Abstract
The on-going growth of urban area in Flanders and in the Brussels Capital Region over the past decades has resulted in a highly sprawled urban tissue, consisting of large and smaller urban agglomerations, connected by a well-developed transportation network. The conversion of open land to urban area is accompanied by an increase in soil sealing, affecting the hydrological cycle and the urban climate. Despite a growing interest in monitoring the process of soil sealing in urban areas, to date no detailed information on the presence and evolution of sealed surfaces is available for Flanders. In this paper a linear regression unmixing approach is proposed to map and monitor changes of sealed surface cover at the regional scale, using medium as well as high resolution remote sensing data. Applied to Flanders and the Brussels Capital Region, a total sealed area of 2687 km² for 2013 is found, corresponding to an increase of 82% since 1976. Residential areas account for nearly half of the sealed area and show the largest increase in sealed surface cover over the past 37 years.
Highlights
The research presented in this paper is funded by
the applicable building regulations during the time period in which the development took place are found to be the main drivers of densification
the major bottleneck of object-based classification is the quality of the segmentation
Summary
10 Perhaps the most straightforward method to estimate the sealed surface cover fraction from a pixel's spectral properties is the use of linear or non-linear regression (Sawaya et al, 2003; Yang & Liu, 2005; Bauer et al, 2008; Van de Voorde et al, 2011), where the fraction of sealed surface cover or its complement – the vegetation fraction – is directly inferred from the pixel’s reflectance in one or more spectral bands, and/or from spectral indices that can be related to the sealed surface or vegetation fraction. Yang & Liu (2005) propose the use of tasselled cap brightness and greenness to estimate the fraction of sealed surface cover from Landsat TM/ETM+ imagery for Pensacola, Florida (US) for two different moments in time to identify hot spots of urban growth.
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