当前我国矿业城市生态风险具有高度的复杂性和严峻性，矿业活动对生态过程的作用受到城市空间格局的显著影响，在“格局-过程”理论下，形成对矿业生态风险防控的系统方法，对空间规划体系构建具有重要意义。本课题开展生态风险多要素监测，采用灰色关联度分析，揭示多种矿业风险要素之间的关联及其对风险后果的作用机制；建立多要素生态风险过程耦合模型，对大气污染、水土流失等风险过程进行动态模拟，采用多目标区位配置方法，建立生态网络，并优化生态网络的结构与组分，形成面向风险过程的优化空间格局；再对格局优化后的风险空间分布进行模拟与对比分析，阐明空间格局对风险过程的影响规律，采用GIS网格分区关联分析结合回归数学模型，量化空间参数与风险变量的关联，提出基于空间参数对风险过程控制的矿业城市空间格局优化方法。研究成果能够形成量化评估、空间模拟与优化调控的系统规划方法，为矿业城市的风险规避和生态修复提供科学依据与创新思路。

Currently, the ecological risk of mining cities in China is of great complexity and severity. The effect mining activities take on ecological process has been greatly affected by a city’s spatial pattern. From the perspective of "pattern and process" theory, forming a systematic approach for the prevention and control of mining ecological risks is of great significance to the construction of spatial planning system . Carrying out multi-source risk data monitoring, via grey relation analysis method, we reveal the correlationship among various mining risk factors as well as their effects on risk consequences. We establish the coupling model of multi-factor ecological risk process; through the dynamic simulation of risk processes such as air pollution and soil erosion, we identify the key spatial approaches of risks; adopting the method of multi-objective location allocation, we build and optimize risk-oriented ecological network, and form the optimizing spatial patterns based on risk processes; with the simulation and comparison of spatial parameters from optimizing spatial patterns, using GIS grid partition association analysis method, we quantify the connection between the spatial parameters and risk target variables, clarify the influence rule that optimizing spatial patterns have on the risk process, and put forward a safety pattern construction method of mining cities on the basis of spatial parameter control and risk process simulation. The research results can form the systematic planning method of quantitative evaluation, space simulation, and optimization control, which could provide scientific basis for both risk aversion and ecological restoration.