Towards automation of impervious surface mapping using high resolution orthophoto
2016-10-14T04:51:08Z (GMT) by
Information on the amount and pattern of impervious surface is important for hydrological modelling of urban areas. As cities expand and/or develop, hydrologic models will become outdated unless information on impervious surfaces is kept up to date. At the moment, the mapping teams are faced with choosing from among a range of alternative approaches/tools/software products to achieve this. We report here, the results of experiments conducted for a range of mapping approaches applied to high resolution orthophoto imagery covering part of the residential zone of Monash City, a local government area in Melbourne, Victoria, Australia. The application of the Expert Classification (EC) or Feature Analyst (FA) approaches requires initial human involvement to set the knowledge/learner function, which, then can be applied to any areas of similar spectral patterns. The Feature Analyst (FA) approach yielded superior results compared these 'pixel-by-pixel' methods. All of these approaches refer to mapping in aid of distributed and connectivity modelling. In the absence of access to EC or FA tools, application of the (sampling-based) Precision Method (PM), (after careful consideration of sampling stratification) will offer total impervious surface data-input estimates for lumped hydrological modelling.