Land cover change analysis is one of the most important tools for landscape management purposes, as it enables exploring of long-term natural processes especially in contrast with anthropogenic factors. Such analysis is always dependent on quality of available data. Due to long tradition of map making and quality and accuracy of preserved historical cartographic data in the Czech Republic it is possible to perform an effective land use change analysis using maps dating even back to early nineteenth century. Clearly, because map making methodology has evolved since then, the primary problem of land cover change analysis are different sources and thus different formats of analyzed data which need to be integrated, both spatially and contextually, into one coherent data set. One of the most difficult problems is caused by the fact that due to different map acquisition methodologies the maps are loaded with various errors originating from measurement, map drawing, storage, digitalization and finally georeferencing and possible vectorization. This means that some apparent changes may be for example caused by different methodology and accuracy of mapping a landscape feature that has not actually changed its shape and spatial position through the time. This work deals with spatial integration of data, namely identifying corresponding lines in map layers from different epochs and adjusting the borders plotted in the less accurate map to spatially correspond to the more accurate map. For such a purpose, a special program had to be created. It basically follows the work by Malach et al., 2009 who introduced their Layer Integrator. This work however presents a significantly different approach to creating an integration tool.
Long-term effects of land use/land cover change on surface runoff in urban areas of Beijing, China