摘要
土壤水分是驱动矿区生态环境变化的关键要素。为研究黄土高原煤矿区开采沉陷对土壤水分变化的扰动影响,以彬长矿区大佛寺煤矿为例,采用主动微波和光学遥感影像反演开采沉陷区土壤水分的空间变化,用水云模型消除植被对主动微波影像的后向散射系数影响,通过实地采样数据构建支持向量机回归模型,获取矿区地表土壤水分的分布特征,分析黄土沟壑区地形因子和开采沉陷变形对矿区土壤水分变化的影响。结果表明:SVM构建的回归分析模型可以有效反演黄土高原煤矿开采区土壤水分的空间分布,地形特征对土壤水分的影响最大,沟壑区域土壤含水量更高;在未受开采影响的区域,土壤水分变化受地形坡度影响最大,坡向次之,高程影响最小;在40201工作面开采沉陷变形区域,土壤水分分布的变异系数显著增大,尤其在采动裂缝发育区更为明显。研究结果为揭示黄土高原煤矿开采区土壤水分变化的时空特征及机理提供了技术支持。
Soil moisture is the key factor to help the ecological environment in a mining area.In order to study the disturbance effect of mining subsidence on soil moisture change in the Loess Plateau coal mining area,Dafosi coal mine in Binchang mining area is taken as an example,and the active microwave and optical remote sensing images are used to invert the spatial variation of soil moisture in the mining subsidence area.The water cloud model is used to eliminate the influence of vegetation on the backscattering coefficient of active microwave images,and the support vector machine regression model is constructed by field sampling data to obtain the distribution characteristics of surface soil moisture in the mining area;the influence of terrain factors and mining subsiding deformation on soil moisture change in the loess gully region is deeply analyzed.The results show that the regression analysis model constructed by SVM can effectively invert the spatial distribution of soil moisture in the coal mining area of the Loess Plateau.The topographic characteristics have the greatest influence on soil moisture,and the soil moisture content is higher in the gully area.In the areas with little impact by mining,soil moisture change is most affected by terrain slope,followed by slope aspect and least affected by elevation.In the mining subsidence and deformation area of 40201 working face,the variation coefficient of soil water distribution increases significantly,especially in the mining fracture development area.The results provide technical support for exploring the spatio-temporal characteristics and mechanism of soil moisture change in the coal mining area of the Loess Plateau.
作者
王聪
汤伏全
马婷
贾晓卉
苏宇
薛俊磊
张馨月
WANG Cong;TANG Fuquan;MA Ting;JIA Xiaohui;SU Yu;XUE Junlei;ZHANG Xinyue(College of Geomatics,Xi’an University of Science and Technology,Xi’an 710054,China;Key Laboratory of Coal Resources Exploration and Comprehensive Utilization,Ministry of Land and Resources,Xi’an 710021,China)
出处
《西安科技大学学报》
CAS
北大核心
2024年第1期166-174,共9页
Journal of Xi’an University of Science and Technology
基金
国家自然科学基金项目(52274168)。
关键词
采煤沉陷
土壤水分
遥感影像
地形因子
黄土高原
coal mining subsidence
soil moisture
remote sensing image
topographic factor
Loess Plateau
