{ "culture": "en-US", "name": "", "guid": "", "catalogPath": "", "snippet": "", "description": "Method descriptionWe developed a method that approximates the prediction pixels into polygons making decisions based on the whole prediction feature space. This is very different from standard approaches, e.g. Douglas-Peucker algorithm, which are greedy in nature. The method tries to impose some of a priory building properties, which are, at the moment, manually defined and automatically tuned. Some of these a priori properties are:The building edge must be of at least some length, both relative and absolute, e.g. 3 metersConsecutive edge angles are likely to be 90 degreesConsecutive angles cannot be very sharp, smaller by some auto-tuned threshold, e.g. 30 degreesBuilding angles likely have very few dominant angles, meaning all building edges are forming angle of (dominant angle ± nπ/2)Data VintageThe vintage of the footprints depends on the vintage of the underlying imagery. Because Bing Imagery is a composite of multiple sources it is difficult to know the exact dates for individual pieces of data.", "summary": "", "title": "Building Footprints (Leading Edge Geomatics)", "tags": [], "type": "", "typeKeywords": [], "thumbnail": "", "url": "", "minScale": 0, "maxScale": 0, "spatialReference": "", "accessInformation": "Microsoft, BING", "licenseInfo": "" }