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遥感技术与应用  2020, Vol. 35 Issue (2): 326-334    DOI: 10.11873/j.issn.1004-0323.2020.2.0326
GEE专栏     
基于Google Earth Engine的中国植被覆盖度时空变化特征分析
龙爽1,3(),郭正飞2,3,徐粒1,3,周华真1,3,方伟华1,2,3,许映军1,2,3()
1.环境演变与自然灾害教育部重点实验室,北京 100875
2.地表过程与资源生态国家重点实验室,北京 100875
3.北京师范大学地理科学学部,北京 100875
Spatiotemporal Variations of Fractional Vegetation Coverage in China based on Google Earth Engine
Shuang Long1,3(),Zhengfei Guo2,3,Li Xu1,3,Huazhen Zhou1,3,Weihua Fang1,2,3,Yingjun Xu1,2,3()
1.Key Laboratory of Environment Change and Natural Disaster, Ministry of Education, Beijing 100875, China
2.State Key Laboratory of Earth Surface Processes and Resources Ecology, Beijing 100875, China
3.Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
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摘要:

植被覆盖时空变化是全球及区域生态环境重要研究内容之一。基于Google Earth Engine云平台,利用2000~2017年250 m分辨率的MODIS-EVI长时间序列数据,采用像元二分模型并辅以趋势分析、去趋势标准差、Hurst指数方法定量估算中国自2000年来植被覆盖度时空变化,并从省域尺度分析中国植被覆盖度近18 a以及未来趋势变化的时空分异特征。研究结果表明:①2000年以来中国植被覆盖度的变化速率为0.09%/a(P<0.01),平均植被覆盖度为44.63%,空间分布格局上整体呈现“东南高、西北低”的特点,但存在空间异质性;②从省级尺度来看,海南省平均植被覆盖度最高(79%),新疆维吾尔自治区最低(13%),山西省改善趋势最显著(0.4%/a),天津市年际波动最大(DSD=0.039),位于中国最西部的3省:新疆、西藏、青海植被覆盖度年际波动最小;③全国尺度植被覆盖度Hurst指数为0.72,未来将继续保持改善的趋势。具有改善持续性的省份基本呈“T”型分布,位于东西两侧的省份应注重加强植被生态修复与防护工作,保障区域生态文明建设的持续性。

关键词: 植被覆盖度像元二分模型Hurst指数时空变化Google Earth EngineMODIS?EVI    
Abstract:

The spatiotemporal variation of vegetation coverage is one of the main research fields in Global and Regional eco-environment. Based on the Google Earth Engine cloud platform, using the MODIS-EVI long-term series data of 250 m resolution from 2000 to 2017. The model of dimidiate pixel was applied in estimating the spatiotemporal variations of Fractional vegetation coverage in China since 2000. The spatiotemporal variation characteristics of China's vegetation coverage for nearly 18 years and future trends from the provincial scale also be analyzed. Trend analysis, Detrended Standard Deviation and Hurst index were employed. The results showed that: (1) The rate of variation of vegetation coverage in China since 2000 is 0.09%/a (P<0.01), the average vegetation coverage is 44.63%. The overall spatial distribution pattern shows the characteristics of “south-high and low-lying northwest”, but there is space Heterogeneity; (2) Hainan Province has the highest average vegetation coverage (79%), the lowest in Xinjiang Uygur Autonomous Region (13%), the most significant improvement in vegetation coverage in Shanxi Province (0.4%/a). Tianjin has the largest inter-annual volatility (DSD=0.039), Xinjiang, Tibet and Qinhai province which located in the westernmost of China have the least annual fluctuations in vegetation coverage; (3) The Hurst Index of Vegetation Coverage at National Scale is 0.72, China Future vegetation coverage will continue to improve. The provinces with improved sustainability are basically “T”-type distribution, and the provinces on both sides of the east and west should focus on strengthening the ecological restoration and protection of vegetation to guarantee the sustainability of regional ecological civilization construction.

Key words: Fractional vegetation cover    Dimidiate Pixel Model    Hurst index    Spatiotemporal variation    Google Earth Engine    MODIS-EVI
收稿日期: 2018-10-09 出版日期: 2020-07-10
ZTFLH:  TP79  
基金资助: 国家重点研发计划支持项目(2017YFC1502503)
通讯作者: 许映军     E-mail: ls@mai.bnu.edu.cn;xyj@bnu.edu.cn
作者简介: 龙 爽(1993—),女,湖南岳阳人,硕士研究生,主要从事资源生态与资源遥感研究。E?mail:ls@mai.bnu.edu.cn
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引用本文:

龙爽,郭正飞,徐粒,周华真,方伟华,许映军. 基于Google Earth Engine的中国植被覆盖度时空变化特征分析[J]. 遥感技术与应用, 2020, 35(2): 326-334.

Shuang Long,Zhengfei Guo,Li Xu,Huazhen Zhou,Weihua Fang,Yingjun Xu. Spatiotemporal Variations of Fractional Vegetation Coverage in China based on Google Earth Engine. Remote Sensing Technology and Application, 2020, 35(2): 326-334.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2020.2.0326        http://www.rsta.ac.cn/CN/Y2020/V35/I2/326

图1  Google Earth Engine用户环境
图2  2000~2017年中国植被覆盖度变化
图3  2000~2017年中国植被覆盖度空间分布
图4  2000~2017年各省份植被覆盖度最大值、平均值与最小值
图5  2000~2017年各省份植被覆盖度年际波动情况
图6  2000~2017年中国植被覆盖度变化趋势以及Hurst指数分布
图7  2000~2017年中国植被覆盖度未来趋势变化
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