The focus of this research is to check if urban crime is related to the social spatial urban structure and to identify the most unsafe territories in the city of Klaipeda from the point of view of crime and urban structure. Space syntax theory and method, as well as correlation analysis have been used for this purpose. The research results have revealed that all types of crimes depend on global integration and global depth: the more integrated and shallow the open public spaces are the more crime incidents in these spaces happen.

Collaborative planning processes have been criticized for inefficiency, but attempts to improve them in planning of urban nature have been limited by lack of usable evaluation methodologies. This paper presents a framework for evaluating and designing collaborative processes in strategic planning of land use and nature areas. A framework with four key perspectives and their success criteria was developed with the help of literature and data from interviews and focus groups in two case areas in the Helsinki metropolitan area, Finland.

This work describes a methodology for Strategic Environmental Assessment of urban areas in Latin America based on the recently approved European Planning Directive, and applies it to the Metropolitan Area of Concepción (Chile). The method is based on the Land Suitability Index (LSI), a cartographic GIS-based index originally developed for the region of Barcelona (Spain) and aimed at determining the suitability of each point in a region for urban development, considering three sub-indexes: (i) Naturalness, (ii) Ecological Connectivity and (iii) Natural Risk.

Detailed urban land-cover maps are essential information for sustainable planning. Land-cover maps assist planners in designing strategies for the optimisation of urban ecosystem services and climate change adaptation. In this study, the statistical software R was applied to land cover analysis for the Catania metropolitan area in Sicily, Italy. Six land cover classes were extracted from high-resolution orthophotos. Five different classification algorithms were compared. Texture and contextual layers were tested in different combinations as ancillary data.

Cities are characterized by dynamic interactions between socio-economic and biophysical forces. Currently more than half of the global population reside in cities which influence the global biogeochemical cycles and climate change, substantially exacerbating pressures on urban pollution, water quality and food security, as well as operating costs for infrastructure development. Goods and services such as aesthetic values, water purification, nutrient recycling, and biological diversity, that urban ecosystems generate for the society, are critical to sustain.

Population growth, urbanisation and climate change represent significant pressures on urban water resources, requiring water managers to consider a wider array of management options that account for economic, social and environmental factors.

Understanding the growth and changes in urban environments are the most dynamic system on the earth’s surface is critical for urban planning and sustainable management. This study attempts to present a space-borne satellite-based approach to demonstrate the urban change and its relation with land surface temperature (LST) variation in urban areas of Klang valley, Malaysia. For this purpose an object-based nearest neighbour classifier (S-NN) approach was first applied on SPOT 5 data acquired on 2003 and 2010 and subsequently five land cover categories were extracted.

In this study, three-phase satellite images were used to define rules for the allocation of time and space in construction land resources based on a complex adaptive system and game theory. The decision behavior and rules of government agent, enterprise agent and resident agent in construction land growth were explored. A distinctive and dynamic simulation model of construction land growth was built, which integrated multi-agent, GIS technology and RS data and described the interaction among influencing agents.

BACKGROUND: Dramatic disparities in a range of health outcomes persist in Alameda County, California. Age-standardised mortality rates range from 300 to 1300 deaths per 100 000 across census tracts in this county, with life expectancies lagging by 10 years in the most disadvantaged census tracts. Finding factors at the community level that affect neighbourhood health levels is a key step towards addressing these inequalities. Walking to work may be one of these factors, and is something that local policy makers could effectively act upon through city planning and maintenance initiatives.

Thermal infrared (TIR) remote-sensing techniques have been used to estimate land surface temperatures (LSTs) and to study the relationship between land uses and LSTs. Remotely sensed thermal data provide a time-synchronized dense grid of temperature data, and there has been a growing interest on LSTs in various fields, such as urban climatology and global environmental change. It is also important for urban planning and management practices to maintain thermally efficient urban structures. This article focuses on differences between the estimated LSTs and the measured temperatures.

Urban areas are the most dynamic region on earth. Their size has been constantly increased during the past and this process will go on in the future. Since there is no standard policy and guidelines for construction of buildings and urban planning, cities tend to have irregular growth. Many cities in the world face the problem of urban sprawl in its suburbs. So issues of urban sprawl need to be settled with the help of technologies such as satellite remote sensing and automated change detection.

Climate change and energy saving are challenging the city and the territorial organization. Innovative spatial and urban planning methods and procedures are required, and new approaches and instruments must be elaborated and applied in order to shift from the building scale to the urban and territorial ones.