Assessing avian habitat fragmentation in urban areas of Hong Kong (Kowloon) at high spatial resolution using spectral unmixing

Abstract

The fragmentation, isolation and sparseness of vegetation in urban areas gives small patches of vegetation enhanced ecological value as habitat islands, compared with rural areas. Habitats as small as an individual tree may provide important landscape linkages across a densely urbanized city. Thus there is a need for micro-scale inventories of whole cities, which should incorporate not just biomass, but also vegetation of different life form, to support different habitat structural requirements. A combination of fine resolution multispectral satellite images from Ikonos, with the image processing technique of Linear Spectral Unmixing (LSU) permits the identification of different types of urban vegetation at sub-pixel level. Any fractional amount of grass and/or trees respectively within each 4 m Ikonos pixel can be identified. To evaluate such fine scale inventory, least cost path (LCP) analysis was performed using pixel fractions representing micro-scale tree habitats. This study adopts an innovative approach by allocating variable weightings to the vegetation fraction amounts within each pixel, rather than to whole pixels. The result is a fuzzy friction surface, which constitutes a very high-resolution database for input to fuzzy querying and decision-making. The friction values represent species’ preferences or tolerance levels, and may be varied according to the fraction amounts within a pixel. Automated mapping of least cost pathways over different friction surfaces produced different routes across the study area, the densely urbanized Kowloon Peninsula in Hong Kong. Comparison of the results with field data of bird sightings indicates the need for high detail in urban ecological analysis.