基于Landsat时间序列影像和LandTrendr算法的浙江省丽水市森林扰动监测

doi:10.6046/zrzyyg.2023285

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采用先进技术手段快速准确地获取森林扰动情况,对维护森林生态安全具有重要意义。该文以浙江省丽水市为研究区域,获取了1992—2022年6—8月所有的Landsat影像,基于GEE平台上的LandTrendr算法分析了丽水市森林扰动特征,对丽水市各县市的森林扰动情况进行时空分析,并探讨了坡度、海拔和降水等自然因素对森林扰动的影响规律。研究发现,丽水市在1992—2022年30 a间总体上呈现出植被干扰减少的趋势; 丽水市西北部的龙泉市和遂昌县是森林扰动最严重的地区,2008年是森林扰动最大的一年; 此外,坡度平缓和海拔高的地区以及降水量减少的年份都容易发生森林扰动。研究可为丽水市森林资源的保护和管理提供科学依据和参考意见。

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	郑思齐
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	朱杰

关键词 ：时间序列, LandTrendr, 谷歌地球引擎(GEE), 森林扰动

Abstract：

The rapid and accurate acquisition of forest disturbances using advanced technological methods is of great significance for maintaining forest ecological security. In this study, all Landsat images of Lishui City, China from June to August from 1992 to 2022 were acquired. Based on the LandTrendr algorithm on the Google Earth Engine (GEE) platform, this study analyzed the characteristics of forest disturbances in the city. A spatiotemporal analysis of forest disturbances across various counties and cities within Lishui was conducted, and the influence patterns of natural factors including slope, elevation, and precipitation on forest disturbances were also explored. The results indicate that vegetation disturbances in Lishui City generally decreased over the 30 years. Spatially, the most severe forest disturbances occurred in Longquan City and Suichang County located in northwestern Lishui City. Temporally, 2008 witnessed the most severe forest disturbances. In addition, areas with gentle slopes and high elevations, as well as years with reduced precipitation, were more sensitive to forest disturbance over the 30 years. This study will provide a scientific basis and reference for the preservation and management of forest resources in Lishui City.

Key words： time series LandTrendr Google Earth Engine (GEE) forest disturbance

收稿日期: 2023-09-12 出版日期: 2025-02-17

ZTFLH:

TP79

基金资助:国家自然科学基金项目“顾及空间异质性的城市用地邻里模式矢量CA建模与模拟”(42101430);江苏省自然科学基金资助项目“顾及散射机理的极化SAR沿海湿地特征提取与分类识别”(BK20180779);实景地理环境安徽省重点实验室开放基金项目“顾及用地管控特征的矢量元胞自动机建模与模拟研究”(2022PGE006)

作者简介: 陈媛媛(1988-),女,博士,讲师,主要从事森林信息提取、土地利用/土地覆被分类等研究。Email: cheny@njfu.edu.cn。

引用本文:

陈媛媛, 严铄婷, 颜瑾, 郑思齐, 王昊, 朱杰. 基于Landsat时间序列影像和LandTrendr算法的浙江省丽水市森林扰动监测[J]. 自然资源遥感, 2025, 37(1): 179-187.
CHEN Yuanyuan, YAN Shuoting, YAN Jin, ZHENG Siqi, WANG Hao, ZHU Jie. Forest disturbance monitoring in Lishui City, China based on Landsat time series images and the LandTrendr algorithm. Remote Sensing for Natural Resources, 2025, 37(1): 179-187.

链接本文:

https://www.gtzyyg.com/CN/10.6046/zrzyyg.2023285 或 https://www.gtzyyg.com/CN/Y2025/V37/I1/179

Fig.1 研究区土地利用分布情况

Tab.1 LandTrendr参数

Fig.2 LandTrendr干扰持续时间及2007—2009年样点区域目视解译

Fig.3 LandTrendr发生干扰的年份及样点区域目视解译

Fig.4 森林扰动精度评估

Fig.5 丽水市森林干扰总体分布

Fig.6 丽水市历年干扰情况变化特征

Fig.7 丽水市各市区县干扰变化特征

Fig.8 丽水市不同坡度森林干扰情况

Fig.9 丽水市不同海拔森林干扰情况

Fig.10 丽水市年干扰面积比和年均降水量随时间变化特征

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