Description: <p><strong>Detailed Dataset Description</strong>: <br /></p>
<p>The impervious map was created using “expert systems” rulesets developed in Trimble Ecognition. These rulesets combine automated image segmentation with-object based image classification techniques. In contrast with machine learning approaches, expert systems rulesets are developed heuristically based on the knowledge of experienced image analysts. Key data sets used in the expert systems rulesets for impervious mapping included: orthophotography (2018), the lidar point cloud (2019), and Lidar derived rasters.</p>
<p>After it was produced using Trimble Ecognition, the preliminary impervious map product was manually edited by a team of UVM’s photo interpreters. Manual editing corrected errors where the automated methods produced incorrect results.</p>
<p>The impervious map has 5 classes, which are described below:</p>
<ul>
<li><strong>Building</strong> – Structures above 200 square feet in area. Structures fully occluded by vegetation will not be mapped.</li>
<li><strong>Paved Road</strong> – Roads that are paved and wide enough for a vehicle.</li>
<li><strong>Dirt/Gravel Road </strong>– Dirt or gravel roads wide enough for a vehicle. Non-ephemeral fire roads, ranch roads and long driveways. Polygons representing narrow unpaved (single track) trails are not included in this data product.</li>
<li><strong>Other Dirt/Gravel Surface</strong> – Dirt or gravel surfaces that are highly compacted and used by humans and equipment, such as parking lots, road pull-offs, some dirt or gravel paths, and highly compacted areas around commercial activities. This class DOES NOT include natural turf playing fields, very lightly used dirt roads, livestock areas, naturally occurring bare soil or rock, or bare areas around ponds.</li>
<li><strong>Other Paved Surface</strong> – <strong>I</strong>ncludes parking lots, sidewalks, paved walking paths, swimming pools, tennis courts.</li>
</ul>
<p>Miscellaneous quality control and processing notes:</p>
<ul>
<li>Zoom level used during manual quality control was no finer than 1 to 500.</li>
<li>Vector data was created with no overlapping polygons.</li>
</ul>
<p><strong>Data Limitations:</strong></p>
<p>This is not a planimetric data product and was created using semi-automated techniques. It provides a reasonable and useful depiction of impervious surfaces for planner and managers but does not have the accuracy or precision to support engineering.</p><p>Appropriate uses of the data product include:</p>
<ul>
<li>As an input to storm water models</li>
<li>For planners to assess % imperviousness in a parcel/watershed</li>
<li>To help identify areas of human infrastructure for fuels and fire management</li>
<li>As an input to fuel models that are used in fire behavior and fire spread models</li>
<li>For cartography and mapping</li>
<li>Generally for use at scales 1:1,000 and smaller</li>
</ul>Inappropriate uses of this product include:<br /><ul>
<li>Measuring exact square footage of structures or impervious features for building projects</li>
<li>Using the impervious as geographically precise information in transportation and public works</li>
</ul>
<p><strong>Minimum Mapping Units:</strong></p>
<p>The table below shows the nominal minimum mapping units (MMUs) for the impervious surfaces map.</p>
<table>
<tbody>
<tr>
<td>
<p><strong>Map Class</strong></p>
</td>
<td>
<p><strong>MMU</strong></p>
</td>
</tr>
<tr>
<td>
<p>Buildings</p>
</td>
<td>
<p>200 square feet</p>
</td>
</tr>
<tr>
<td>
<p>All Other Classes</p>
</td>
<td>
<p>400 square feet</p>
</td>
</tr>
</tbody>
</table>