<?xml version="1.0" encoding="UTF-8"?><metadata xml:lang="en">
    <Esri>
        <ArcGISFormat>1.0</ArcGISFormat>
        <ArcGISProfile>DCPLUS</ArcGISProfile>
        <CreaDate>20151220</CreaDate>
        <CreaTime>01223000</CreaTime>
        <ModDate>20151220</ModDate>
        <ModTime>01223000</ModTime>
        <DataProperties>
            <itemProps>
                <portalDetails>
                    <thumbnailURL>https://www.arcgis.com/sharing/rest/content/items/9d2ec097e4d444af96e2e093170907da/info/thumbnail/ago_downloaded.png</thumbnailURL>
                    <itemDetailsURL>https://www.arcgis.com/home/item.html?id=9d2ec097e4d444af96e2e093170907da</itemDetailsURL>
                    <itemIdentifier>9d2ec097e4d444af96e2e093170907da</itemIdentifier>
                    <itemType>Feature Service</itemType>
                    <resourceURL>http://services.arcgis.com/ULBqC49IEeIR01GF/arcgis/rest/services/Area e TotalMod/FeatureServer</resourceURL>
                </portalDetails>
            </itemProps>
        </DataProperties>
    </Esri>
    <dataIdInfo>
        <idCitation>
            <resTitle>Area e TotalMod</resTitle>
            <date>
                <createDate>2015-12-20T01:22:30</createDate>
                <reviseDate>2015-12-20T01:23:02</reviseDate>
            </date>
        </idCitation>
        <searchKeys>
            <keyword>Analysis Result</keyword>
            <keyword>Hot Spots</keyword>
            <keyword>SU_Density_e_20142015</keyword>
            <keyword>TotalMod</keyword>
        </searchKeys>
        <idPurp>Analysis Feature Service generated from Find Hot Spots</idPurp>
        <idAbs>&lt;b&gt;The following report outlines the workflow used to optimize your Find Hot Spots result:&lt;/b&gt;&lt;br /&gt;&lt;u&gt;&lt;b&gt;Initial Data Assessment.&lt;/b&gt;&lt;/u&gt;&lt;br /&gt;&lt;ul&gt;&lt;li&gt;There were 516 valid input features.&lt;/li&gt;&lt;/ul&gt;&lt;ul&gt;&lt;li&gt;TOTALMOD Properties:&lt;/li&gt;&lt;/ul&gt;&lt;table style='width: 200px;margin-left: 2.5em;'&gt;&lt;tbody&gt;&lt;tr&gt;&lt;td&gt;Min&lt;/td&gt;&lt;td style='float:right'&gt;0.0000&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td&gt;Max&lt;/td&gt;&lt;td style='float: right;'&gt;421.0000&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td&gt;Mean&lt;/td&gt;&lt;td style='float: right;'&gt;22.8915&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td&gt;Std. Dev.&lt;/td&gt;&lt;td style='float: right;'&gt;34.5675&lt;/td&gt;&lt;/tr&gt;&lt;/tbody&gt;&lt;/table&gt;&lt;br /&gt;&lt;ul&gt;&lt;li&gt;There were 5 outlier locations; these were not used to compute the optimal fixed distance band.&lt;/li&gt;&lt;/ul&gt;&lt;br /&gt;&lt;u&gt;&lt;b&gt;Scale of Analysis&lt;/b&gt;&lt;/u&gt;&lt;br /&gt;&lt;ul&gt;&lt;li&gt;The optimal fixed distance band selected was based on peak clustering found at 145.1761 Meters.&lt;/li&gt;&lt;/ul&gt;&lt;br /&gt;&lt;u&gt;&lt;b&gt;Hot Spot Analysis&lt;/b&gt;&lt;/u&gt;&lt;br /&gt;&lt;ul&gt;&lt;li&gt;11 output features are statistically significant based on a FDR correction for multiple testing and spatial dependence.&lt;/li&gt;&lt;/ul&gt;&lt;br /&gt;&lt;u&gt;&lt;b&gt;Output&lt;/b&gt;&lt;/u&gt;&lt;br /&gt;&lt;ul&gt;&lt;li&gt;Red output features represent hot spots where high TOTALMOD values cluster.&lt;/li&gt;&lt;/ul&gt;&lt;ul&gt;&lt;li&gt;Blue output features represent cold spots where low TOTALMOD values cluster.&lt;/li&gt;&lt;/ul&gt;&lt;br /&gt;</idAbs>
        <dataExt>
            <geoEle>
                <GeoBndBox>
                    <westBL Sync="FALSE">23.361829823938987</westBL>
                    <eastBL Sync="FALSE">23.40460759776876</eastBL>
                    <northBL Sync="FALSE">38.18062086993863</northBL>
                    <southBL Sync="FALSE">38.164229630718815</southBL>
                    <exTypeCode Sync="TRUE">1</exTypeCode>
                </GeoBndBox>
            </geoEle>
        </dataExt>
    </dataIdInfo>
    <Binary>
        <Thumbnail>
            <Data EsriPropertyType="PictureX">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</Data>
        </Thumbnail>
    </Binary>
    <mdFileID>9d2ec097e4d444af96e2e093170907da</mdFileID>
    <distInfo>
        <distTranOps>
            <onLineSrc>
                <linkage>http://services.arcgis.com/ULBqC49IEeIR01GF/arcgis/rest/services/Area e TotalMod/FeatureServer</linkage>
            </onLineSrc>
        </distTranOps>
        <distFormat>
            <formatName>Feature Service</formatName>
        </distFormat>
    </distInfo>
</metadata>
