The effects of sensor spatial resolution and changing grain size on fragmentation indices in urban landscape

Satellite images are now used as the primary source of spatial information for landscape pattern analysis. Choosing data of proper resolution has always been a big problem for landscape pattern analysis using satellite images. However, the effects of remote sensor spatial resolution on urban landscape fragmentation have never been reported. In this study, landscape fragmentation of Shanghai was analysed using land use maps produced from TM and IRS-PAN images, attempting to discover the effects of remote sensor spatial resolution on urban landscape fragmentation. Four landscape fragmentation indices were computed along a 51 km long and 9 km wide transect cutting across Shanghai with a moving window to detect the behaviour of landscape indices along the gradient of land use zones. The results showed that fragmentation indices were sensitive to varied spatial resolution and grain size, indicating that fine resolution data and small grain size of about 7.5m might be optimal for urban fragmentation analysis. The behaviour of landscape indices along the gradient of land use zones suggests that urban fragmentation can be distinguished as occurring in two phases: dissection introduced by roads and shrinkage caused primarily by urban sprawl.