基于无人机遥感的开采沉陷耕地质量评价及复垦建议

Quality Evaluation of Farmland and Land Reclamation Suggestions of Mining Subsidence Area Based on Unmanned Aerial Vehicle Remote Sensing

针对我国东部高潜水位矿区煤炭开采造成耕地减产绝收及生态破坏等问题,以东滩煤矿开采沉陷耕地玉米作物为例,利用无人机多光谱影像和田间同步实测数据,采用经验模型法建立了开采沉陷耕地玉米叶面积指数反演模型并进行了耕地质量评价。结果表明:引入红边波段的归一化植被指数(red-red edge normalized differ?ence vegetation index,RRENDVI)构建的幂函数模型为最优模型,其R2=0.756,RMSE=1.125,模型具有较高的精度和可靠性。通过该模型对研究区玉米叶面积指数(leaf area index,LAI)进行反演,得到玉米LAI分布图。根据研究区玉米及当地正常生长玉米的LAI均值,并结合实际沉陷积水情况,构建了沉陷耕地质量评价规则,将开采沉陷耕地分为五等,根据各等级地块损毁程度分别提出了划方平整、挖深垫浅等复垦建议。分析结果对于小范围沉陷耕地损毁监测、耕地质量评价及复垦工作具有一定的参考价值。

In view of the problem of reduced yield and ecological damage caused by coal mining in the high phreatic mining area in the east of China,takes the maize crop of coal mining subsidence in Dongtan Coal Mine as an example,based on the multi-spectral image of the UAV(unmanned aerial vehicle)and the field measured data,and combing with the empirical model method,the inversion model of maize leaf area index of coal mining subsidence farmland is established and the quality evaluation of farmland carried out.The results show that the power function model established by the RRENDVI(red-red edge normalized difference vegetation index)is the optimal model with R2=0.756 and RMSE=1.125,and this model has features of high precision and reliability.Based on the model,LAI of maize from the study area was inverted to obtain the distribution map of maize LAI.According to the spatial distribution of maize LAI in the study area and the average value of local normal growing maize LAI,combing with the actual subsidence of water accumulation,the quality evaluation rules for subsided farmland are constructed,and the quality of coal mining subsidence is classified into five grades.According to the degree of damage of various grades of farmland,suggestions for reclamation are proposed,such as flattening,digging,deepening and padding.The above discussion results has important guiding significance for monitoring the damage to farmland in small subsidence area,evaluation the farmland quality and land reclamation.