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    Land Reclamation in Ecological Fragile Areas : Proceedings of the 2nd International Symposium on Land Reclamation and Ecological Restoration (LRER 2017), October 20-23, 2017, Beiji... Yazar: Zhenqi, Hu

    Baskı/Yayın Bilgisi Taylor & Francis Group, 2017.
    İçindekiler: “…Study on calculating projection deformation of measured length using an amended particle swarm optimization -- Study on the acquisition technology for information on damaged land in coal-mining areas -- Deformation mechanism and support measures of the soft rock roadway in Ronghua coal mine -- Evaluation of the ecological environment in mining areas based on fuzzy comprehensive evaluation method -- Evaluation for land damage in mining areas with a high underground water level based on RS -- Assessing ecological security based on fishnet: A case study of Guiyang City -- The application of classified assignment and power-law models for wound space in quantitative assessments of degraded land -- Preliminary analysis of the geological hazards prediction in the process of coal mining -- The application of mobile GIS in mine land reclamation monitoring -- Object-based change monitoring in mining areas-taking Pingshuo as an example -- Fast surveying and large scale mapping in the mining area of the delta wing -- Study on the limit angle of mining subsidence basin based on the field survey data in the mining area -- Formation mechanisms and characteristics of ground collapse during shallow coal seam mining -- Urban heat island effect of mining cities under mining disturbance: A case study of Wu'an -- Application of fuzzy mathematics and GIS technology in the evaluation of mine environmental restoration -- Ecological footprint and carrying capacity of mining cities: A case study of Wu'an -- Landscape pattern change monitoring and predicting using remote sensing method-taking Jiaozuo as an example -- Monitoring of vegetation coverage by multi-temporal remote sensing images: A case study of Yulin coal mine -- Remote sensing inversion of soil organic carbon in Jining city based on decision tree classification.…”
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