Analysis of urban sprawl at mega city Cairo, Egypt using multisensoral remote sensing data, landscape metrics and gradient analysis

This paper is intended to highlight the capabilities of synergistic usage of remote sensing, landscape metrics and gradient analysis. We aim to improve the understanding of spatial characteristics and effects of urbanization on city level. Multisensoral and multitemporal remotely sensed data sets from the Landsat and TerraSAR-X sensor enable monitoring a long time period with area-wide information on the spatial urban expansion over time. Landscape metrics aim to quantify patterns on urban footprint level complemented by gradient analysis giving insight into the spatial developing of spatial parameters from the urban center to the periphery. The results paint a characteristic picture of the emerging spatial urban patterns at mega city Cairo, Egypt since the 1970s