestation in Southeast Asia. Oil palm height enables the quantitative estimation for carbon stock or palm oil yield. Nevertheless, there are still no accurate characterization of oil palm height providing information for the tradeoff between forest damage and carbon stock of oil palm in Southeast Asia. The new generation of spaceborne LiDAR provides large-extent canopy height samples, offering an opportunity for mapping the oil palm height at the regional scale yet with challenge to extrapolate the footprint heights to spatially coherent maps. Here, we proposed a new method by combining Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) footprint data with stand age that is closely related to tree height. We first developed a semi-automatic filtering algorithm to filter the low-quality ICESat-2 data, and used a change detection algorithm to optimize the planting year map of oil palm. Then, an empirical age-height model was derived by linking ICESat-2 footprint canopy height with oil palm age that was used to estimate spatially and temporally oil palm height for the whole Peninsular Malaysia. A validation with independent ICESat-2 footprint data suggests a high agreement for the height estimates in 2020 from the age-height model (R2 = 0.63; RMSE = 1.64 m) with a bias within ±3 m for >90% of the height estimates. Using the age-height model and planting year map of oil palm, we produced the first comprehensive wall-to-wall maps of long-term yearly oil palm height at a spatial resolution of 30 m in Peninsular Malaysia during 2001 through 2020. Our results suggest that the mean height of oil palm in all and regionally-disturbed areas have increased by 10.82 m and 9.29 m respectively during the last two decades in Peninsular Malaysia. Our results indicate that combining stand age and ICESat-2 footprint data has great potential in spatially-explicit mapping regional oil palm height that contributes to a better quantification for regional plantation carbon stock.