| 基于Google Earth Engine云平台的植被覆盖度变化长时间序列遥感监测 |
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| 引用本文： | 裴 杰,牛 铮,王 力,黄 妮,曹建华.基于Google Earth Engine云平台的植被覆盖度变化长时间序列遥感监测[J].中国岩溶,2018,37(4):608-616. |
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| 作者姓名： | 裴 杰 牛 铮 王 力 黄 妮 曹建华 |
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| 作者单位： | 1.中国科学院遥感与数字地球研究所遥感科学国家重点实验室/中国科学院大学 |
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| 基金项目： | 喀斯特断陷盆地石漠化演变及综合治理技术与示范(2016YFC0502501)；国家自然科学基金项目（41371358） |
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| 摘 要： | 基于Google Earth Engine遥感大数据云计算平台，以云南省南洞地下河流域为例，利用近2 000景30 m分辨率Landsat-NDVI长时间序列数据，采用像元二分模型对研究区1988-2016年的年最大植被覆盖度进行定量估算，并分别从流域整体和像元尺度分析近29 a间植被覆盖度的时空变化特征。研究结果表明:（1）南洞地下河流域大部分区域处于中等覆盖度和中高覆盖度，覆盖度随高程和坡度的增加而增大，其中年最大植被覆盖度 > 60%的区域占流域总面积的45.75%；（2）近29 a来，流域年最大植被覆盖度整体呈现不断增加的趋势，年均增长速率为0.56%，其中植被覆盖度轻微改善或是明显改善的面积占38.84%；（3）相比1988年，2016年高植被覆盖区和中高植被覆盖区面积分别增长50.51%、18.40%；而中等植被覆盖区、中低植被覆盖区和低植被覆盖区面积分别减少24.05%、47.95%和37.72%。封山育林等石漠化治理工程以及气候变化对于流域植被恢复和生态环境重建具有重要影响，其研究成果可为后续石漠化监测提供重要的基础研究数据。
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| 关 键 词： | Google Earth Engine 植被覆盖度 像元二分模型 时空变化 Landsat 南洞地下河流域 |
Monitoring to variations of vegetation cover using long-term time series remote sensing data on the Google Earth Engine cloud platform |
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| PEI Jie,NIU Zheng,WANG Li,HUANG Ni and CAO Jianhua.Monitoring to variations of vegetation cover using long-term time series remote sensing data on the Google Earth Engine cloud platform[J].Carsologica Sinica,2018,37(4):608-616. |
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| Authors: | PEI Jie NIU Zheng WANG Li HUANG Ni and CAO Jianhua |
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| Institution: | 1.State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences/University of Chinese Academy of Sciences2.State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences3.Institute of Karst Geology, CAGS/ Key Laboratory of Karst Dynamics, MNR＆GZAR, Guilin/The International Research Center on Karst under the Auspices of UNESCO |
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| Abstract: | In this paper, we take the Nandong underground river watershed as an example, to quantitatively estimate annual maximum Fractional Vegetation Cover(FVC) using time series Landsat-NDVI data from 1988 to 2016. There were in total 1952 scenes extracted and analyzed using Dimidiate Pixel Model through Google Earth Engine which is the most advanced cloud computing platform for remotely sensed big data. Spatio-temporal change characteristics during the past 29 years were also analyzed on both the entire groundwater water catchment and a pixel scales, respectively. Results show that，(1) Most parts of the Nandong underground river watershed have the middle or middle-high coverage; FVC increases with the growing elevation and slope; the area of the region in Nandong which has the annual maximum FVC higher than 60% accounts for 45.75% of the total watershed. (2) During the past 29 years, the annual maximum FVC exhibits a growing trend in Nandong, with the average annual increase rate of 0.56%. The area of the region which experienced slight improvement or obvious improvement in FVC accounts for 38.84% of the total area. (3) Compared with 1988, the area of high coverage and middle-high coverage regions in 2016 increased by 50.51% and 18.40%, respectively. While the area of the middle coverage region, middle-low coverage and low coverage regions decreased by 24.05%, 47.95% and 37.72%, respectively. Comprehensive control on karst rocky desertification, e.g. natural forest conservation and climate change, have important effects on vegetation recovery and eco-environment reconstruction in Nandong. Results of this study can provide basic data for monitoring to subsequent karst rocky desertification. |
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| Keywords: | Google Earth Engine fractional vegetation cover Dimidiate Pixel Model spatio-temporal change Landsat Nandong underground river watershed |
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