基于Google Earth Engine的京津冀2001~2015年植被覆盖变化与城镇扩张研究

doi:10.11873/j.issn.1004-0323.2018.4.0593

遥感技术与应用

2018, Vol. 33

Issue (4): 593-599 DOI: 10.11873/j.issn.1004-0323.2018.4.0593

GEE专栏

基于Google Earth Engine的京津冀2001~2015年植被覆盖变化与城镇扩张研究

张滔，唐宏

(环境遥感与数字城市北京市重点实验室，北京师范大学地理科学学部，北京 100875)

Vegetation Cover Change and Urban Expansion in Beijing-Tianjin-Hebei during 2001~2015 based on Google Earth Engine

Zhang Tao，Tang Hong

(Beijing Key Laboratory for Remote Sensing of Environment and Digital Cities，Faculty of Geographical Science，Beijing Normal University，Beijing 100875，China)

全文: PDF(5862 KB)

摘要：

目前遥感影像分析与应用的主要数据处理模式是先下载数据、再预处理、信息提取、地学分析与应用和利用算法模型提取专题信息。这种模式在大尺度地学分析与应用中存在数据收集难、存储量大、处理效率低等弊端。基于Google Earth Engine(GEE)平台的海量共享遥感影像数据和强大数据存储与云计算能力，首先利用一元线性回归趋势分析法高效地处理MOD13Q1\|NDVI数据，直观地分析京津冀2001至2015年植被覆盖变化情况；其次利用阈值法处理DMSP/OLS数据快速提取城镇建区，并利用变化检测法对比分析2001、2013年城镇的扩张和退化。结果表明：①植被变化趋势以改善为主，且改善的面积比例63%远大于退化的比例22%；植被改善的区域主要在研究区的西北部，而植被明显退化的区域主要研究区中东部(北京、天津等特大城市)。②2001年至2010年，京津冀的城镇区面积变化较小，有60%的区域未发生变化。而2013年比2010年减少的城镇面积为1.3万km²，降低的幅度为5.97%。城镇未改变区域占90.45%，城镇退化区的比例(7.2%)明显高于扩张区的比例(2.3%)。该研究充分利用GEE平台，实现快速高效处理数据，解决地学问题，为相关研究提供参考。

关键词： Google Earth Engine(GEE); NDVI时序数据; 植被覆盖变化; DMSP/OLS数据; 城镇扩张

Abstract: At present，the main mode of remote sensing image analysis is to download the data，preprocess and extract the thematic information by using the algorithm model.The model has disadvantages of huge amount of data and low efficiency in large scale area.Based on the massive remote sensing image data and powerful computing and storage capabilities of Google Earth Engine platform，we use a linear regression trend analysis method programming to process MOD13Q1-NDVI data，and then analyze the change of vegetation coverage from 2001 to 2015 in beijing\|tianjin\|hebei.We use threshold method of processing DMSP/OLS data to extract urban land，and analysis of 2001 and 2013 urban expansion and degradation by using change detection method.The results show that:(1)The trend of vegetation change was mainly improved，and the area proportion of improvement was 63%，which was far greater than the proportion of degradation 22%.The region of vegetation improvement is mainly in the northwestern part of the study area，and the region with obvious degraded vegetation is the mainly in the Middle East(Beijing，Tianjin and other megacities).(2)From 2001 to 2010，the area of Beijing，Tianjin and Hebei changed little，with a ratio of 60%.[JP2]In 2013，the area decreased by 13 thousand Km2 compared with 2010，with a decrease of 5.97%.(3)90.45% of the urban areas remained unchanged，and the proportion of urban degradation areas(7.2%) was significantly higher than that of the expansion areas(2.3%).This paper makes full use of GEE platform to realize data processing quickly and efficiently，and solve Geosciences problems，so as to provide reference for related research.[JP]

Key words: Google Earth Engine(GEE) NDVI timing data Change of vegetation cover DMSP/OLS data Urban expansion

收稿日期: 2017-11-27 出版日期: 2018-09-08

基金资助: 国家重点研发计划(2017YFB0504100)第二课题“重特大灾害应急评估与动态决策支持关键技术”（2017YFB0504102）。

作者简介: 张滔（1994-），男，四川巴中人，硕士研究生，主要从事地图制图学与地理信息工程研究。Email:zhangtaobnu@mail.bnu.edu.cn。

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引用本文:

张滔，唐宏. 基于Google Earth Engine的京津冀2001~2015年植被覆盖变化与城镇扩张研究[J]. 遥感技术与应用, 2018, 33(4): 593-599.

Zhang Tao，Tang Hong. Vegetation Cover Change and Urban Expansion in Beijing-Tianjin-Hebei during 2001~2015 based on Google Earth Engine. Remote Sensing Technology and Application, 2018, 33(4): 593-599.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2018.4.0593 或 http://www.rsta.ac.cn/CN/Y2018/V33/I4/593

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[2]	王桂钢, 周可法, 孙莉, 秦艳芳, 李雪梅. 近10a新疆地区植被动态与R/S分析[J]. 遥感技术与应用, 2010, 25(1): 84-90.

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