<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<metadata xml:lang="en">
<Esri>
<CreaDate>20261007</CreaDate>
<CreaTime>23492700</CreaTime>
<ArcGISFormat>1.0</ArcGISFormat>
<SyncOnce>FALSE</SyncOnce>
<DataProperties>
<itemProps>
<itemName Sync="FALSE">village_boundary</itemName>
<imsContentType Sync="TRUE">002</imsContentType>
<itemSize Sync="TRUE">0.000</itemSize>
</itemProps>
<coordRef>
<type Sync="TRUE">Projected</type>
<geogcsn Sync="TRUE">GCS_ITRF_2005</geogcsn>
<csUnits Sync="TRUE">Linear Unit: Meter (1.000000)</csUnits>
<projcsn Sync="TRUE">ITRF_2005</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/3.6.0'&gt;&lt;WKT&gt;PROJCS[&amp;quot;ITRF_2005&amp;quot;,GEOGCS[&amp;quot;GCS_ITRF_2005&amp;quot;,DATUM[&amp;quot;D_ITRF_2005&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;Transverse_Mercator&amp;quot;],PARAMETER[&amp;quot;False_Easting&amp;quot;,500000.0],PARAMETER[&amp;quot;False_Northing&amp;quot;,5000000.0],PARAMETER[&amp;quot;Central_Meridian&amp;quot;,30.0],PARAMETER[&amp;quot;Scale_Factor&amp;quot;,0.9999],PARAMETER[&amp;quot;Latitude_Of_Origin&amp;quot;,0.0],UNIT[&amp;quot;Meter&amp;quot;,1.0]]&lt;/WKT&gt;&lt;XOrigin&gt;-5122600&lt;/XOrigin&gt;&lt;YOrigin&gt;-5001100&lt;/YOrigin&gt;&lt;XYScale&gt;10000&lt;/XYScale&gt;&lt;ZOrigin&gt;-100000&lt;/ZOrigin&gt;&lt;ZScale&gt;10000&lt;/ZScale&gt;&lt;MOrigin&gt;-100000&lt;/MOrigin&gt;&lt;MScale&gt;10000&lt;/MScale&gt;&lt;XYTolerance&gt;0.001&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;/ProjectedCoordinateSystem&gt;</peXml>
</coordRef>
</DataProperties>
<SyncDate>20251126</SyncDate>
<SyncTime>12422200</SyncTime>
<ModDate>20251126</ModDate>
<ModTime>12422200</ModTime>
</Esri>
<dataIdInfo>
<envirDesc Sync="FALSE">Esri ArcGIS 13.6.0.59527</envirDesc>
<dataLang>
<languageCode Sync="TRUE" value="eng">
</languageCode>
<countryCode Sync="TRUE" value="RWA">
</countryCode>
</dataLang>
<idCitation>
<resTitle Sync="FALSE">village_boundary_2022</resTitle>
<presForm>
<PresFormCd Sync="TRUE" value="005">
</PresFormCd>
</presForm>
</idCitation>
<spatRpType>
<SpatRepTypCd Sync="TRUE" value="001">
</SpatRepTypCd>
</spatRpType>
<idAbs>&lt;div style='text-align:Left;'&gt;&lt;div&gt;&lt;p&gt;&lt;span&gt;During the Rwanda Base Map Review that started in December 2018 and completed in July 2020, data across public and private institutions were gathered and harmonized in a single National Geodatabase. This layer "Villages Boundaries", was created following the administrative entities reorganization that took place during the 2005 reform. The initial version of the Villages Boundaries was produced in 2006 and updated by the 2012 Census Mapping.&lt;/span&gt;&lt;/p&gt;&lt;/div&gt;&lt;/div&gt;</idAbs>
<searchKeys>
<keyword>administrative</keyword>
<keyword>villages</keyword>
<keyword>boundaries</keyword>
</searchKeys>
<idPurp>This layer is part of the National Geodatabase. It contains the Villages Boundaries for Rwanda, as established during the 2022 Household and Population Census of Rwanda. (NISR)</idPurp>
<idCredit>NISR, RLA</idCredit>
<resConst>
<Consts>
<useLimit>&lt;div style='text-align:Left;'&gt;&lt;div&gt;&lt;p&gt;&lt;span&gt;The work on the National Geodatabase is ongoing. Only Rwanda Land Authority (RLA) can confirm which version is the latest. This layer shall not be transferred to third party without RLA's permission.&lt;/span&gt;&lt;/p&gt;&lt;/div&gt;&lt;/div&gt;</useLimit>
</Consts>
</resConst>
</dataIdInfo>
<mdLang>
<languageCode Sync="TRUE" value="eng">
</languageCode>
<countryCode Sync="TRUE" value="RWA">
</countryCode>
</mdLang>
<distInfo>
<distFormat>
<formatName Sync="TRUE">Enterprise Geodatabase Feature Class</formatName>
</distFormat>
<distTranOps>
<transSize Sync="TRUE">0.000</transSize>
</distTranOps>
</distInfo>
<mdHrLv>
<ScopeCd Sync="TRUE" value="005">
</ScopeCd>
</mdHrLv>
<mdHrLvName Sync="TRUE">dataset</mdHrLvName>
<refSysInfo>
<RefSystem>
<refSysID>
<identCode Sync="TRUE" code="0">
</identCode>
</refSysID>
</RefSystem>
</refSysInfo>
<spatRepInfo>
<VectSpatRep>
<geometObjs Name="village_boundary">
<geoObjTyp>
<GeoObjTypCd Sync="TRUE" value="002">
</GeoObjTypCd>
</geoObjTyp>
<geoObjCnt Sync="TRUE">0</geoObjCnt>
</geometObjs>
<topLvl>
<TopoLevCd Sync="TRUE" value="001">
</TopoLevCd>
</topLvl>
</VectSpatRep>
</spatRepInfo>
<spdoinfo>
<ptvctinf>
<esriterm Name="village_boundary">
<efeatyp Sync="TRUE">Simple</efeatyp>
<efeageom Sync="TRUE" code="4">
</efeageom>
<esritopo Sync="TRUE">FALSE</esritopo>
<efeacnt Sync="TRUE">0</efeacnt>
<spindex Sync="TRUE">TRUE</spindex>
<linrefer Sync="TRUE">FALSE</linrefer>
</esriterm>
</ptvctinf>
</spdoinfo>
<eainfo>
<detailed Name="village_boundary">
<enttyp>
<enttypl Sync="FALSE">village_boundary</enttypl>
<enttypt Sync="TRUE">Feature Class</enttypt>
<enttypc Sync="TRUE">0</enttypc>
</enttyp>
<attr>
<attrlabl Sync="TRUE">objectid</attrlabl>
<attalias Sync="TRUE">objectid</attalias>
<attrtype Sync="TRUE">OID</attrtype>
<attwidth Sync="TRUE">4</attwidth>
<atprecis Sync="TRUE">10</atprecis>
<attscale Sync="TRUE">0</attscale>
<attrdef Sync="TRUE">Internal feature number.</attrdef>
<attrdefs Sync="TRUE">Esri</attrdefs>
<attrdomv>
<udom Sync="TRUE">Sequential unique whole numbers that are automatically generated.</udom>
</attrdomv>
</attr>
<attr>
<attrlabl Sync="TRUE">Shape</attrlabl>
<attalias Sync="TRUE">shape</attalias>
<attrtype Sync="TRUE">Geometry</attrtype>
<attwidth Sync="TRUE">8</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
<attrdef Sync="TRUE">Feature geometry.</attrdef>
<attrdefs Sync="TRUE">Esri</attrdefs>
<attrdomv>
<udom Sync="TRUE">Coordinates defining the features.</udom>
</attrdomv>
</attr>
<attr>
<attrlabl Sync="TRUE">province</attrlabl>
<attalias Sync="TRUE">province</attalias>
<attrtype Sync="TRUE">String</attrtype>
<attwidth Sync="TRUE">50</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">province_i</attrlabl>
<attalias Sync="TRUE">province_i</attalias>
<attrtype Sync="TRUE">String</attrtype>
<attwidth Sync="TRUE">1</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">district</attrlabl>
<attalias Sync="TRUE">district</attalias>
<attrtype Sync="TRUE">String</attrtype>
<attwidth Sync="TRUE">50</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">district_i</attrlabl>
<attalias Sync="TRUE">district_i</attalias>
<attrtype Sync="TRUE">String</attrtype>
<attwidth Sync="TRUE">2</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">sector</attrlabl>
<attalias Sync="TRUE">sector</attalias>
<attrtype Sync="TRUE">String</attrtype>
<attwidth Sync="TRUE">50</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">sector_id</attrlabl>
<attalias Sync="TRUE">sector_id</attalias>
<attrtype Sync="TRUE">String</attrtype>
<attwidth Sync="TRUE">4</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">cell</attrlabl>
<attalias Sync="TRUE">cell</attalias>
<attrtype Sync="TRUE">String</attrtype>
<attwidth Sync="TRUE">50</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">cell_id</attrlabl>
<attalias Sync="TRUE">cell_id</attalias>
<attrtype Sync="TRUE">String</attrtype>
<attwidth Sync="TRUE">6</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">village</attrlabl>
<attalias Sync="TRUE">village</attalias>
<attrtype Sync="TRUE">String</attrtype>
<attwidth Sync="TRUE">50</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">village_id</attrlabl>
<attalias Sync="TRUE">village_id</attalias>
<attrtype Sync="TRUE">String</attrtype>
<attwidth Sync="TRUE">8</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">st_area(shape)</attrlabl>
<attalias Sync="TRUE">st_area(shape)</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">st_length(shape)</attrlabl>
<attalias Sync="TRUE">st_length(shape)</attalias>
<attrtype Sync="TRUE">Double</attrtype>
<attwidth Sync="TRUE">0</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
</detailed>
</eainfo>
<mdDateSt Sync="TRUE">20251126</mdDateSt>
<Binary>
<Thumbnail>
<Data EsriPropertyType="PictureX">iVBORw0KGgoAAAANSUhEUgAAASwAAADICAYAAABS39xVAAAAAXNSR0IB2cksfwAAAAlwSFlzAAAO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</Data>
</Thumbnail>
</Binary>
</metadata>
