|| In the past, due to the global industrialization, various industries were set up in Taiwan. A ton of by-products or wastes from industries have been emitted into our environment without any proper treatments. These wastes eventually lead to water pollution in irrigation area and soil pollution. Because the heavy metals emitted from industrial sector into soil are highly toxic, long-lasting and persistent, they tend to adverse effects on public health and environment. In addition, soil heavy metals also affect species inhabiting in the contaminated area via food webs. Heavy metals tend to accumulate in plants and lower-level consumers inhabiting in contaminated soil, and further magnify into higher consumers level, such as birds, through unintentionally intaking heavy metal toxicities into their body when preying on plants or lower-level consumers. Therefore, in addition to setting up monitoring and controlling processes, a comprehensive remediation design focusing on soil heavy metal contamination needs to be proposed. In this study, we took eight soil heavy metals and eight birds of which the protected level is greater than conservation-deserving level as an example. Based on the survey data of soil heavy metals, we applied geostatistics to jointly simulate the possible distribution of eight soil heavy metals in Taiwan. After that, based on Taiwan’s Environmental Protection Administration (EPA) decided classification, in which the concentrations of soil heavy metals were classified into five classes, the area with concentrations within or above fourth range are regarded as polluted. Besides, the uncertainty analysis for simulated distributions of soil heavy metals is also completed. With respect to the simulation of bird distribution, we applied bootstrap resample technique and species distribution model to generate as many distributions as possible. The area with high ecological values are delineated using Zonation, a systematic conservation model, based on the possible bird distributions. Similar to soil heavy metals, the uncertainty analysis for simulated distributions of bird was also completed. Finally, based on the simulated maps of soil heavy metals and birds, a robust decision-making approach is used to evaluate the performance of each candidate solution and decide the area in need for remediation. The results show the approach proposed in this study can help decision-makers to set up the remediation area given the pollution-free habitat suitability (index of ecological value based on environmental pollution), false positive rate (dividing the number of non-polluted areas that are wrongly classified as contaminated by the total number of non-polluted areas) and robustness (the proportion of realizations in which the pollution-free habitat suitability and false positive rate both reach pre-defined standards). This study provides decision-makers with a structural approach in consideration of the influence of uncertainty which is applicable to the decision making regarding environmental remediation based on the quantified robustness.