Study on land cover change in Hefei City based on Google Earth Engine

Journal Information

J. Hefei Univ. Tech. (Nat. Sci.), Jun.2023, Vol.46 No.6: 795-800

DOI: 10.3969/j.issn.1003-5060.2023.06.012

Authors

XU Lichen $ ^{1} $, GENG Jun $ ^{1} $, ZHU Canyang $ ^{1} $, XU Jieming $ ^{1} $, TU Lili $ ^{2} $, HUANG Jianwei $ ^{1} $

(1. School of Civil and Hydraulic Engineering, Hefei University of Technology, Hefei 230009, China; 2. School of Resources and Environment, Anhui Agricultural University, Hefei 230036, China)

Abstract and Keywords

Abstract: Aiming at the shortcomings of the traditional stand-alone processing of remote sensing images that are difficult to implement a large-scale and long-term land cover monitoring, based on Google Earth Engine(GEE), this paper takes Hefei City as the study area, and uses the multi-view Landsat images from 2000 to 2020 and a variety of auxiliary data to obtain land cover classification maps via the random forest(RF) algorithm. The driving force factors for land cover change(LCC) are analyzed. Based on the fractional vegetation cover(FVC) inversion algorithm, the temporal and spatial changes of FVC are obtained. The research results show that in the past 20 years, the spatial and temporal variation characteristics of land cover in the study area are very obvious; the temporal and spatial variation of FVC in the study area shows a decreasing characteristic; the population growth and socio-economic development are the main driving factors of LCC.

Keywords: remote sensing; land cover change(LCC); Hefei City; Google Earth Engine(GEE); spatiotemporal analysis

作者信息

徐立晨 $ ^{1} $，耿君 $ ^{1} $，朱璨阳 $ ^{1} $，徐杰铭 $ ^{1} $，涂丽丽 $ ^{2} $，黄建伟 $ ^{1} $

(1. 合肥工业大学土木与水利工程学院，安徽合肥 230009；2. 安徽农业大学资源与环境学院，安徽合肥 230036)

摘要和关键词

摘要: 针对传统的单机处理遥感影像方式难以进行大尺度和长时间序列土地覆盖监测的缺点,文章以合肥市为研究区,借助谷歌地球引擎(Google Earth Engine,GEE)平台,利用2000—2020年多景Landsat卫星影像和多种辅助数据,采用随机森林(random forest,RF)算法得到土地覆盖分类图,并对土地覆盖变化(land cover change,LCC)进行驱动力因素分析,基于植被覆盖度(fractional vegetation cover,FVC)反演算法进一步得到FVC时空变化。研究结果表明:近20年来研究区土地覆盖时空变化特征十分明显,FVC时空变化呈现减少特征;人口增加和社会经济发展是LCC主要驱动因素。

关键词: 遥感；土地覆盖变化(LCC)；合肥；谷歌地球引擎(GEE)；时空分析

Funding

国家自然科学基金资助项目(41801234; 41701383); 安徽省自然科学基金资助项目(1808085QD105)和安徽省测绘科技专项资金资助项目(W2018JSFW0629)

合肥工业大学学报(自然科学版)

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