The study sets out the benefits of the new IKONOS satellite image data for urban planning and for urban information tasks in general. Following a brief delineation of the reference modalities,the quality of the data is assessed and the problems for georeferencing are pointed up.Diverse fields of application of the data in urban planning and aministration are then enumerated.

Traditional methods use NDVI to investigate vegetation cover from remote sensing imagery. These methods provide per-pixel vegetation distribution, and cause a modifiable areal unit problem (MAUP), when a meaningful statistical result is issued. In this paper, a new method based on advanced segmentation techniques and classification is proposed for urban vegetation investigation extraction. This method utilizes ASTER data to build a hierarchical multi-resolution structure, so as to reflecting the inherent relationship between ground features under various scale levels.

The recent increase in spatial resolution of data from spaceborne sensor systems, strongly improved the target discrimination capacity. One of the areas that benefited from such type of images, is the remote sensing of urban areas which, in spite of the availability of high spatial resolution sources (such as aerial photographs), did not have data available with both high spatial and radiometric resolution hitherto.