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Tropical Forest Disturbance Monitoring Based on Multi-Source Time Series Satellite Images and the LandTrendr Algorithm

文献类型： 外文期刊

作者： Yin, Xiong 1 ; Kou, Weili 2 ; Yun, Ting 3 ; Gu, Xiaowei 1 ; Lai, Hongyan 1 ; Chen, Yue 2 ; Wu, Zhixiang 1 ; Chen, Bangqian 1 ;

作者机构： 1.Chinese Acad Trop Agr Sci CATAS, Rubber Res Inst RRI, Hainan Danzhou Agroecosyst Natl Observat & Res Stn, State Key Lab Incubat Base Cultivat & Physiol Trop, Haikou 571101, Peoples R China

2.Southwest Forestry Univ, Coll Big Data & Intelligence Engn, Kunming 650224, Peoples R China

3.Nanjing Forestry Univ, Coll Forestry, Nanjing 210037, Peoples R China

关键词： Hainan Island; forest disturbances; LandTrendr; Google Earth engine

期刊名称：FORESTS （ 影响因子：3.282； 五年影响因子：3.292 ）

ISSN：

年卷期： 2022 年 13 卷 12 期

页码：

收录情况： SCI

摘要： Monitoring disturbances in tropical forests is important for assessing disturbance-related greenhouse gas emissions and the ability of forests to sequester carbon, and for formulating strategies for sustainable forest management. Thanks to a long-term observation history, large spatial coverage, and support from powerful cloud platforms such as Google Earth Engine (GEE), remote sensing is increasingly used to detect forest disturbances. In this study, three types of forest disturbances (abrupt, gradual, and multiple) were identified since the late 1980s on Hainan Island, the largest tropical island in China, using an improved LandTrendr algorithm and a dense time series of Landsat and Sentinel-2 satellite images on the GEE cloud platform. Results show that: (1) the algorithm identified forest disturbances with high accuracy, with the R-2 for abrupt and gradual disturbance detection reaching 0.92 and 0.83, respectively; (2) the total area in which forest disturbances occurred on Hainan Island over the past 30 years accounted for 10.84% (2.33 x 10(5) hm(2) in total area, at 0.35% per year) of the total forest area in 2020 and peaked around 2005; (3) the areas of abrupt, gradual, and multiple disturbances were 1.21 x 10(5) hm(2), 9.96 x 10(4) hm(2), and 1.25 x 10(4) hm(2), accounting for 51.93%, 42.75%, and 5.32% of the total disturbed area, respectively; and (4) most forest disturbance occurred in low-lying (<600 m elevation accounts for 97.42%) and gentle (<25 degrees slope accounts for 94.42%) regions, and were mainly caused by the rapid expansion of rubber, eucalyptus, and tropical fruit plantations and natural disasters such as typhoons and droughts. The resulting algorithm and data products provide effective support for assessments of such things as tropical forest productivity and carbon storage on Hainan Island.

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