China has the largest population and the fastest growing economy in the world. The general public's demand for health is rising promptly with the improvement of the living standard. However, the limited and unbalanced medical resource have caused the prominent problem of the society, even in the capital city of Beijing, the new hospital constructions with rational allocation is iminent and significant. Along with the technology development and Internet popularization, GIS approaches and related products has been widely used in the people's daily life. The main focus of this paper is to select a site for building a new hospital in Haidian District of Beijing using GIS-based Multi-Criteria Analysis (MCA). With Analytical Hieraichy Process(AHP) and Rank Order Method (ROM) for the weight setting on factor criteria, necessity tests and sensitivity tests are applied to check which criteria are really necessary and how the results are sensitive to their weight change. The optimal site located in Wenquan Town (E: 116.182, N:40.039) is screened from several candidate sites usin Google Earth maps, which makes the ultimate result more convincing and practical. It can be concluded that GIS-based MCA with necessity and sensitivity tests proposes a novel and useful reference to other site selection decision makers, and also provides constructive tools for the public asministration to set up efficent databases for decision makers to carry out spatial analyses. To make it more maneuverable and practical, a further research on th improvement of this method will have a promising future.

This thesis offers a method that informs on the most appropriate sites for successful tree establishment and provides protection to the planted trees in CDM forestry projects. It also offers a method that can accurately and precisely estimate woody biomass in CDM forestry projects established on an agricultural landscape. The thesis has established a set of evaluation criteria that are defined and generally agreed upon by a panel of local forestry experts in Malawi. These criteria express the degree of appropriateness of particular locations to support successful tree establishment and growth, and protect the planted trees from deforestation and forest degradation. They also influence farmers’ decision-making to allocate land for either tree planting or other competing land use options, e.g. crop cultivation. The thesis uses these evaluation criteria to functionally identify priority sites on the landscape of Central Malawi for the establishment of CDM forestry projects. The priority sites are identified using trade-off analysis tools of the GIS-based MCA protocols. Besides site identification, the thesis has established a magnitude of discrepancy that can result from the use of imported allometric models in estimating woody biomass in CDM forestry projects. Imported allometric models consistently under-estimate the woody biomass of the growing trees in the study area with a mean prediction error of as high as 50%. Local allometric models are therefore developed and they are found to be both accurate and precise in estimating woody biomass. These results imply that identification of priority sites, and accurate and precise estimation of woody biomass in CDM forestry project activities are likely and can be attained. In turn, successful establishment of CDM project activities lead to enhanced productivity that will attract expanded investments in CDM forestry projects. The thesis uses Malawi as a case study. The findings of this thesis can be scaled out to other countries whose socio-ecological characteristics are similar to Malawi. These are mostly tropical countries of the Sub-Saharan Africa. In so doing, the thesis contributes to improving productivity and estimation of carbon in CDM forestry project.