<?xml version="1.0" encoding="UTF-8"?><metadata xml:lang="en">
    <Esri>
        <ArcGISFormat>1.0</ArcGISFormat>
        <ArcGISProfile>DCPLUS</ArcGISProfile>
        <CreaDate>20151201</CreaDate>
        <CreaTime>21280500</CreaTime>
        <ModDate>20151201</ModDate>
        <ModTime>21280500</ModTime>
        <DataProperties>
            <itemProps>
                <portalDetails>
                    <thumbnailURL>https://www.arcgis.com/sharing/rest/content/items/3afc2479a75446d2aa4cac894e01aca6/info/thumbnail/ago_downloaded.png</thumbnailURL>
                    <itemDetailsURL>https://www.arcgis.com/home/item.html?id=3afc2479a75446d2aa4cac894e01aca6</itemDetailsURL>
                    <itemIdentifier>3afc2479a75446d2aa4cac894e01aca6</itemIdentifier>
                    <itemType>Feature Service</itemType>
                    <resourceURL>http://services.arcgis.com/ULBqC49IEeIR01GF/arcgis/rest/services/Area B TotalMod/FeatureServer</resourceURL>
                </portalDetails>
            </itemProps>
        </DataProperties>
    </Esri>
    <dataIdInfo>
        <idCitation>
            <resTitle>Area B TotalMod</resTitle>
            <date>
                <createDate>2015-12-01T21:28:05</createDate>
                <reviseDate>2015-12-01T21:28:38</reviseDate>
            </date>
        </idCitation>
        <searchKeys>
            <keyword>Analysis Result</keyword>
            <keyword>Hot Spots</keyword>
            <keyword>SU_Density_b_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 437 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;1130.0000&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td&gt;Mean&lt;/td&gt;&lt;td style='float: right;'&gt;83.0870&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td&gt;Std. Dev.&lt;/td&gt;&lt;td style='float: right;'&gt;159.0608&lt;/td&gt;&lt;/tr&gt;&lt;/tbody&gt;&lt;/table&gt;&lt;br /&gt;&lt;ul&gt;&lt;li&gt;There were 7 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 145.9477 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;41 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">23.403089444938598</westBL>
                    <eastBL Sync="FALSE">23.46549540772638</eastBL>
                    <northBL Sync="FALSE">38.1566083207777</northBL>
                    <southBL Sync="FALSE">38.14090407470007</southBL>
                    <exTypeCode Sync="TRUE">1</exTypeCode>
                </GeoBndBox>
            </geoEle>
        </dataExt>
    </dataIdInfo>
    <Binary>
        <Thumbnail>
            <Data EsriPropertyType="PictureX">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</Data>
        </Thumbnail>
    </Binary>
    <mdFileID>3afc2479a75446d2aa4cac894e01aca6</mdFileID>
    <distInfo>
        <distTranOps>
            <onLineSrc>
                <linkage>http://services.arcgis.com/ULBqC49IEeIR01GF/arcgis/rest/services/Area B TotalMod/FeatureServer</linkage>
            </onLineSrc>
        </distTranOps>
        <distFormat>
            <formatName>Feature Service</formatName>
        </distFormat>
    </distInfo>
</metadata>
