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基于多源遥感数据和GEE平台的博斯腾湖面积变化及影响因素分析
引用本文:彭妍菲,李忠勤,姚晓军,牟建新,韩伟孝,王盼盼.基于多源遥感数据和GEE平台的博斯腾湖面积变化及影响因素分析[J].地球信息科学,2021,23(6):1131-1153.
作者姓名:彭妍菲  李忠勤  姚晓军  牟建新  韩伟孝  王盼盼
作者单位:1.西北师范大学地理与环境科学学院,兰州 7300702.中国科学院西北生态环境资源研究院 冰冻圈科学国家重点实验室/天山冰川观测试验站,兰州 7300003.石河子大学理学院,石河子 8320004.中国科学院西北生态环境资源研究院 甘肃省遥感重点实验室,兰州 7300005.中国科学院大学,北京 100049
基金项目:第二次青藏高原综合科学考察研究(2019QZKK0201);中国科学院战略性先导科技专项(A类XDA20060201、XDA20020102);国家自然科学基金项目国际合作(41761134093);国家自然科学基金项目(41471058);冰冻圈科学国家重点实验室自主课题资助(SKLCS-ZZ-2020)
摘    要:作为典型的干旱区内陆湖泊,博斯腾湖的面积变化趋势与当地自然和人文环境的变迁密不可分。本文结合GIS与RS技术,利用Landsat影像和MODIS数据共2289景及JRC GSW水体掩膜产品,基于Google Earth Engine(GEE)平台采用指数法得出2000—2019年博斯腾湖面积年际和年内变化趋势,并采用2019年Sentinel-2影像进行结果对比分析,同时通过2000—2018年焉耆、库尔勒和巴音布鲁克气象站日值数据和人类活动分析其变化原因。得出如下结论:① 本结果中基于海量遥感数据提取面积的结果表明,GEE可以充分应用高时间分辨率遥感数据进行湖泊年际尤其是年内面积变化分析。相比于Landsat-5/7/8影像与MOD09GQ数据,由于Sentinel-2影像的时空分辨率优势,基于其所得的湖岸线可显示出较多细节。② 2000—2013年博斯腾湖面积共减少181.66 km2,变化速率为13.98 km/a;2013—2019年,湖泊共增加133.13 km2,变化速率为22.19 km2/a;③ 博斯腾湖面积一般在每年的3—6月呈上升趋势,且在当年6—9月保持峰值,面积在10—12月减小;④ 博斯腾湖面积年际变化与其流域内焉耆、库尔勒、巴音布鲁克气象站的降水、蒸发及积温因素变化的相关性未达到显著水平,而年内变化与上述气候要素相关性较高。

关 键 词:博斯腾湖  面积变化  遥感提取  湖岸线  Landsat  MODIS  Sentinel-2  Google  Earth  Engine  
收稿时间:2020-06-30

Area Change and Cause Analysis of Bosten Lake based on Multi-source Remote Sensing Data and GEE Platform
PENG Yanfei,LI Zhongqin,YAO Xiaojun,MOU Jianxin,HAN Weixiao,WANG Panpan.Area Change and Cause Analysis of Bosten Lake based on Multi-source Remote Sensing Data and GEE Platform[J].Geo-information Science,2021,23(6):1131-1153.
Authors:PENG Yanfei  LI Zhongqin  YAO Xiaojun  MOU Jianxin  HAN Weixiao  WANG Panpan
Abstract:Bosten Lake is a typical inland lake in the arid zone. The change in the lake area is strongly related to local natural and cultural environmental changes. Based on the GIS and RS technologies, this paper combines Landsat imagery and MODIS data, including a total of 2289 scenes, with JRC GSW water mask products to characterize the interannual and intraannual changes of the area of Bosten Lake from 2000 to 2019 through the Google Earth Engine (GEE) platform using index methods. We use the 2019 Sentinel-2 images to compare and analyze the results. To quantify the the causes of the changes, we analyzed the human activities and daily meteorological data of Yanqi, Korla and Bayanbuluk meteorological stations during 2000-2018. Results show that: (1) the GEE is efficient for integrating multi-temporal high-resolution remote sensing data to analyze the temporal change of lake area, especially the intraannual change. Compared with Landsat-5/7/8 and MOD09GQ data, the lake shoreline extracted based on Sentinel-2 images shows more details due to their high temporal and spatial resolution; (2) during 2000-2013, the total lake area decreases by 181.66 km2 with a decreasing rate of 13.98km2/a; while during 2013-2019, the lake area increases by 133.13 km2 with a increasing rate of 22.19 km2/a; (3) Intraannually, the lake area shows an upward trend from Mar. to Jun., keeps peak until September, and decreases from Oct. to Dec. and (4) the interannual change of Bosten Lake area has no significant correlations with the changes of evaporation, precipitation, and accumulated temperature within the watershed. While the intraannual change of Bosten Lake area shows strong correlations with those meteorological varabiles.
Keywords:Boston Lake  area Change  remote sensing extraction  shoreline  Landsat  MODIS  Sentinel-2  Google Earth Engine  
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