Applications of Multi-source Remote Sensing Information to Urban Environment Monitoring in Mining Industrial Cities

Remote Sensing (RS) has been viewed as the one of the most effective tools for environment monitoring, urban resources and environment investigation, change detection and urban growth analysis in mining industrial cities. Firstly, the framework and structure of applying multi-source RS information to environment monitoring of mining industrial cities is proposed based on the general methodologies of RS applications and the characteristics of mining industrial cities. RS can be used to monitor land use/cover change, extract subsidence land because of underground mining, analyze the dynamic change and simulate the trends of mining industrial city growth, monitor the extension of mining contamination, analyze the impacts of mining to farmland and ground buildings, assess the feasibility and performance of land reclamation and ecological reconstruction, and so on. Land subsidence is a very serious environmental damage caused by mining, and that leads to more negative impacts to ecological system, even leads to geological disaster. Three methods to extract subsidence land from RS image: thematic information based on decision tree, object-oriented subsidence land extraction and target identification based on RS information, geographical data and domain knowledge are experimented. Multi-source and multi-temporal RS information fusion is used for environmental analysis in mining areas. By the fusion of Landsat TM and SAR image, both high spatial resolution and multi-spectral information can be integrated so high classification and target extraction accuracy can be got. IHS fusion algorithm is improved by considering the image content and adaptive IHS fusion is experimented. Multi-temporal RS information fusion is used for change detecting and dynamic monitoring. By the case study in Xuzhou city, it proves that remote sensing can play important roles in environmental analysis and assessment in mining industrial cities and serve as the efficient decision-making support tool f- or regional sustainable development.