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<rpIndName>Mindy Cochran</rpIndName>
<rpOrgName>Flathead County GIS</rpOrgName>
<rpPosName>Program Manager</rpPosName>
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<delPoint>800 South Main Street Room 203</delPoint>
<city>Kalispell</city>
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<rpOrgName>Flathead County GIS</rpOrgName>
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<faxNum>406-758-2139</faxNum>
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<delPoint>800 South Main Street Room 203</delPoint>
<city>Kalispell</city>
<adminArea>MT</adminArea>
<postCode>59901</postCode>
<country>US</country>
<eMailAdd>gis_online@flathead.mt.gov</eMailAdd>
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<cntHours>8:00 - 5:00 Monday - Friday</cntHours>
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<pubDate>2005-01-01</pubDate>
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<idCredit>Credit given to Microsoft and Flathead County GIS would be appreciated when deriving products from this data.</idCredit>
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<rpIndName>Mindy Cochran</rpIndName>
<rpOrgName>Flathead County GIS</rpOrgName>
<rpPosName>Program Manager</rpPosName>
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<cntPhone>
<voiceNum>(406)758-5540</voiceNum>
<faxNum>(406)758-2139</faxNum>
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<delPoint>800 South Main Street Room 203</delPoint>
<city>Kalispell</city>
<adminArea>Montana</adminArea>
<postCode>59901</postCode>
<country>US</country>
<eMailAdd>gis_online@flathead.mt.gov</eMailAdd>
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<cntHours>8:00 am - 5:00 pm</cntHours>
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<resTitle>ISO 19115 Topic Category</resTitle>
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<keyword>Flathead County</keyword>
<keyword>Building</keyword>
<keyword>Footprints</keyword>
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<Consts>
<useLimit>&lt;DIV STYLE="text-align:Left;"&gt;&lt;DIV&gt;&lt;P&gt;&lt;SPAN&gt;Neither Flathead County, nor any of its employees, makes any warranty or guarantee to this data and assumes no legal responsibility for the information. Information is derived from multiple sources, subject to constant change, and may be of questionable accuracy, currency and completeness. Data is provided for informational purposes only. Primary information sources should be consulted for verification of data. Deriving conclusions from this data is done at the user’s risk. This data does not necessarily meet mapping, surveying, or engineering standards and is not intended for design purposes. User should use caution when overlaying other datasets as it may not display correctly with other layers.&lt;/SPAN&gt;&lt;/P&gt;&lt;/DIV&gt;&lt;/DIV&gt;</useLimit>
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<idPurp>This data represents computer generated building footprints and was originally provided by Microsoft in a GeoJSON format. Flathead County GIS used QGIS to export the data as a feature class, reproject the data, and clip it to Flathead County. The 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. However, we (Flathead County) believes ~2011 era imagery was used in our region. We intended to go through Department of Revenue data to look for builds after that data and update manually - this work is ongoing.
</idPurp>
<idAbs>&lt;DIV STYLE="text-align:Left;"&gt;&lt;DIV&gt;&lt;P&gt;&lt;SPAN&gt;Microsoft says the building extraction was done in two stages:&lt;/SPAN&gt;&lt;SPAN&gt;1.Semantic Segmentation – Recognizing building pixels on the aerial image using DNNs&lt;/SPAN&gt;&lt;SPAN&gt;2.Polygonization – Converting building pixel blobs into polygons&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;We 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:&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;1.The building edge must be of at least some length, both relative and absolute, e.g. 3 meters&lt;/SPAN&gt;&lt;SPAN&gt;2.Consecutive edge angles are likely to be 90 degrees&lt;/SPAN&gt;&lt;SPAN&gt;3.Consecutive angles cannot be very sharp, smaller by some auto-tuned threshold, e.g. 30 degrees&lt;/SPAN&gt;&lt;SPAN&gt;4.Building angles likely have very few dominant angles, meaning all building edges are forming angle of (dominant angle ± nπ/2)&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;In near future, we will be looking to deduce this automatically from existing building information. &lt;/SPAN&gt;&lt;SPAN&gt;We track various metrics to measure the quality of the output. Estimated building matching metrics:&lt;/SPAN&gt;&lt;SPAN&gt;Precision 99.3% &lt;/SPAN&gt;&lt;SPAN&gt;Recall 93.5% &lt;/SPAN&gt;&lt;SPAN&gt;Our metrics show that in the vast majority of cases the quality is at least as good as data hand digitized buildings in OpenStreetMap. It is not perfect, particularly in dense urban areas but it is still awesome.&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN /&gt;&lt;/P&gt;&lt;/DIV&gt;&lt;/DIV&gt;</idAbs>
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