<?xml version="1.0" encoding="UTF-8"?><metadata xml:lang="pt">
<Esri>
<CreaDate>20180205</CreaDate>
<CreaTime>13132500</CreaTime>
<ArcGISFormat>1.0</ArcGISFormat>
<SyncOnce>FALSE</SyncOnce>
<DataProperties>
<itemProps>
<itemName Sync="TRUE">of_1949_wg_ProjectRaster.tif</itemName>
<imsContentType Sync="TRUE">002</imsContentType>
<nativeExtBox>
<westBL Sync="TRUE">479088.861357</westBL>
<eastBL Sync="TRUE">488318.945769</eastBL>
<southBL Sync="TRUE">7417497.286183</southBL>
<northBL Sync="TRUE">7425527.923763</northBL>
<exTypeCode Sync="TRUE">1</exTypeCode>
</nativeExtBox>
</itemProps>
<coordRef>
<type Sync="TRUE">Projected</type>
<geogcsn Sync="TRUE">GCS_SIRGAS_2000</geogcsn>
<csUnits Sync="TRUE">Linear Unit: Meter (1.000000)</csUnits>
<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/2.4.0'&gt;&lt;WKT&gt;PROJCS[&amp;quot;SIRGAS_2000_UTM_Zone_22S&amp;quot;,GEOGCS[&amp;quot;GCS_SIRGAS_2000&amp;quot;,DATUM[&amp;quot;D_SIRGAS_2000&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;,10000000.0],PARAMETER[&amp;quot;Central_Meridian&amp;quot;,-51.0],PARAMETER[&amp;quot;Scale_Factor&amp;quot;,0.9996],PARAMETER[&amp;quot;Latitude_Of_Origin&amp;quot;,0.0],UNIT[&amp;quot;Meter&amp;quot;,1.0],AUTHORITY[&amp;quot;EPSG&amp;quot;,31982]]&lt;/WKT&gt;&lt;XOrigin&gt;-5120900&lt;/XOrigin&gt;&lt;YOrigin&gt;1900&lt;/YOrigin&gt;&lt;XYScale&gt;450445547.3910538&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;WKID&gt;31982&lt;/WKID&gt;&lt;LatestWKID&gt;31982&lt;/LatestWKID&gt;&lt;/ProjectedCoordinateSystem&gt;</peXml>
<projcsn Sync="TRUE">SIRGAS_2000_UTM_Zone_22S</projcsn>
</coordRef>
<RasterProperties>
<General>
<PixelDepth Sync="TRUE">32</PixelDepth>
<HasColormap Sync="TRUE">FALSE</HasColormap>
<CompressionType Sync="TRUE">LZW</CompressionType>
<NumBands Sync="TRUE">1</NumBands>
<Format Sync="TRUE">TIFF</Format>
<HasPyramids Sync="TRUE">TRUE</HasPyramids>
<SourceType Sync="TRUE">continuous</SourceType>
<PixelType Sync="TRUE">signed integer</PixelType>
<NoDataValue Sync="TRUE">2.1474836e+09</NoDataValue>
</General>
</RasterProperties>
</DataProperties>
<SyncDate>20191008</SyncDate>
<SyncTime>16204400</SyncTime>
<ModDate>20191009</ModDate>
<ModTime>15353100</ModTime>
<scaleRange>
<minScale>150000000</minScale>
<maxScale>5000</maxScale>
</scaleRange>
</Esri>
<dataIdInfo>
<envirDesc Sync="FALSE">Esri ArcGIS 12.4.0.19948</envirDesc>
<dataLang>
<languageCode Sync="TRUE" value="por"/>
<countryCode Sync="TRUE" value="BRA"/>
</dataLang>
<idCitation>
<resTitle Sync="FALSE">Foto Aérea de 1949</resTitle>
<presForm>
<PresFormCd Sync="TRUE" value="005"/>
</presForm>
</idCitation>
<spatRpType>
<SpatRepTypCd Sync="TRUE" value="002"/>
</spatRpType>
<dataExt>
<geoEle>
<GeoBndBox esriExtentType="search">
<exTypeCode Sync="TRUE">1</exTypeCode>
<westBL Sync="TRUE">-51.204582</westBL>
<eastBL Sync="TRUE">-51.114219</eastBL>
<northBL Sync="TRUE">-23.279468</northBL>
<southBL Sync="TRUE">-23.352101</southBL>
</GeoBndBox>
</geoEle>
</dataExt>
<idPurp>Aerofoto de 1949: Londrina exportava café para o mundo e este foi o primeiro levantamento aerofotogramétrico do município. No núcleo central é possível localizar detalhes das primeiras edificações. Nos limites dessa área urbana, projetada pela Companhia de Terras Norte do Paraná, o café.</idPurp>
<idAbs>&lt;DIV STYLE="text-align:Left;"&gt;&lt;DIV&gt;&lt;DIV&gt;&lt;P&gt;&lt;SPAN&gt;Aerofoto de 1949: Realizado pela empresa ENFA, para o Município de Londrina, o acervo de fotos encontra-se na Secretaria Municipal de Obras e Pavimentação. Londrina exportava café para o mundo e este foi o primeiro levantamento aerofotogramétrico do município. Este voo a contempla 47 fotografias&lt;/SPAN&gt;&lt;/P&gt;&lt;/DIV&gt;&lt;/DIV&gt;&lt;/DIV&gt;</idAbs>
<idCredit>Prefeitura do Município de Londrina.</idCredit>
<searchKeys>
<keyword>Aerofoto; 1949; Londrina</keyword>
<keyword>aerofotogrametria</keyword>
<keyword>café</keyword>
<keyword>ENFA.</keyword>
</searchKeys>
</dataIdInfo>
<mdLang>
<languageCode Sync="TRUE" value="por"/>
<countryCode Sync="TRUE" value="BRA"/>
</mdLang>
<mdChar>
<CharSetCd Sync="TRUE" value="004"/>
</mdChar>
<distInfo>
<distFormat>
<formatName Sync="TRUE">Raster Dataset</formatName>
</distFormat>
</distInfo>
<mdHrLv>
<ScopeCd Sync="TRUE" value="005"/>
</mdHrLv>
<mdHrLvName Sync="TRUE">dataset</mdHrLvName>
<refSysInfo>
<RefSystem>
<refSysID>
<identCode Sync="TRUE" code="31982"/>
<idCodeSpace Sync="TRUE">EPSG</idCodeSpace>
<idVersion Sync="TRUE">7.8.3(8.1.2)</idVersion>
</refSysID>
</RefSystem>
</refSysInfo>
<spatRepInfo>
<Georect>
<cellGeo>
<CellGeoCd Sync="TRUE" value="002"/>
</cellGeo>
<numDims Sync="TRUE">2</numDims>
<tranParaAv Sync="TRUE">1</tranParaAv>
<chkPtAv Sync="TRUE">0</chkPtAv>
<cornerPts>
<pos Sync="TRUE">479088.861357 7417497.286183</pos>
</cornerPts>
<cornerPts>
<pos Sync="TRUE">479088.861357 7425527.923763</pos>
</cornerPts>
<cornerPts>
<pos Sync="TRUE">488318.945769 7425527.923763</pos>
</cornerPts>
<cornerPts>
<pos Sync="TRUE">488318.945769 7417497.286183</pos>
</cornerPts>
<centerPt>
<pos Sync="TRUE">483703.903563 7421512.604973</pos>
</centerPt>
<axisDimension type="002">
<dimSize Sync="TRUE">55483</dimSize>
<dimResol>
<value Sync="TRUE" uom="m">0.166359</value>
</dimResol>
</axisDimension>
<axisDimension type="001">
<dimSize Sync="TRUE">48273</dimSize>
<dimResol>
<value Sync="TRUE" uom="m">0.166359</value>
</dimResol>
</axisDimension>
<ptInPixel>
<PixOrientCd Sync="TRUE" value="001"/>
</ptInPixel>
</Georect>
</spatRepInfo>
<eainfo>
<detailed Name="of_1949_wg.vat">
<enttyp>
<enttypl Sync="TRUE">of_1949_wg.vat</enttypl>
<enttypt Sync="TRUE">Table</enttypt>
<enttypc Sync="TRUE">252</enttypc>
</enttyp>
<attr>
<attrlabl Sync="TRUE">Rowid</attrlabl>
<attalias Sync="TRUE">Rowid</attalias>
<attrtype Sync="TRUE">OID</attrtype>
<attwidth Sync="TRUE">4</attwidth>
<atprecis Sync="TRUE">0</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">VALUE</attrlabl>
<attalias Sync="TRUE">VALUE</attalias>
<attrtype Sync="TRUE">Integer</attrtype>
<attwidth Sync="TRUE">4</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">COUNT</attrlabl>
<attalias Sync="TRUE">COUNT</attalias>
<attrtype Sync="TRUE">Integer</attrtype>
<attwidth Sync="TRUE">4</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
</detailed>
</eainfo>
<contInfo>
<ImgDesc>
<contentTyp>
<ContentTypCd Sync="TRUE" value="001"/>
</contentTyp>
<covDim>
<Band>
<dimDescrp Sync="TRUE">Band_1</dimDescrp>
<maxVal Sync="TRUE">255.000000</maxVal>
<minVal Sync="TRUE">0.000000</minVal>
<bitsPerVal Sync="TRUE">32</bitsPerVal>
<valUnit>
<UOM type="length"/>
</valUnit>
</Band>
</covDim>
</ImgDesc>
</contInfo>
<mdDateSt Sync="TRUE">20191009</mdDateSt>
<spdoinfo>
<rastinfo>
<rasttype Sync="TRUE">Pixel</rasttype>
<rowcount Sync="TRUE">48273</rowcount>
<colcount Sync="TRUE">55483</colcount>
<rastxsz Sync="TRUE">0,166359</rastxsz>
<rastysz Sync="TRUE">0,166359</rastysz>
<rastbpp Sync="TRUE">32</rastbpp>
<vrtcount Sync="TRUE">1</vrtcount>
<rastorig Sync="TRUE">Upper Left</rastorig>
<rastcmap Sync="TRUE">FALSE</rastcmap>
<rastcomp Sync="TRUE">LZ77</rastcomp>
<rastband Sync="TRUE">1</rastband>
<rastdtyp Sync="TRUE">pixel codes</rastdtyp>
<rastifor Sync="TRUE">FGDBR</rastifor>
<rastplyr Sync="TRUE">TRUE</rastplyr>
</rastinfo>
</spdoinfo>
<spref>
<horizsys>
<planar>
<planci>
<plance Sync="TRUE">row and column</plance>
<coordrep>
<absres Sync="TRUE">0,166359</absres>
<ordres Sync="TRUE">0,166359</ordres>
</coordrep>
</planci>
</planar>
</horizsys>
</spref>
<Binary>
<Thumbnail>
<Data EsriPropertyType="PictureX">/9j/4AAQSkZJRgABAQEAYABgAAD/2wBDAAMCAgMCAgMDAwMEAwMEBQgFBQQEBQoHBwYIDAoMDAsK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</Data>
</Thumbnail>
</Binary>
</metadata>
