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Ma Deli, Sun Yongkang, Yang Jianying, Shi Changqing, Zhang Yan, Zhang Chunyu. Site condition classification based on remote sensing technology of unmanned aerial vehicle in abandoned quarry[J]. Journal of Beijing Forestry University, 2018, 40(9): 90-97. DOI: 10.13332/j.1000-1522.20180051
Citation: Ma Deli, Sun Yongkang, Yang Jianying, Shi Changqing, Zhang Yan, Zhang Chunyu. Site condition classification based on remote sensing technology of unmanned aerial vehicle in abandoned quarry[J]. Journal of Beijing Forestry University, 2018, 40(9): 90-97. DOI: 10.13332/j.1000-1522.20180051

Site condition classification based on remote sensing technology of unmanned aerial vehicle in abandoned quarry

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  • Received Date: January 31, 2018
  • Revised Date: April 04, 2018
  • Published Date: August 31, 2018
  • ObjectiveThe combination of unmanned aerial vehicle (UAV) remote sensing image and ArcGIS technology has become a new method of ecological restoration in abandoned land. The accurate classification of site conditions is the key step of ecological restoration and mine greening of abandoned quarries. The purpose of this study is to classify site conditions of abandoned quarries in the north of Hebei Province, northern China quickly and accurately based on UAV remote sensing images and GIS technology.
    MethodBy quantitative theory Ⅰ and ArcGIS spatial analysis, the classification and quality evaluation of site types of abandoned mines were studied. The site type distribution map was obtained and the accuracy of site classification results was tested.
    ResultUsing above method, the grass cap mountain quarry in the north of Hebei Province was divided into 9 site types, and the site was classified into 4 grades according to the site classification results. Compared with the field site type survey results, the accuracy of the study classification results reached 96%.
    ConclusionThe application of UAV remote sensing image and GIS technology can not only realize the high-precision classification of site types in quarry wasteland, but also provide decision basis and technical support for the rational planning of afforestation and greening of mine wasteland.
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