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Research On Investigation And Monitoring Of Mine Exploitation Based On Remote Sensing In Gannan Polymetallic Mine Area

Posted on:2012-01-10Degree:MasterType:Thesis
Country:ChinaCandidate:Z F LiFull Text:PDF
GTID:2120330335491041Subject:Cartography and Geographic Information System
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With the fast development of social economy, the demand of mineral resources grows rapidly, resulting in a lot of unreasonable exploitations. The mining supervision mode in China has low operating efficiency and poor supervision effects. There are a great of challenges for China to achieve a sustainable development and utilization for mineral resources. Recently, the development of automatic extraction technology of the surface changes information provides new research idea for remote sensing investigation and monitoring of mine exploitation.This paper chose Gannan polymetallic mine in Gansu Province as the study area. Remote sensing images in 2008 and 2010 were used to research automatic extraction change information of mine exploitation. Based on that, superimposed the results of investigation in 2008, and investigation and monitoring of mine exploitation based on remote sensing had been researched in 2010. Then, the technical process of mine exploitation remote sensing investigation and monitoring which using change information automatic extraction technology had been researched.The main conclusions are that:(1)Some research methods about original data had been done, such as radiometric correction, ortho-rectification, data fusion and so on. The problem, SPOT-5 lacking of blue band, had been solved with simulating true-color. And the problem of radiation and geometric distortion of original images was solved, the spatial resolution of multi-spectral data was improved, the remote sensing image information was enriched, also the based images was provided for thematic information's extraction of mine exploitation.(2)Two typical mining areas was selected to research change information automatic extraction of mine exploitation. The results showed that five methods have certain effects to mining areas, and the change areas of the two mining areas have the same characteristics, presented as highlighted grey and a specific color rage in resulting images.(3)For auto findings of mine exploitation change information, the research method based on image segmentation algorithm to a specific goal was proposed. After analyzed the spectral characteristics of resulting images adequately, computer automatic extraction model of remote sensing information was established, band ratio was used to enhancing the gamma of target scalar and background of surface features, and mine exploitation change information were extracted by the treatments as filtering enhancement and density slicing.(4)According to accuracy analysis of several kinds of change information automatic extraction, it was assigned different weights. Data weighted matrix was used to treat multiform extraction results comprehensively, lowering the effects to precision of results made from images, automatic findings and extraction method. Tests showed when data matrix is used to treat a various of extraction results comprehensively, the rate of omission and mistaking reduce to 8.02% and 24.45%.(5)Congruenting mine exploitation thematic information in 2008 and change information obtained by automatic extraction technology between 2008 and 2010, the mine exploitation thematic information in study area was extracted, the remote sensing investigation and monitoring of mine exploitation was done in 2010. Based on that, the working flow of mine exploitation investigation and monitoring and monitoring using remote sensing change information automatic extraction was defined:data pre-processing—change information automatic extraction-- field identification--mine exploitation land occupation change monitoring--remote sensing investigate of mine exploitation.
Keywords/Search Tags:mine exploitation, change information automatic extraction, image segmentation, remote sensing investigation and monitoring, Gannan
PDF Full Text Request
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