Study On Landscape Pattern Changes And Ecological Effects In Mining Area

Mining of mineral resources in China have contributed a lot to the economic boom for the past years．However, it produced many ecological and environmental problems as well. In recent years, land reclamation and ecological reconstruction in mining area has become an important solution to solve the confliction between the natural supply and human’s demand of land, improve ecological environment and ensure regional sustainable development. Evaluation of landscape pattern changes and ecological effects driven by coal mining is of great importance to keep ecosystem balance, sustainable utilization of land resources and coral resources green mining from local to regional scales.Based on the background above, this study focuses on the scientific proposition of landscape “pattern, process, effect” based on landscape ecology, ecology and ecological risk assessment theory et al., landscape pattern changes, spatial heterogeneity, gradient features and ecological effects driven by coal mining are evaluated by making use of remote sensing, geographic information system, geo-statistics technique by taking high underground water mining area Jiawang mining area as an example in mid-eastern china. Main contents of the thesis are listed as follows:(1) The thesis elaborated on the concept, composition and succession laws of ecosystem in mining area based on life cycle theory, from the perspective of complex ecological systems theory. The landscape pattern changes and their ecological effects were evaluated in mining area based on the analysis of the landscape. The connotation of ecological risk, land use change on ecological risk and evaluation method of ecological risk was stated.(2) In combined with current land use/land cover classification system, The classification system of land use and land cover in Jiawang mining area was built up, based on the data source of Landsat MSS、TM and OLI. The land use and land cover information was extracted form remote sensing images in1983,1993,2003and2013based on BP neural network by using Matlab software. The land use classification results were evaluated with Kappa coefficient, cartographic accuracy and user precision. The results show that this classification method has higher accuracy, and the overall accuracy of the classification results for each year is more than0.82. (3) The landscape grain size60m was determined as the optimal grain for landscape pattern analysis of Jiawang mining area with the method of the grain effect analysis of landscape index and data loss assessment．By adopting this grain size, the landscape pattern was analyzed form the perspective of landscape and landscape type level.(4) The author adopted CLUE-S model, which is set up through incorporating components describing the spatial autocorrelation into a classic logistic model by choosing policy, natural environment, socioeconomic and space constraint factors, to simulate land-use distribution in Jiawang in2013, which improved the simulation precision. Then three scenarios of land-use spatial allocation, namely, trend development scenario, economic-oriented scenario and ecologically oriented scenario, were established through designing different restrictions on land-use transition when running CLUE-S model in GIS environment.(5) In order to reveal the spatial behavior and the dynamics of ecosystem service value of reclaimed land in mining area, spatial heterogeneity and evolution of ecosystem service value were analyzed by using the methods of Grid GIS (Geographic Information System) and geo-statistics on the basis of the remote sensing images of Jiawang mining area in Xuzhou city.(6) The spatial-temporal differentiation of ecological risk caused by land use change were analyzed by means of spatial statistics like spatial autocorrelation and semi-variance analysis based on the method of ecological risk model which was built based on landscape disturbance index and landscape fragility. The results show that the region with high or medium ecological risk changed into the two extremes of ecological risk (low or higher ecological risk area) due to the coral mining and land reclamation.