首页|基于GEE的赣州安远县30年植被覆盖度时空变化分析

基于GEE的赣州安远县30年植被覆盖度时空变化分析

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在谷歌地球引擎(GEE)云平台上,以1991-2021年Landsat影像数据为基础,采用像元二分模型、趋势分析法、赫斯特指数及莫兰指数分析安远县30年植被覆盖度,探究其时空变化特征、空间自相关及未来变化趋势.结果表明,安远县的植被覆盖度在空间上整体水平较高,在研究期30年内,植被覆盖度增加区域占75.48%,退化区域占17.11%,无变化区域占7.41%.赫斯特指数预测未来安远县植被覆盖度将以持续增加为主,研究区整体表现为显著的正空间自相关,呈聚集状态分布.安远县在植被改善方面已取得了显著成果,后期还需重点关注植被覆盖度退化区域与空间自相关异常值区域.
Analysis of 30 Years Spatio-temporal Variation of Vegetation Cover Based on GEE in Anyuan County,Ganzhou
Based on the Landsat image data from 1991 to 2021 from the cloud plat form of Google East Engine(GEE),dimidiate pixel model,trend analysis method,Hurst index,and Moran index are used to analyse the vegetation cover of Anyuan county in 30 years and to explore its spatial and temporal change characteristics,spa-tial autocorrelation and future tendency.The results showed that the vegetation cover in Anyuan county was high in space.The area with increased vegetation cover auounts for 75.48%,the degraded area auounts for 17.11%,and the unchanged area auounts for 7.41%in the 30 years of the study period.The Hurst index predicted that the future vegetation cover in Anyuan county would mainly increase continuously.The results of spatial autocorrelation analysis showed that the study area as a whole showed significant positive spatial autocorrelation and was distribu-ted in a clustered state.The study area exhibits an overall significant positive spatial autocorrelation with an aggre-gated distribution.The improvement of vegetation cover in Anyuan county has already achieved significant results,however,it is necessary to focus on the areas with degraded vegetation cover and spatial autocorrelation anomalies in future.

vegetation coverGEEdimidiate pixel modeltrend analysisspatial autocorrelation

洪梓崟、李满根、多玲花、陈念楠

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东华理工大学地球科学学院,江西南昌 330013

东华理工大学测绘与空间信息工程学院,江西南昌 330013

植被覆盖度 GEE 像元二分模型 趋势分析 空间自相关

2024

东华理工大学学报(自然科学版)
东华理工学院

东华理工大学学报(自然科学版)

北大核心
影响因子:0.634
ISSN:1674-3504
年,卷(期):2024.47(1)