Urban Development Suitability Research Articles

Correction: Dong, J. et al. Integrated Evaluation of Urban Development Suitability Based on Remote Sensing and GIS Techniques–A Case Study in Jingjinji Area, China. Sensors 2008, 8, 5975–5986

We found that formula (1) was incorrect in our paper published in Sensors in 2008 [1]. [...]

Integrated Evaluation of Urban Development Suitability Based on Remote Sensing and GIS Techniques - A Case Study in Jingjinji Area, China.

Jingjinji area (namely Beijing, Tianjin and He Bei Province) is one of the three largest regional economic communities in China. Urban expansion has sped up in the past 20 years in this area due to the rapid economic and population growth. Evaluating the land-use suitability for urban growth on a regional scale is an urgent need, because the most suitable areas and the most suitable scale of urban growth can thus be determined accordingly. In order to meet this requirement, remote sensing and geographic information system (GIS) techniques were adopted, and an integrated evaluating model was developed supported by AHP method. The integrated urban development suitability index (UDSI) was calculated using this model. According to the UDSI result, the spatial distribution of urban development suitability and its driving forces were analyzed. Urban boundaries in 1995, 2000 and 2005, which were derived from Landsat TM/ETM+ satellite data, were overlaid on the UDSI map, and the suitable urban develop tendency in this area were discussed. The result of this study indicated that integrated evaluation of urban development could be conducted in an operational way using remote sensing data, GIS spatial analysis technique and AHP modeling method.

Suitability Assessment for New Minia City, Egypt: A GIS Approach to Engineering Geology

Urban development is a high priority in Egypt. New Minia City, located on the eastern bank of the Nile River, approximately 250 km south of Cairo, is one of 16 new development communities. Urban development in New Minia City may encounter several geo-environmental problems. Karst conditions and structural features in the local heterogeneous bedrock limit its suitability for constructional purposes. In this research, suitability of the area for urban development was assessed using a geographic information systems (GIS)-based approach. A weighted GIS model that incorporated land use/cover, types of soil, karst feature distribution, fracture densities, slopes, distances to major faults and streams, road network, and city boundaries was established to create a map of site suitability for the city. Model weights were developed using the analytical hierarchy process (AHP) approach. Current urban land use within New Minia City falls into four classes of suitability. Approximately 7 percent of the area built by 2002 is in the low suitability class, which suggests that the map of site suitability can serve as a reliable base for planning sustainable development in New Minia City. The developed map of site suitability is effective for assessing and revealing ratings of suitability for urban development. Furthermore, the map of suitability provides the foundation for informed decision making in the development of New Minia City.

Performing Land-Capability Evaluation by Use of Numerical Taxonomy: Land Use and Environmental Decisionmaking Made Hard?

Researchers have attempted to incorporate environmental variables into the land-use planning process by use of several ranking and mapping formulations. Most of these are based on some type of classification scheme. More recently, multivariate statistical techniques have been utilized to classify land areas into groups with similar suitability for urban development. A test was made of one of these numerical taxonomic techniques on a data set from Medford Township, New Jersey, and the results analyzed in terms of the pros and cons of these methods. A group of 484 forty-acre grid cells with forty-two environmental variables was collapsed into a ten variable set for ten groups of grid cells having like characteristics. The analysis involved two steps, factor analysis followed by a euclidean-distance-classification algorithm. The results show that numerical taxonomy can greatly facilitate the analysis of large environmental data sets and can help to identify the ecological relationships in quantitative terms. However, the complexity of the statistical methods involved greatly limits the wide application of these techniques, and the use of numerical taxonomic results in land-capability evaluation cannot release the researcher from making many judgmental decisions.