Remote sensing for efficient describe residential land use density structures "case study of Barcelona Metropolitan Area"
frequent coverage, low cost and the possibility of overlaying images from different dates exactly on top of
each other. The determination of land-use data with high geometric and thematic accuracy is generally
limited by the availability of adequate remote sensing data, in terms of special and temporal resolution
and digital analysis image techniques.
This study introduces a methodology using information on spatial images to describe urban land-use
density and changes. The analysis is based on spatial analysis of land-cover structure mapped from
digitally classified satellite images of the metropolitan region of Barcelona. The results show a useful
separation and characterization of various types of land-uses of this area and several important structural
land-cover features were identified for this study. The analysis shows the importance of the special
measurements as second order image information that can contribute to more detailed mapping of urban
areas and towards a more accurate characterization of spatial urban growth pattern. However, Improve
classification categories one of the image processing targets based on different kind of analyses to obtain
the missing data or to divide the existing one for more class’s levels. The first level of Residential urban
fabric category obtained from satellite images data sources as a homogeneous data (undivided data).
When we are talking about residential density that’s mean the occupation of construction building areas of
lands because the volume is not exist in our case of study so the neighbour categories such as Green,
Street and industrial areas will affect on dividing the Residential density levels. Our data source is formed
by classified Spot 5 (year 2004) satellite image (False Colour image with 10m resolution) which cover the
metropolitan area of Barcelona. This paper focused on the development of a methodology based on
segmentation and buffer zone analysis for urban residential areas that may improve the urban
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