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The Application Of Remote Sensing Technology To Forecast The Groundwater Recourse

Posted on:2020-11-17Degree:MasterType:Thesis
Country:ChinaCandidate:Y Y WangFull Text:PDF
GTID:2370330590987386Subject:Resources and Environment Remote Sensing
Abstract/Summary:PDF Full Text Request
As we all know,remote sensing technology methods are widely used in geological exploration,hydrogeological survey,groundwater prediction,etc.due to their many advantages such as macroscopicity,timeliness and limited access to information.The northwestern part of China is mostly in arid and semi-arid areas with harsh environment.The exploration of groundwater by means of remote sensing can not only reduce the burden of field geological workers,improve the efficiency of geological mapping,but also solve the problem of local drinking water and serve the relevant departments.Research and development of flood control and drought relief policies.The structural conditions are the key factors for the formation of groundwater,and the favorable water storage structure,as a place for groundwater formation,movement and storage,its characteristics and properties control the amount of groundwater.The surface water body replenishes the groundwater,and the groundwater can also be drained to the loess gully area to form small runoff or springs.Therefore,the construction conditions,surface water bodies,and water-bearing rock layers are the key elements of the hydrogeological element method and are essential for predicting groundwater.However,the predecessors' application research on this method mostly stays in the area where the bedrock is well exposed,and rarely involves the loess coverage area.For the construction interpretation,more attention is paid to the establishment of the interpretation mark directly on the geological body through the image itself.However,the differences in the spectrum,texture and hue of the loess cover area are weak,and the difficulty of directly interpreting the mark is not effectively solved;The extraction of surface water information has not been able to fully utilize high-resolution images to reinterpret small-scale water bodies such as surface springs and wetlands,and to eliminate the false anomaly information of the same-spectrum foreign bodies with water information,resulting in water body interpretation accuracy and precision.Not enough,seriously affecting the judgment of groundwater occurrence information.This paper takes the loess-covered area in the northern part of Baoji City,Shaanxi Province as the research area,and uses Landsat 8 OLI,Resources No.3,SPOT-6 and other remote sensing satellite images,DEM elevation data,and spectral reflectance data of measured water bodies as data sources.Image preprocessing,image correction,image extraction,and spatial analysis,such as calibration,atmospheric correction,geometric correction,image cropping,etc.,to interpret information such as fault structure in loess-covered areas,spatial distribution of surface water systems,and small-scale water bodies on the surface.In the previous studies on the interpretation of lithology in this area,the prediction of groundwater enrichment area was completed,and the application range of remote sensing technology in groundwater prediction was broadened,which provided new ideas and methods for hydrogeological investigation in loess cover area..The research contents and research results of this paper have the following specific points:1.Fully collected remote sensing images,DEM elevation data,geological maps,topographic maps,and spectral reflectance data of measured water bodies in different spatial resolutions in the study area,and preprocessed the images for the special case of loess cover.,image enhancement and other operations,highlighting the features of the features,to facilitate interpretation of the ground.2.In order to solve the relatively difficult problem of constructing the interpretation mark in the study area,we perform principal component analysis on the image,enhance the hue and saturation of the image,highlight the texture feature,and establish the interpretation mark from the front.The gully water system in the study area was extracted,and its relationship with the structural distribution was analyzed,and the interpretation mark was established from the side.The research shows that the false color composite images of the main components of Landsat OLI images PC1,PC3 and PC4 are rich in color,which can highlight geological information and environmental information,and the geological structure determines the spatial distribution of the valley water system.The distribution of the valley water system is also certain.The extent reflects the existence of fracture structures.3.In the process of extracting surface water information,the band ratio is firstly imaged to highlight the water body characteristics,then the fractal water model is used to extract the surface water body information,and the extracted false anomaly information is removed by spatial analysis.The research shows that the B4/B7 band ratio image of Landsat OLI image can effectively enhance the water body information,and its effect is comparable to the water body index method such as NDVI,and the fractal model can accurately give the classification thresholds of different water bodies and distinguish them.Based on the interpretation results of the water system in the study area after the gully is removed,the false anomaly information of the “homogeneous foreign matter” with the water body can be effectively eliminated,thereby enhancing the accuracy and accuracy of interpretation of the water body in the loess covered area.4.Comprehensively analyze the distribution of water control structures,water-bearing strata and surface water bodies in the area,complete the remote sensing prediction of groundwater in the study area,and carry out field verification on some prediction areas,indicating that groundwater and geology information is used to predict groundwater in the loess-covered area.
Keywords/Search Tags:Remote sensing technology, Loess coverage area, Fractal, Space analysis, Underground water
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