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Remote Sensing for Natural Resources    2023, Vol. 35 Issue (2) : 42-49     DOI: 10.6046/zrzyyg.2022235
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A study of the disturbance to mangrove forests in Dongzhaigang, Hainan based on LandTrendr
YU Sen1,2(), JIA Mingming2(), CHEN Gao2, LU Yingying2,3, LI Yi1,2, ZHANG Bochun1,2, LU Chunyan4, LI Huiying5
1. School of Surveying, Mapping and Exploration Engineering, Jilin Jianzhu University, Changchun 130118, China
2. Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchuan 130102, China
3. Changchun New District Beihu Yingcai School, Changchun 130000, China
4. College of Computer and Information Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China
5. School of Environmental and Municipal Engineering, Qingdao University of Technology, Qingdao 266520, China
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Abstract  

With the rapid socio-economic development and the increasing demand for natural resources in China, the protection of natural reserves is facing increasing difficulties. The remote sensing-based research on monitoring the disturbance and the restoration of mangrove forests through time series analysis is still in its initial stage. Moreover, time series algorithms are highly complex. Based on the LandTrendr time segmentation algorithm of Google Earth Engine (GEE) and the Landsat image time-series data, this study investigated the disturbance to mangrove forests in the Dongzhaigang Mangrove Nature Reserve during 1990—2020. The results are as follows: ① A total of 42.39 hm2 of mangrove forests were disturbed during 1990—2020, among which the largest disturbance area of 12.78 hm2 occurred in 2014; ② During 1990—2020, minor, moderate, and severe disturbances accounted for 65.39%, 30.78%, and 3.83%, respectively; ③ The overall identification accuracy of the pixels of mangrove forests subject to changes was 89.50%, and the overall detection accuracy of years witnessing disturbance was 88%, with a Kappa coefficient of 0.79. This study analyzed the years and areas of the disturbance to mangrove forests in the Dongzhaigang Mangrove Nature Reserve over 30 years based on LandTrendr. Moreover, this study analyzed the disturbance factors according to the actual situation and concluded that human activities are the main disturbance factor, followed by natural factors, such as diseases, pests, and extreme weather events. This study will provide a scientific basis and a decision reference for the management of the mangrove forest reserve.
Keywords Dongzhaigang      mangrove forest      Google Earth Engine (GEE)      LandTrendr      Landsat     
ZTFLH:  TP79  
Issue Date: 07 July 2023
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Sen YU
Mingming JIA
Gao CHEN
Yingying LU
Yi LI
Bochun ZHANG
Chunyan LU
Huiying LI
Cite this article:   
Sen YU,Mingming JIA,Gao CHEN, et al. A study of the disturbance to mangrove forests in Dongzhaigang, Hainan based on LandTrendr[J]. Remote Sensing for Natural Resources, 2023, 35(2): 42-49.
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https://www.gtzyyg.com/EN/10.6046/zrzyyg.2022235     OR     https://www.gtzyyg.com/EN/Y2023/V35/I2/42
Fig.1  Geographical location of Dongzhaigang Reserve
Fig.2  Mangrove forest growth area of Dongzhaigang Reserve from 1990 to 2020
Fig.3  Concept of LandTrendr change detection algorithm
参数 参数描述 数值
Max Segments 最大分割段数 6
Spike Threshold 去除峰值的阈值 0.9
Vertex Count Overshoot 基于初始回归函数的潜在顶点可以超过的顶点数 3
Prevent One Year Recovery 是否阻止1 a后恢复的情况 TRUE
Recovery Threshold 如果某个分割段的恢复率大于该值的倒数,则该舍弃分割段 0.25
Pval Threshold 回归分析中F检验的P,超过该值的话,则认为该像元没有发生变化 0.05
Best Model Proportion 最佳比例模型,如果超过该值,则被选中 0.75
Min Observations
Needed		 进行拟合中需要的最少观测个数 6
Tab.1  Parameters of LandTrendr
Fig.4  Schematic diagram of the monitoring trajectory curves for mangrove disturbance by different indices
Fig.5  Schematic diagram of the different interference levels
类别 变化像元 稳定像元 像元总数 用户精度/%
变化像元/个 84 16 100 84.00
稳定像元/个 5 95 100 95.00
像元总数/个 89 111 200
生产者精度/% 94.38 85.59
Tab.2  Mangrove forest disturbance accuracy assessment
年份 生产者
精度		 用户
精度		 年份 生产者
精度		 用户
精度		 年份 生产者
精度		 用户
精度
1991年 95 72 2000年 95 100 2012年 85 92
1995年 100 80 2001年 80 95 2013年 80 95
1996年 92 85 2002年 100 75 2014年 96 82
1997年 75 95 2003年 88 100 2015年 95 100
1999年 100 100 2005年 100 95 2019年 100 100
Tab.3  Accuracy assessment of mangrove forest disturbance years(%)
Fig.6  Temporal and spatial distribution of mangrove forest disturbances in Dongzhaigang Reserve
年份 面积 年份 面积 年份 面积 年份 面积 年份 面积
1991年 8.79 1997年 7.86 2001年 2.52 2005年 0.03 2014年 12.78
1995年 1.35 1999年 0.06 2002年 0.54 2012年 0.09 2015年 1.98
1996年 4.98 2000年 0.06 2003年 0.09 2013年 0.51 2019年 0.75
Tab.4  Area of mangrove disturbance in Dongzhaigang Reserve during 1990—2020(hm2)
Fig.7  Temporal and spatial distribution of mangrove disturbance intensity in Dongzhaigang Reserve
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