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基于Landsat 8遥感影像的峁底矿区土壤含水量反演研究
引用本文:王丹萍,康建荣,练靖文,崔腾飞.基于Landsat 8遥感影像的峁底矿区土壤含水量反演研究[J].有色金属(矿山部分),2023,75(1):82-89.
作者姓名:王丹萍  康建荣  练靖文  崔腾飞
作者单位:江苏师范大学地理测绘与城乡规划学院,江苏师范大学地理测绘与城乡规划学院,江苏师范大学地理测绘与城乡规划学院,江苏师范大学地理测绘与城乡规划学院
基金项目:国家自然科学基金资助项目(52074133);江苏省研究生科研与实践创新计划项目(SJCX21_1127
摘    要:为研究适用于峁底矿区土壤含水量的反演方法,以峁底矿所在的奥家湾乡为研究区域,以2013—2021年的Landsat 8 OLI_TIRS为数据源,MODIS地表温度产品为精度评定数据,选用植被供水指数法(VSWI)反演研究区9年内的土壤含水量,并分析研究区土壤含水量的时空分布特征及矿体开采对土壤含水量的影响。结果表明:1)基于Landsat 8遥感影像数据,植被供水指数法可用于反演峁底矿区及周边环境的土壤含水量。2)2013—2021年,研究区土壤含水量的整体时间变化呈波动降低的趋势,空间上以“北部高、东部较高、西部低”分布为主。3)2013—2021年,研究区土壤含水量的类型发生了明显变化,土壤含水量的整体变化趋势较差。4)矿体开采过程中排水等一系列操作使得土壤含水量有短暂的升高,但长期开采导致土壤含水量降低。通过研究土壤含水量在煤矿开采的影响下产生的变化情况,研究结果可为该地区土壤含水量的实时监测、动态预估以及改善生态环境提供一定的科学依据。

关 键 词:土壤含水量  地表温度(LST)  归一化植被指数(NDVI)  植被供水指数(VSWI)
收稿时间:2022/9/15 0:00:00
修稿时间:2022/10/18 0:00:00

Inversion of soil moisture in maodi coal mine area based on landsat 8 image data
Authors:WANG Danping  KANG Jianrong  LIAN Jingwen and CUI Tengfei
Affiliation:School?of?Geomatics?&?Planning,?Jiangsu?Normal?University, Xuzhou Jiangsu 221116, China),School?of?Geomatics?&?Planning,?Jiangsu?Normal?University, Xuzhou Jiangsu 221116, China),School?of?Geomatics?&?Planning,?Jiangsu?Normal?University, Xuzhou Jiangsu 221116, China),School?of?Geomatics?&?Planning,?Jiangsu?Normal?University, Xuzhou Jiangsu 221116, China)
Abstract:This study aims to analyze the applicable inversion method to the soil moisture content in the Maodi coal mine area. To achieve this goal, the Aojiawan Township, where the Maodi coal mine is located, was selected as the study area of the subject. The primary data of this study is the Landsat 8 OLI_TIRS data from 2013 to 2021, and the land surface temperature from MODIS was participating as the accuracy assessment data. Moreover, the vegetation supplication water index (VSWI) method was used while inverting the soil moisture content of the study area over the selected years. At last, the spatial and temporal distribution characteristics of soil moisture content and the effects of coal mining on soil moisture were analyzed. Based on the study, there are several results. Firstly, based on the Landsat 8 image data, VSWI can be used to invert the soil moisture content of the Maodi coal mine and its surrounding environments. Secondly, the overall temporal variation of soil moisture content in the study area from 2013 to 2021 showed a fluctuating decrease trend, with a spatial distribution of "high in the north, high in the east, and low in the west". Thirdly, from 2013 to 2021, the soil moisture content in the study area changed significantly, while the overall trend of soil moisture content decreased. Lastly, a series of operations, such as drainage during coal mining, had made the soil moisture content temporarily increased, but long-term mining has led to decrease in soil moisture content. Therefore, this paper mainly studied the change in soil moisture content under the influence of coal mining. The results of this study can provide a scientific reference for real-time monitoring and dynamic prediction of soil moisture content and improvement of the ecological environment in the area.
Keywords:soil moisture  Land Surface Temperature (LST)  NDVI  Vegetation Supplication Water Index (VSWI)
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