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资源型城市长时间序列土壤含水量变化分析——以锡林浩特市为例
引用本文:李军,桑潇,张成业,赵伟,刘新华,王宏鹏,王金阳,李佳瑶,杨颖.资源型城市长时间序列土壤含水量变化分析——以锡林浩特市为例[J].测绘通报,2021,0(7):17-22,38.
作者姓名:李军  桑潇  张成业  赵伟  刘新华  王宏鹏  王金阳  李佳瑶  杨颖
作者单位:中国矿业大学(北京)地球科学与测绘工程学院,北京100083;中国矿业大学(北京)煤炭资源与安全开采国家重点实验室,北京100083;中国矿业大学(北京)地球科学与测绘工程学院,北京100083;神华地质勘查有限责任公司,北京102209
基金项目:国家自然科学基金(41901291);中国矿业大学(北京)越崎青年学者资助计划;中央高校基本科研业务费(2021YQDC02);大学生创新训练项目(C202002179)
摘    要:大规模的煤炭开采活动将对生态环境产生扰动,而土壤含水量是受扰动的生态参数之一,且具有重要意义。现有的土壤含水量产品分辨率较低,不适用于区域尺度的研究,而高精度的微波反演由于数据的局限性无法进行长时间序列的研究。本文以我国的重要产煤基地锡林浩特市为研究区,以2004—2020年的AMSR-E与AMSR-2土壤含水量产品及同期的Landsat遥感影像为主要数据源,采用随机森林方法对AMSR-E/2土壤含水量产品进行降尺度处理,通过标准差椭圆等方法对研究区土壤含水量的变化特征进行分析。结果表明:①被动微波土壤含水量降尺度方法可实现对资源型城市的土壤含水量进行长时间序列、高空间分辨率的监测;②无论在矿区还是非矿区,降水均是影响土壤含水量变化的主导因素;③研究区土壤含水量的整体分布在空间上由西北向东南呈现逐渐升高的变化特征,且此分布格局在长时间尺度上保持稳定;④煤炭开采活动对土壤含水量产生扰动,且不同开采阶段的影响具有不同特征。研究结果可为资源型城市生态环境的评价与保护提供科学依据。

关 键 词:土壤含水量  降尺度  随机森林  长时问序列  资源型城市
收稿时间:2021-05-13

Analysis of soil moisture content changes in resource-based cities over a long time series:a case study of Xilinhot city
LI Jun,SANG Xiao,ZHANG Chengye,ZHAO Wei,LIU Xinhua,WANG Hongpeng,WANG Jinyang,LI Jiayao,YANG Ying.Analysis of soil moisture content changes in resource-based cities over a long time series:a case study of Xilinhot city[J].Bulletin of Surveying and Mapping,2021,0(7):17-22,38.
Authors:LI Jun  SANG Xiao  ZHANG Chengye  ZHAO Wei  LIU Xinhua  WANG Hongpeng  WANG Jinyang  LI Jiayao  YANG Ying
Institution:1. School of Earth Science and Surveying Engineering, China University of Mining and Technology-Beijing, Beijing 100083, China;2. State Key Laboratory of Coal Resources and Safe Mining, China University of Mining and Technology-Beijing, Beijing 100083, China;3. ShenHua Geological Exploration Co., Ltd., Beijing 102209, China
Abstract:Large-scale coal mining activities have disturbed the ecological environment. Soil moisture content is important as one of the disturbed ecological parameters. Currently, existing soil moisture content products have coarse resolution and are not suitable for regional scale studies, while microwave inversion of soil moisture content with fine resolution are limited by the data so that can not be used for long time series studies. This paper takes Xilinhot, an important coal production base in China, as the study area, and uses AMSR-E, AMSR-2 soil moisture content products from 2004 to 2020 and Landsat remote sensing images for the same period as the main data sources. The random forest method is used to downscale the AMSR-E/2 soil moisture content products. The variation characteristics of soil moisture content in the study area are analyzed by standard deviation ellipse. And the results show that:① Passive microwave soil water moisture downscaling method enables long time series and high spatial resolution monitoring of soil moisture content in resource-based cities. ② Precipitation is the dominant factor affecting soil moisture content changes in both mining and non-mining areas. ③ The overall distribution of soil moisture content in the study area shows a gradual increase in spatial characteristics from northwest to southeast, and this distribution pattern remained stable over long time scales. ④ Coal mining activities disturb soil moisture content, and the impact of different mining stages has different characteristics. The results of the study provide a scientific basis for the evaluation and protection of the ecological environment of coal cities.
Keywords:soil moisture content  downscale  random forest  long time series  resource-based city  
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