Extraction of Rubber Plantations on Hainan Island, China, Using Multi-Source Remote Sensing Images During 2021–2025

Precise monitoring of rubber plantations is critical for effective management and ecological assessments, enabling optimal resource allocation, disease detection, and mitigation of environmental impacts. This study integrated multi-source remote sensing data—including Landsat 8, Sentinel-1/2, GaoFen-1 (GF-1) optical and SAR imagery, and DEM data of Hainan Island. The rubber plantation areas from 2021 to 2025 were extracted from the Google Earth Engine (GEE) platform by employing a multi-step threshold segmentation method, which utilized the Otsu algorithm to automatically determine optimal thresholds for distinguishing rubber plantations from other land covers. The overall accuracy of the extracted rubber plantations in this study was above 90%; the Kappa coefficient was greater than 0.85; and the F1-score surpassed 0.93. The resulting distribution maps reveal that rubber plantations on Hainan Island are predominantly concentrated in the northwestern and northern regions. The rubber plantation area of Hainan Island remained relatively stable from 2021 to 2023. During 2023–2024, the rubber plantation area experienced a decline. This reduction was particularly pronounced in 2024, when the area decreased by nearly 150 km2 compared to the previous year. However, in 2025, this downward trend reversed sharply with an increase of approximately 300 km2. These findings provide a critical scientific basis for sustainable rubber production, supporting informed decision-making in irrigation, pest control, and yield optimization. Furthermore, they offer valuable insights for strategic planning to balance economic returns with ecological conservation, thereby ensuring the long-term viability of the industry.

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Publication Details

Journal
Forests
Published
2025-11-25
DOI
https://doi.org/10.3390/f16121773
Primary Topic
Oil Palm Production and Sustainability
Type
article
Field-Weighted Citation Impact
0.00
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article

Extraction of Rubber Plantations on Hainan Island, China, Using Multi-Source Remote Sensing Images During 2021–2025

X. Liu, Ruofan Jing, Huichun Ye, Lingling Teng et al.
Forests
Oil Palm Production and Sustainability
article

Extraction of Rubber Plantations on Hainan Island, China, Using Multi-Source Remote Sensing Images During 2021–2025

X. Liu, Ruofan Jing, Huichun Ye, Lingling Teng, Jingjuan Liao
article en

Abstract

Precise monitoring of rubber plantations is critical for effective management and ecological assessments, enabling optimal resource allocation, disease detection, and mitigation of environmental impacts. This study integrated multi-source remote sensing data—including Landsat 8, Sentinel-1/2, GaoFen-1 (GF-1) optical and SAR imagery, and DEM data of Hainan Island. The rubber plantation areas from 2021 to 2025 were extracted from the Google Earth Engine (GEE) platform by employing a multi-step threshold segmentation method, which utilized the Otsu algorithm to automatically determine optimal thresholds for distinguishing rubber plantations from other land covers. The overall accuracy of the extracted rubber plantations in this study was above 90%; the Kappa coefficient was greater than 0.85; and the F1-score surpassed 0.93. The resulting distribution maps reveal that rubber plantations on Hainan Island are predominantly concentrated in the northwestern and northern regions. The rubber plantation area of Hainan Island remained relatively stable from 2021 to 2023. During 2023–2024, the rubber plantation area experienced a decline. This reduction was particularly pronounced in 2024, when the area decreased by nearly 150 km2 compared to the previous year. However, in 2025, this downward trend reversed sharply with an increase of approximately 300 km2. These findings provide a critical scientific basis for sustainable rubber production, supporting informed decision-making in irrigation, pest control, and yield optimization. Furthermore, they offer valuable insights for strategic planning to balance economic returns with ecological conservation, thereby ensuring the long-term viability of the industry.

ForestsVol. 16(12)
Chinese Academy of Sciences (CN), Hainan University (CN), Beijing Institute of Big Data Research (CN), Aerospace Information Research Institute (CN), Sanya University (CN), University of Chinese Academy of Sciences (CN)
Openalex Percentile: Top 64%
Oil Palm Production and Sustainability
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