High-Resolution Mapping and Spatial Pattern Analysis of Areca Palm Plantations in Sanya, China, Using SAMLoRA

Abstract

Areca palm (Areca catechu L.) is an important perennial tropical cash crop in Hainan Province, and accurate information on its spatial distribution is essential for plantation monitoring and land-resource management. Focusing on Sanya, China, this study integrated 0.59 m RGB imagery acquired from Google Earth between October 2021 and February 2025, field surveys conducted in 2025, Landsat time-series data from 1986 to 2016, ASTER GDEM V3 data, and data from the 2019 Third National Land Survey. Three ResNet U-Net models were compared with Segment Anything Model adapted using Low-Rank Adaptation (SAMLoRA) using a ViT-B backbone, and the mapped distribution was further analyzed in terms of spatial clustering, terrain characteristics, historical spectral changes, and land-use context. SAMLoRA demonstrated favorable segmentation performance and was selected for citywide mapping. After manual cross-checking, the estimated area of areca palm plantations was 5468 ha, with most plantations concentrated in Tianya and Yazhou districts. Spatial analysis revealed significant clustering, and plantations occurred predominantly on gentle slopes. Historical spectral and land-use analyses further indicated that most mapped plantations showed no candidate spectral disturbance under the specified parameters and corresponded primarily to the “other garden land” category. This study provides a city-scale, high-resolution distribution baseline for fragmented tropical cash-crop plantations and offers a practical framework for plantation monitoring, agricultural spatial planning, and future assessments of land-use transitions and environmental suitability.