Forest disturbance monitoring in Lishui City, China based on Landsat time series images and the LandTrendr algorithm

doi:10.6046/zrzyyg.2023285

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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.

Keywords time series LandTrendr Google Earth Engine (GEE) forest disturbance

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TP79

Issue Date: 17 February 2025

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	Yuanyuan CHEN
	Shuoting YAN
	Jin YAN
	Siqi ZHENG
	Hao WANG
	Jie ZHU

Cite this article:

Yuanyuan CHEN,Shuoting YAN,Jin YAN, et al. Forest disturbance monitoring in Lishui City, China based on Landsat time series images and the LandTrendr algorithm[J]. Remote Sensing for Natural Resources, 2025, 37(1): 179-187.

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https://www.gtzyyg.com/EN/10.6046/zrzyyg.2023285 OR https://www.gtzyyg.com/EN/Y2025/V37/I1/179

Fig.1 Land use distribution in the study area

Tab.1 LandTrendr parameter

Fig.2 LandTrendr interference duration and visual interpretation of sample areas from 2007 to 2009

Fig.3 The year of LandTrendr interference and the visual interpretation of sample areas

Fig.4 Assessment of forest disturbance accuracy

Fig.5 Overall distribution of forest disturbance in Lishui City

Fig.6 Characteristics of disturbance changes in Lishui City over the years

Fig.7 Disturbance variation characteristics of cities and counties in Lishui City

Fig.8 Forest disturbance of different slopes in Lishui City

Fig.9 Forest disturbance at different altitudes in Lishui City

Fig.10 Characteristics of annual disturbance area ratio and average annual precipitation over time in Lishui City

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