Toward an operational framework for fine-scale urban land-cover mapping in Wallonia using submeter remote sensing and ancillary vector data
Encouraged by the EU INSPIRE directive requirements and recommendations, the Walloon authorities, similar to other EU regional or national authorities, want to develop operational land-cover (LC) and land-use (LU) mapping methods using existing geodata. Urban planners and environmental monitoring stakeholders of Wallonia have to rely on outdated, mixed, and incomplete LC and LU information. The current reference map is 10-years old. The two object-based classification methods, i.e. a rule- and a classifier-based method, for detailed regional urban LC mapping are compared. The added value of us... Mehr ...
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Dokumenttyp: | Artikel |
Erscheinungsdatum: | 2017 |
Schlagwörter: | Télédétection / Cartographie / Systèmes d'information géographique / Géographie humaine et aménagement du territoire / Land cover / Cartograhy / Remote sensing / Wallonia |
Sprache: | Französisch |
Permalink: | https://search.fid-benelux.de/Record/base-26904093 |
Datenquelle: | BASE; Originalkatalog |
Powered By: | BASE |
Link(s) : | http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/256783 |
Encouraged by the EU INSPIRE directive requirements and recommendations, the Walloon authorities, similar to other EU regional or national authorities, want to develop operational land-cover (LC) and land-use (LU) mapping methods using existing geodata. Urban planners and environmental monitoring stakeholders of Wallonia have to rely on outdated, mixed, and incomplete LC and LU information. The current reference map is 10-years old. The two object-based classification methods, i.e. a rule- and a classifier-based method, for detailed regional urban LC mapping are compared. The added value of using the different existing geospatial datasets in the process is assessed. This includes the comparison between satellite and aerial optical data in terms of mapping accuracies, visual quality of the map, costs, processing, data availability, and property rights. The combination of spectral, tridimensional, and vector data provides accuracy values close to 0.90 for mapping the LC into nine categories with a minimum mapping unit of 15 m2. Such a detailed LC map offers opportunities for fine-scale environmental and spatial planning activities. Still, the regional application poses challenges regarding automation, big data handling, and processing time, which are discussed. ; SCOPUS: ar.j ; info:eu-repo/semantics/published