<?xml version="1.0" encoding="UTF-8"?><metadata xml:lang="en">
<Esri>
<CreaDate>20180212</CreaDate>
<CreaTime>10541000</CreaTime>
<ArcGISFormat>1.0</ArcGISFormat>
<ArcGISstyle>ISO 19139 Metadata Implementation Specification</ArcGISstyle>
<SyncOnce>FALSE</SyncOnce>
<DataProperties>
<itemProps>
<itemName Sync="FALSE">ImperviousSurfacePly_2017</itemName>
<nativeExtBox>
<westBL Sync="TRUE">389808.289000</westBL>
<eastBL Sync="TRUE">407854.039000</eastBL>
<southBL Sync="TRUE">124954.519000</southBL>
<northBL Sync="TRUE">147521.056000</northBL>
<exTypeCode Sync="TRUE">1</exTypeCode>
</nativeExtBox>
<imsContentType export="False">002</imsContentType>
</itemProps>
<coordRef>
<type Sync="TRUE">Projected</type>
<geogcsn Sync="TRUE">GCS_North_American_1983</geogcsn>
<csUnits Sync="TRUE">Linear Unit: Meter (1.000000)</csUnits>
<projcsn Sync="TRUE">NAD_1983_StatePlane_Maryland_FIPS_1900</projcsn>
<peXml Sync="TRUE">&lt;ProjectedCoordinateSystem xsi:type='typens:ProjectedCoordinateSystem' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.0.0'&gt;&lt;WKT&gt;PROJCS[&amp;quot;NAD_1983_StatePlane_Maryland_FIPS_1900&amp;quot;,GEOGCS[&amp;quot;GCS_North_American_1983&amp;quot;,DATUM[&amp;quot;D_North_American_1983&amp;quot;,SPHEROID[&amp;quot;GRS_1980&amp;quot;,6378137.0,298.257222101]],PRIMEM[&amp;quot;Greenwich&amp;quot;,0.0],UNIT[&amp;quot;Degree&amp;quot;,0.0174532925199433]],PROJECTION[&amp;quot;Lambert_Conformal_Conic&amp;quot;],PARAMETER[&amp;quot;False_Easting&amp;quot;,400000.0],PARAMETER[&amp;quot;False_Northing&amp;quot;,0.0],PARAMETER[&amp;quot;Central_Meridian&amp;quot;,-77.0],PARAMETER[&amp;quot;Standard_Parallel_1&amp;quot;,38.3],PARAMETER[&amp;quot;Standard_Parallel_2&amp;quot;,39.45],PARAMETER[&amp;quot;Latitude_Of_Origin&amp;quot;,37.66666666666666],UNIT[&amp;quot;Meter&amp;quot;,1.0],AUTHORITY[&amp;quot;EPSG&amp;quot;,26985]]&lt;/WKT&gt;&lt;XOrigin&gt;-36747100&lt;/XOrigin&gt;&lt;YOrigin&gt;-29091500&lt;/YOrigin&gt;&lt;XYScale&gt;1000&lt;/XYScale&gt;&lt;ZOrigin&gt;0&lt;/ZOrigin&gt;&lt;ZScale&gt;1&lt;/ZScale&gt;&lt;MOrigin&gt;0&lt;/MOrigin&gt;&lt;MScale&gt;1&lt;/MScale&gt;&lt;XYTolerance&gt;0.002&lt;/XYTolerance&gt;&lt;ZTolerance&gt;0.001&lt;/ZTolerance&gt;&lt;MTolerance&gt;0.001&lt;/MTolerance&gt;&lt;HighPrecision&gt;true&lt;/HighPrecision&gt;&lt;WKID&gt;26985&lt;/WKID&gt;&lt;LatestWKID&gt;26985&lt;/LatestWKID&gt;&lt;/ProjectedCoordinateSystem&gt;</peXml>
</coordRef>
</DataProperties>
<SyncDate>20230928</SyncDate>
<SyncTime>14311100</SyncTime>
<ModDate>20230928</ModDate>
<ModTime>14320300</ModTime>
<ArcGISProfile>FGDC</ArcGISProfile>
<scaleRange>
<maxScale>5000</maxScale>
<minScale>150000000</minScale>
</scaleRange>
</Esri>
<mdLang>
<languageCode value="eng"/>
<countryCode Sync="TRUE" value="USA"/>
</mdLang>
<mdChar>
<CharSetCd value="004"/>
</mdChar>
<mdHrLv>
<ScopeCd value="005"/>
</mdHrLv>
<mdHrLvName Sync="TRUE">dataset</mdHrLvName>
<mdContact>
<editorSource>external</editorSource>
<editorDigest>3cf56e1fc8cc8205cbc5981374be7a2dd7af6e10</editorDigest>
<rpOrgName>Office of the Chief Technology Officer</rpOrgName>
<rpCntInfo>
<cntPhone>
<voiceNum tddtty="">(202) 727-2277</voiceNum>
</cntPhone>
<cntAddress addressType="both">
<delPoint>200 I Street SE</delPoint>
<city>Washington</city>
<adminArea>DC</adminArea>
<postCode>20003</postCode>
<country>US</country>
<eMailAdd>dcgis@dc.gov</eMailAdd>
</cntAddress>
<cntHours>8:30 am - 5 pm</cntHours>
</rpCntInfo>
<displayName>GIS Data Coordinator</displayName>
<rpPosName>GIS Data Coordinator</rpPosName>
<editorSave>True</editorSave>
<displayName>Office of the Chief Technology Officer</displayName>
<role>
<RoleCd value="011"/>
</role>
</mdContact>
<mdDateSt Sync="TRUE">20230928</mdDateSt>
<distInfo>
<distributor>
<distorOrdPrc>
<ordInstr>DC datasets can be downloaded from "http://opendata.dc.gov".</ordInstr>
</distorOrdPrc>
<distorCont>
<editorSource>external</editorSource>
<editorDigest>3cf56e1fc8cc8205cbc5981374be7a2dd7af6e10</editorDigest>
<rpOrgName>Office of the Chief Technology Officer</rpOrgName>
<rpCntInfo>
<cntPhone>
<voiceNum tddtty="">(202) 727-2277</voiceNum>
</cntPhone>
<cntAddress addressType="both">
<delPoint>200 I Street SE</delPoint>
<city>Washington</city>
<adminArea>DC</adminArea>
<postCode>20003</postCode>
<country>US</country>
<eMailAdd>dcgis@dc.gov</eMailAdd>
</cntAddress>
<cntHours>8:30 am - 5 pm</cntHours>
</rpCntInfo>
<displayName>GIS Data Coordinator</displayName>
<rpPosName>GIS Data Coordinator</rpPosName>
<editorSave>True</editorSave>
<displayName>Office of the Chief Technology Officer</displayName>
<role>
<RoleCd value="005"/>
</role>
</distorCont>
</distributor>
<distFormat>
<formatName Sync="TRUE">Enterprise Geodatabase Feature Class</formatName>
</distFormat>
</distInfo>
<dataIdInfo>
<idCitation>
<resTitle>Impervious Surface 2017</resTitle>
<date>
<createDate>2017-10-01T00:00:00</createDate>
<pubDate>2017-10-01T00:00:00</pubDate>
</date>
<presForm>
<PresFormCd value="005"/>
</presForm>
<citRespParty>
<editorSource>external</editorSource>
<editorDigest>3cf56e1fc8cc8205cbc5981374be7a2dd7af6e10</editorDigest>
<rpOrgName>Office of the Chief Technology Officer</rpOrgName>
<rpCntInfo>
<cntPhone>
<voiceNum tddtty="">(202) 727-2277</voiceNum>
</cntPhone>
<cntAddress addressType="both">
<delPoint>200 I Street SE</delPoint>
<city>Washington</city>
<adminArea>DC</adminArea>
<postCode>20003</postCode>
<country>US</country>
<eMailAdd>dcgis@dc.gov</eMailAdd>
</cntAddress>
<cntHours>8:30 am - 5 pm</cntHours>
</rpCntInfo>
<displayName>GIS Data Coordinator</displayName>
<rpPosName>GIS Data Coordinator</rpPosName>
<editorSave>True</editorSave>
<displayName>Office of the Chief Technology Officer</displayName>
<role>
<RoleCd value="006"/>
</role>
</citRespParty>
</idCitation>
<idAbs>&lt;DIV STYLE="text-align:Left;"&gt;&lt;DIV&gt;&lt;DIV&gt;&lt;P&gt;&lt;SPAN&gt;The dataset contains basemap features that are typically classified as impervious surface, captured in 2017. Some examples of Impervious Surfaces include: Airport Taxiways, Helipads, Outdoor Building Stairs, Buildings, Sidewalks, Roads, Alleys, Driveways, and Swimming Pools.&lt;/SPAN&gt;&lt;/P&gt;&lt;/DIV&gt;&lt;/DIV&gt;&lt;/DIV&gt;</idAbs>
<idPurp>The dataset contains basemap features that are typically classified as impervious surface captured in 2017.</idPurp>
<idCredit>Office of the Chief of Technology Officer</idCredit>
<dataLang>
<languageCode value="eng"/>
<countryCode Sync="TRUE" value="USA"/>
</dataLang>
<dataChar>
<CharSetCd value="004"/>
</dataChar>
<idStatus>
<ProgCd value="001"/>
</idStatus>
<spatRpType>
<SpatRepTypCd value="001"/>
</spatRpType>
<searchKeys>
<keyword>impervious surface</keyword>
<keyword>stormwater</keyword>
<keyword>octo</keyword>
<keyword>washington dc</keyword>
<keyword>district of columbia</keyword>
<keyword>water</keyword>
</searchKeys>
<themeKeys>
<keyword>Environment, Flood, Runoff, Impervious, Hydrography</keyword>
</themeKeys>
<placeKeys>
<keyword>washington dc</keyword>
<keyword>district of columbia</keyword>
<keyword>dc</keyword>
</placeKeys>
<dataExt>
<tempEle>
<TempExtent>
<exTemp>
<TM_Instant>
<tmPosition>2017-03-08T00:00:00</tmPosition>
</TM_Instant>
</exTemp>
</TempExtent>
</tempEle>
<exDesc>ground condition</exDesc>
</dataExt>
<resMaint>
<maintFreq>
<MaintFreqCd value="007"/>
</maintFreq>
</resMaint>
<resConst>
<Consts>
<useLimit>&lt;DIV STYLE="text-align:Left;"&gt;&lt;DIV&gt;&lt;DIV&gt;&lt;P&gt;&lt;SPAN&gt;This work is licensed under a &lt;/SPAN&gt;&lt;A href="http://creativecommons.org/licenses/by/4.0/" STYLE="text-decoration:underline;"&gt;&lt;SPAN&gt;Creative Commons Attribution 4.0 International License&lt;/SPAN&gt;&lt;/A&gt;&lt;SPAN&gt;.&lt;/SPAN&gt;&lt;/P&gt;&lt;/DIV&gt;&lt;/DIV&gt;&lt;/DIV&gt;</useLimit>
</Consts>
</resConst>
<envirDesc Sync="FALSE">Esri ArcGIS 13.0.3.36057</envirDesc>
<dataExt>
<geoEle>
<GeoBndBox esriExtentType="search">
<exTypeCode Sync="TRUE">1</exTypeCode>
<westBL Sync="TRUE">-77.117650</westBL>
<eastBL Sync="TRUE">-76.909336</eastBL>
<northBL Sync="TRUE">38.995630</northBL>
<southBL Sync="TRUE">38.792283</southBL>
</GeoBndBox>
</geoEle>
<exDesc>Washington DC</exDesc>
</dataExt>
<idPoC>
<editorSource>external</editorSource>
<editorDigest>3cf56e1fc8cc8205cbc5981374be7a2dd7af6e10</editorDigest>
<rpOrgName>Office of the Chief Technology Officer</rpOrgName>
<rpCntInfo>
<cntPhone>
<voiceNum tddtty="">(202) 727-2277</voiceNum>
</cntPhone>
<cntAddress addressType="both">
<delPoint>200 I Street SE</delPoint>
<city>Washington</city>
<adminArea>DC</adminArea>
<postCode>20003</postCode>
<country>US</country>
<eMailAdd>dcgis@dc.gov</eMailAdd>
</cntAddress>
<cntHours>8:30 am - 5 pm</cntHours>
</rpCntInfo>
<displayName>GIS Data Coordinator</displayName>
<rpPosName>GIS Data Coordinator</rpPosName>
<editorSave>True</editorSave>
<displayName>Office of the Chief Technology Officer</displayName>
<role>
<RoleCd value="006"/>
</role>
</idPoC>
<tpCat>
<TopicCatCd value="009"/>
</tpCat>
<tpCat>
<TopicCatCd value="007"/>
</tpCat>
</dataIdInfo>
<mdMaint>
<maintFreq>
<MaintFreqCd value="009"/>
</maintFreq>
</mdMaint>
<dqInfo>
<dqScope>
<scpLvl>
<ScopeCd value="005"/>
</scpLvl>
</dqScope>
<dataLineage>
<prcStep>
<stepDesc>This process describes 2017 updates to planimetric data originally captured in 2015.
The planimetric dataset provided by DC OCTO on 5/22/2017 was used as the base dataset for update by Fugro. Following the Aerotriangulation of the imagery, stereo images were generated for the planimetric compilation to allow for full view of features that could be obscured by building lean in a 2D environment. Relative and absolute orientation for the stereo images will be achieved by importing the orientation parameters from the AT results.
The planimetrics were collected using MicroStation and KLT Atlas software packages and combined for final QC in ArcGIS in the final geodatabase format. Prior to the initiation of compilation, a data capture matrix was established based on the data dictionary and compilation guidelines provided by DC OCTO. Requirements for the 2017 planimetric collect included the addition of a feature class for features associated with airports called AirPly, crosswalks as a new feature to the sidewalk layer, and a complete recollection of data in areas around the White House and Capitol that was compiled in 2013 but not captured in the 2015 collect. Topology checks were run using the OCTO provided rule set. When running topology, flags were identified on the existing 2015 dataset and this topology check was submitted with the updated 2017 collect. Additionally, the inclusion of crosswalks in the sidewalk feature class has created flags in the topology due to overlapping with roads. A separate geodatabase was generated to run the topology check (DC_Planimetrics2017_TopologyChks.gdb) and temporary sets of all feature classes with deleted data were generated. The deleted data was removed in the temporary feature classes to reduce the number of false errors that had to be reviewed. Due to the large number of exceptions in the 2015 data for curbs that were not covered by roads, the 2015 exceptions were identified and excluded from the current review. This working topology dataset was used as a guide to make corrections to the final deliverable dataset (DC_Planimetrics2017.gdb). Both the working topology geodatabase and the final deliverable geodatabase were submitted to DC.</stepDesc>
<stepProc>
<rpOrgName>Fugro Geospatial, Inc.</rpOrgName>
<role>
<RoleCd value="009"/>
</role>
<rpCntInfo>
<cntAddress addressType="both">
<eMailAdd>metadata@earthdata.com</eMailAdd>
<delPoint>7320 Executive Way</delPoint>
<city>Frederick</city>
<adminArea>MD</adminArea>
<postCode>21704</postCode>
<country>US</country>
</cntAddress>
<cntPhone>
<voiceNum tddtty="">(301)948-8550</voiceNum>
<faxNum>(301)963-2064</faxNum>
</cntPhone>
</rpCntInfo>
<displayName>EarthData International, Inc</displayName>
</stepProc>
</prcStep>
<prcStep>
<stepDesc>All planimetric data within the scope of the 2015 project was newly collected by Sanborn using DAT/EM Summit Evolution digital photogrammetric workstations, with the exception of StreetCenterlineLn_2015 (street centerlines) and GeoControlPt_2015 (ground control.) The photogrammetric supervisor established the data collection conventions to be used for data capture, including the data schema, global origin and working units to be used for data collection. The vendor assigned collection areas to stereo-compilation technicians based on OCTO’s orthophoto tile layout. They collected and saved planimetric data to the designated network subdirectory.
After the data for the tile was collected, the technician visually reviewed the planimetric information for completeness and accuracy. The data was then passed on to GIS staff.
GIS staff performed a preliminary review of the planimetric data. Omissions or errors that were found were communicated to stereo-compilation staff, who then updated the corresponding stereo-compilation file. The corrected data was then passed on to GIS staff.
GIS staff then merged all data per delivery block. Polyline features that were required by OCTO not to have pseudo nodes were dissolved. Following the dissolve, all point and polyline features were appended to a template geodatabase in their respective feature classes and attributed as defined in OCTO’s Data Dictionary.
Polylines that participated in building polygons were placed into a working dataset, and topology built to locate gaps in the lines where polygons would not properly build. A technician closed those gaps. Then, polygons were built from these polylines in a working feature class. Based on centroids collected during the stereo-compilation process, polygons were then assigned their appropriate feature code based on OCTO’s Data Dictionary. Once all polygons were assigned their feature codes based on their corresponding centroid codes, the polygons remaining were then checked against the 2015 orthophoto imagery. Any unclassified polygons that were erroneously not given a feature code (because the stereo-compiler omitted a centroid that was not caught in a previous review) were then coded with the proper feature code. Also, at this point an additional review for proper code was performed, and incorrect codes changed to correct codes. Then, all remaining un-coded polygons were removed from the working polygon feature class.
Polygons for each feature class were selected from the working feature class and appended to their appropriate feature classes based on OCTO’s Data Dictionary specifications.
Once all features were put into their proper location in the geodatabase and attribution populated, a topology was established to locate geometry errors. GIS technicians corrected errors then removed the topology from the geodatabase. The geodatabase was then compacted.
There are two isolated pockets of data that were not collected by Sanborn in the 2015 project, which are located around the White House and Capitol. Much of these two pockets have no 2015 stereo-photo coverage because the flying height required to collect imagery suitable for 3” pixel resolution orthophotos was too low relative to the no-fly zones over these areas. To avoid splitting a large number of planimetric features between differing imagery dates, the stereo-imagery voids were generally expanded to the center of the closest street (coincident with street centerlines where possible) to produce the final void areas. Inside these voids in the 2015 data, OCTO’s existing planimetrics (updated in 2013) were appended to the 2015 data for all feature classes except BarrierLn and CurbLn.</stepDesc>
<stepDateTm>2016-03-28T00:00:00</stepDateTm>
<stepProc>
<rpOrgName>EarthData International, Inc</rpOrgName>
<role>
<RoleCd value="009"/>
</role>
<rpCntInfo>
<cntAddress addressType="both">
<eMailAdd>metadata@earthdata.com</eMailAdd>
<delPoint>7320 Executive Way</delPoint>
<city>Frederick</city>
<adminArea>MD</adminArea>
<postCode>21704</postCode>
<country>US</country>
</cntAddress>
<cntPhone>
<voiceNum tddtty="">(301)948-8550</voiceNum>
<faxNum>(301)963-2064</faxNum>
</cntPhone>
</rpCntInfo>
</stepProc>
<stepSrc type="used">
<srcDesc>Sanborn has successfully completed the aerial triangulation (AT) task for the aerial photography acquired April 1st through April 24th, 2015 for the DC OCTO project.
Using fully analytical aerial triangulation (FAAT) methods incorporating automatic analytical aerial triangulation (AAAT) procedures, Sanborn determined ground coordinates for each exposure by flying at an average altitude of 1100m AMSL covering the project area.
The results of the final adjustment are sufficient to enable Sanborn to produce orthophoto imagery and planimetric stereo collected data that meets project accuracy requirements (ASPRS Class 1 for 1”=100‟ mapping; RMSE 30cm).</srcDesc>
</stepSrc>
</prcStep>
</dataLineage>
<report dimension="" type="DQConcConsis">
<measDesc>This report describes data originally captured in 2015. OCTO developed and operated a QA/QC program to check the deliverables. Generally, the program consists of various types of processes grouped into visual checks, automated procedures, edge-matching routines, specialized checks, and field verification. Through the application of these processes, the data's spatial and attribute accuracy, usability, data documentation adherence, and specialized characteristics are checked. Staff identified issues in a shapfile with appropriate descriptions for the vendor to fix. The data was delivered in preliminary format for a thorough review and identification of issues. The vendor fixed the data and delivered final data which OCTO checked to ensure the vendor made the fixes appropriately.</measDesc>
</report>
<report dimension="" type="DQCompOm">
<measDesc>Geometry Capture Rules:
Airport/Heliport Perimeter: Delineate the full perimeter of the airport or heliport.
Helipad: Delineate clearly marked hard surface landing area or platform for helicopters
Basketball Court: Capture full outline of the court Tennis Court: Capture full outline of the court
Baseball Field: Capture infield and outfield of a baseball area as one polygon if easily defined in aerial photo. Otherwise capture infield as the baseball field.
Football Field: Capture full outline of the field as best defined in aerial photo
Soccer Field: Capture full outline of the field as best defined in aerial photo
Track: Capture outline of track. Any recreation fields within tracks will be captured and coded separately.
Other Recreation Area: For areas that cannot be easily defined by function, capture as other recreation area. Capture full outline of the field as best defined in aerial photo.
Road: A generally named thoroughfare, that is usually paved and can be public or private. Unimproved thoroughfares are excluded. Capture the perimeter of roads and ramps, exclusive of median strips and traffic islands. Road polygons are formed by a combination of road edge, curb, sidewalk, street intersection closure line and map sheet edge.
Paved Median Island: Perimeter of non-traffic paved areas that separate traffic lanes in opposing directions.
Paved Traffic Island: Perimeter of non-traffic concrete areas in the middle of streets designed to segregate traffic flow. This does not include linear barriers, e.g., Jersey barriers, walls or guardrails, or point barriers, such as impact attenuators. Features will not overlap sidewalks. Major traffic circles will not be coded as traffic circles.
Alley: Perimeter of alleys first plotted photogrammetrically from other indicators such as building footprints, fence lines, curb lines, walls, paved or unpaved drives, and map sheet edge. Alley polygons are closed along the lines where they intersect with road polygons.
Paved Drive: A paved driveway for a building or entranceway for a parking lot. Delineate the perimeter of all driveways greater than 200 feet throughout the City and smaller driveways within the Monumental Core only. Driveways are neither streets nor alleys, but provide access to public facilities, such as a drive to a monument, museum, hotel, large estate, sports field or golf course, grounds of the U.S. Capital, etc. Do not capture private driveways that are less than
200 feet in length. If the driveway is less than 200 feet and leads to a parking lot, the entire paved area will be captured as Parking Lot. Driveways will be photogrammetrically compiled as polygons and not compiled from individual vectors on different levels.
Parking Lot: Generally paved surfaces used for cars to park on. Paved drives usually form entrances to these features, if the drive is more than 200 feet. If the driveway is less than 200 feet leading into the parking lot, the entire paved area will be captured as Parking Lot. Delineate the outline of the parking lot. The curb need not be distinguished. Parking lots sharing a common boundary with linear features must have the common segment captured once, but coded as both polygon and line. Distinguish paved from unpaved. Small parking areas, where individuals park their cars in the middle of a block off a public alley, will not be captured as parking lots. These are either public space (e.g., alleys) or private space where owners permit parking to occur.
Intersection: A location where more than one road comes together. Intersections will be captured in an opened fashion if the intersection is in a traffic circle. For standard cross streets, intersection polygons are bounded by curbs and four closure lines at street intersection crosswalks (outer line) or placed arbitrarily where crosswalks could logically be placed. For "T" intersections, the polygons are bounded by curbs and three such closure lines. Complex intersections could have more closure lines. Entire traffic circles will be coded as intersections.
Building: Delineate around roof line showing the building "footprint." Roof breaks and rooflines, such as between individual residences in row houses or separate spaces in office structures, will be captured to partition building footprints. This includes capturing all sheds, garages, or other non-addressable buildings over 100 square feet throughout the City. Atriums, courtyards, and other “holes” in buildings created as part of demarcating the building outline will not be part of the building capture. This includes construction trailers greater than 100 square feet.
As a guide, use the ownerply lot lines to assist in delineating roof breaks for those buildings where visual indentification is difficult. This layer should be relied on heavily outside the downtown areas to capture roofbreaks. Within the downtown area, ownerply will serve as a guide for areas where roofbreak delineation is not clear. Aerial photography will be used as the primary source.
Memorials: Delineate around roof line showing the building "footprint." A list of memorials will be provided for capture and coding. DC GIS will provide a list of memorials to use as the source.
Bleachers: Delineate around the base of connected sets of bleachers.
Parking Garage: Capture this multi-story structure for parking as a parking garage. Delineate the perimeter of the parking garage including ramps. Parking garages sharing a common boundary with linear features must have the common segment captured once. A parking garage will only be attributes as such if there is rooftop parking. Not all rooftop parking is a parking garage, however. There are structures that only have rooftop parking but serve as a business. Those should be captured as buildings.
Pools: Capture the outline of the water portion of fountains and code as pools. This includes US Capitol and Reflecting Pool.
Fountains: Delineate around the base of fountain structures.
Sidewalk: Sidewalks either compiled photogrammetrically as polygons or derived from a combination of vectors including: curbs, buildings, walls, driveways, or other features. Any stair feature that is less than 5 stairs will be coded as sidewalk to maintain continuity.
Stairs: Groups of 5 or more stairs outside of major buildings or monuments, as well as part of sidewalks, shall be captured, Individual stairs will not be captured; capture all stairs for in one polygon. Do not capture stairs for minor buildings, including individual homes. Fire cases will not be included. If landings exist within the stairs, it will be captured as sidewalk, not stairs.
The perimeter of public and private swimming pools will be captured, for both above ground and in ground pools. No other features can make a side for this feature. Pools will not overlap any other feature class. Pool decks and pavement around pools will not be captured as a pool. Pavement around pools is captured as sidewalk. Roof top pools will not be captured. Legacy data in areas without change will not be updated.</measDesc>
</report>
<report dimension="" type="DQTopConsis">
<measDesc>This report describes 2017 updates to planimetric data originally captured in 2015. Topology checks were run using the OCTO provided rule set. When running topology, flags were identified on the existing 2015 dataset and this topology check was submitted with the updated 2017 collect. Additionally, the inclusion of crosswalks in the sidewalk feature class has created flags in the topology due to overlapping with roads. A separate geodatabase was generated to run the topology check and temporary sets of all feature classes with deleted data were generated. The deleted data was removed in the temporary feature classes to reduce the number of false errors that had to be reviewed. Due to the large number of exceptions in the 2015 data for curbs that were not covered by roads, the 2015 exceptions were identified and excluded from the current review. This working topology dataset was used as a guide to make corrections to the final deliverable dataset.</measDesc>
<evalMethDesc>The following topological rules were used:
Must Be Larger Than Cluster Tolerance BldgPly Must Not Overlap ObsAreaPly Must Not Overlap RecareaPly Must Not Overlap SwmPoolPly Must Not Overlap WaterPly Must Not Overlap RoadPly Must Not Overlap SidewalkPly Must Not Overlap BrgTunPly Must Not Overlap BldgPly Must Not Overlap With RoadPly
RoadPly Must Not Overlap With SidewalkPly
SwmPoolPly Must Not Overlap With WaterPly
RecareaPly Must Not Overlap With WaterPly
RecareaPly Must Not Overlap With RoadPly
RecareaPly Must Not Overlap With SwmPoolPly
BrgTunPly Must Not Overlap With SwmPoolPly
BrgTunPly Must Not Overlap With RecareaPly
SidewalkPly Must Not Overlap With SwmPoolPly
SidewalkPly Must Not Overlap With RecareaPly
BldgPly Must Not Overlap With BrgTunPly
BldgPly Must Not Overlap With SwmPoolPly
BldgPly Must Not Overlap With RecareaPly
BldgPly Must Not Overlap With SidewalkPly
BrgTunPly Must Not Overlap With RoadPly
CurbLn Must Be Covered By Boundary Of RoadPly
HydroLn Must Not Have Pseudo Nodes RailRdLn Must Not Have Pseudo Nodes StreetCenterlineLn Must Not Have Pseudo Nodes CurbLn Must Not Have Pseudo Nodes BarrierLn Must Not Have Pseudo Nodes GeoControlPt Must Be Disjoint GratePt Must Be Disjoint BarrierLn Must Not Self-Overlap StreetCenterlineLn Must Not Self-Overlap RailRdLn Must Not Self-Overlap HydroLn Must Not Self-Overlap CurbLn Must Not Self-Overlap BarrierLn Must Not Self-Intersect CurbLn Must Not Self-Intersect HydroLn Must Not Self-Intersect RailRdLn Must Not Self-Intersect StreetCenterlineLn Must Not Self-Intersect CurbLn Must Not Intersect Or Touch Interior StreetCenterlineLn Must Not Intersect Or Touch Interior HydroLn Must Not Intersect Or Touch Interior BarrierLn Must Not Intersect Or Touch Interior RailRdLn Must Not Intersect Or Touch Interior </evalMethDesc>
</report>
</dqInfo>
<spatRepInfo>
<VectSpatRep>
<geometObjs Name="ImperviousSurfacePly_2017">
<geoObjTyp>
<GeoObjTypCd Sync="TRUE" value="002"/>
</geoObjTyp>
<geoObjCnt Sync="TRUE">245723</geoObjCnt>
</geometObjs>
<topLvl>
<TopoLevCd Sync="TRUE" value="001"/>
</topLvl>
</VectSpatRep>
</spatRepInfo>
<refSysInfo>
<RefSystem>
<refSysID>
<identCode code="26985"/>
<idCodeSpace Sync="TRUE">EPSG</idCodeSpace>
<idVersion Sync="TRUE">4.5(3.0.1)</idVersion>
</refSysID>
</RefSystem>
</refSysInfo>
<eainfo>
<detailed Name="ImperviousSurfacePly_2017">
<enttyp>
<enttypl Sync="FALSE">ImperviousSurfacePly_2017</enttypl>
<enttypt Sync="TRUE">Feature Class</enttypt>
<enttypc Sync="TRUE">245723</enttypc>
</enttyp>
<attr>
<attrlabl>OBJECTID</attrlabl>
<attalias Sync="TRUE">OBJECTID</attalias>
<attrdef>Internal feature number.</attrdef>
<attrdefs>ESRI</attrdefs>
<attrtype Sync="TRUE">OID</attrtype>
<attwidth Sync="TRUE">4</attwidth>
<atprecis Sync="TRUE">10</atprecis>
<attscale Sync="TRUE">0</attscale>
<attrdomv>
<udom>Sequential unique whole numbers that are automatically generated.</udom>
</attrdomv>
</attr>
<attr>
<attrlabl>SHAPE</attrlabl>
<attalias Sync="TRUE">SHAPE</attalias>
<attrdef>Feature geometry.</attrdef>
<attrdefs>ESRI</attrdefs>
<attrtype Sync="TRUE">Geometry</attrtype>
<attwidth Sync="TRUE">4</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
<attrdomv>
<udom>Coordinates defining the features.</udom>
</attrdomv>
</attr>
<attr>
<attrlabl>GIS_ID</attrlabl>
<attalias Sync="TRUE">GIS_ID</attalias>
<attrdef>OCTO GIS sequential identifier</attrdef>
<attrtype Sync="TRUE">String</attrtype>
<attwidth Sync="TRUE">50</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
<attrdefs>OCTO</attrdefs>
</attr>
<attr>
<attrlabl>FEATURECODE</attrlabl>
<attalias Sync="TRUE">FEATURECODE</attalias>
<attrdef>Feature Code</attrdef>
<attrtype Sync="TRUE">SmallInteger</attrtype>
<attwidth Sync="TRUE">2</attwidth>
<atprecis Sync="TRUE">5</atprecis>
<attscale Sync="TRUE">0</attscale>
<attrdefs>OCTO</attrdefs>
</attr>
<attr>
<attrlabl>DESCRIPTION</attrlabl>
<attalias Sync="TRUE">DESCRIPTION</attalias>
<attrdef>Description of feature code</attrdef>
<attrtype Sync="TRUE">String</attrtype>
<attwidth Sync="TRUE">50</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
<attrdefs>OCTO</attrdefs>
</attr>
<attr>
<attrlabl>CAPTUREYEAR</attrlabl>
<attalias Sync="TRUE">CAPTUREDATE</attalias>
<attrdef>Capture Date</attrdef>
<attrtype Sync="TRUE">Date</attrtype>
<attwidth Sync="TRUE">36</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
<attrdefs>OCTO</attrdefs>
</attr>
<attr>
<attrlabl>CAPTUREACTION</attrlabl>
<attalias Sync="TRUE">CAPTUREACTION</attalias>
<attrdef>Type of edit performed on the feature</attrdef>
<attrtype Sync="TRUE">String</attrtype>
<attwidth Sync="TRUE">1</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
<attrdefs>OCTO</attrdefs>
</attr>
<attr>
<attrlabl Sync="TRUE">SOURCE</attrlabl>
<attalias Sync="TRUE">SOURCE</attalias>
<attrtype Sync="TRUE">String</attrtype>
<attwidth Sync="TRUE">70</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">SE_ANNO_CAD_DATA</attrlabl>
<attalias Sync="TRUE">SE_ANNO_CAD_DATA</attalias>
<attrtype Sync="TRUE">Blob</attrtype>
<attwidth Sync="TRUE">0</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">GLOBALID</attrlabl>
<attalias Sync="TRUE">GLOBALID</attalias>
<attrtype Sync="TRUE">GlobalID</attrtype>
<attwidth Sync="TRUE">38</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">CREATOR</attrlabl>
<attalias Sync="TRUE">CREATOR</attalias>
<attrtype Sync="TRUE">String</attrtype>
<attwidth Sync="TRUE">255</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">CREATED</attrlabl>
<attalias Sync="TRUE">CREATED</attalias>
<attrtype Sync="TRUE">Date</attrtype>
<attwidth Sync="TRUE">36</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">EDITOR</attrlabl>
<attalias Sync="TRUE">EDITOR</attalias>
<attrtype Sync="TRUE">String</attrtype>
<attwidth Sync="TRUE">255</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">EDITED</attrlabl>
<attalias Sync="TRUE">EDITED</attalias>
<attrtype Sync="TRUE">Date</attrtype>
<attwidth Sync="TRUE">36</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">SHAPE.AREA</attrlabl>
<attalias Sync="TRUE">SHAPE.AREA</attalias>
<attrtype Sync="TRUE">Double</attrtype>
<attwidth Sync="TRUE">0</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">SHAPE.LEN</attrlabl>
<attalias Sync="TRUE">SHAPE.LEN</attalias>
<attrtype Sync="TRUE">Double</attrtype>
<attwidth Sync="TRUE">0</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
</detailed>
</eainfo>
<spdoinfo>
<ptvctinf>
<esriterm Name="ImperviousSurfacePly_2017">
<efeatyp Sync="TRUE">Simple</efeatyp>
<efeageom Sync="TRUE" code="4"/>
<esritopo Sync="TRUE">FALSE</esritopo>
<efeacnt Sync="TRUE">245723</efeacnt>
<spindex Sync="TRUE">TRUE</spindex>
<linrefer Sync="TRUE">FALSE</linrefer>
</esriterm>
</ptvctinf>
</spdoinfo>
<Binary>
<Thumbnail>
<Data EsriPropertyType="PictureX">/9j/4AAQSkZJRgABAQEBLAEsAAD/2wBDAAMCAgMCAgMDAwMEAwMEBQgFBQQEBQoHBwYIDAoMDAsK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</Data>
</Thumbnail>
</Binary>
</metadata>
