AddAttributesFast.Add_Topographic_Attributes_High_Tool.pyt.xml

<?xml version="1.0"?>
<metadata xml:lang="en"><Esri><CreaDate>20260310</CreaDate><CreaTime>14432800</CreaTime><ArcGISFormat>1.0</ArcGISFormat><SyncOnce>TRUE</SyncOnce><ModDate>20260616</ModDate><ModTime>11173100</ModTime><scaleRange><minScale>150000000</minScale><maxScale>5000</maxScale></scaleRange><ArcGISProfile>ItemDescription</ArcGISProfile></Esri><tool name="Add_Topographic_Attributes_High_Tool" displayname="Add Topographic Attributes High Tool Fast" toolboxalias="AddAttributesFast" xmlns=""><arcToolboxHelpPath>c:\program files\arcgis\pro\Resources\Help\gp</arcToolboxHelpPath><parameters><param name="inFeatClass" displayname="Input Features" type="Required" direction="Input" datatype="Feature Layer" expression="inFeatClass"><dialogReference>&lt;DIV STYLE="text-align:Left;"&gt;&lt;DIV&gt;&lt;DIV&gt;&lt;P&gt;&lt;SPAN STYLE="font-weight:bold;"&gt;This is a feature class delineates the bathymetric high features.&lt;/SPAN&gt;&lt;/P&gt;&lt;/DIV&gt;&lt;/DIV&gt;&lt;/DIV&gt;</dialogReference></param><param name="bathyRas" displayname="Input Bathymetry Raster" type="Required" direction="Input" datatype="Raster Layer" expression="bathyRas"><dialogReference>&lt;DIV STYLE="text-align:Left;"&gt;&lt;DIV&gt;&lt;DIV&gt;&lt;P&gt;&lt;SPAN STYLE="font-weight:bold;"&gt;This is the bathymetry &lt;/SPAN&gt;&lt;SPAN STYLE="font-weight:bold;"&gt;raster&lt;/SPAN&gt;&lt;SPAN STYLE="font-weight:bold;"&gt;.&lt;/SPAN&gt;&lt;/P&gt;&lt;/DIV&gt;&lt;/DIV&gt;&lt;/DIV&gt;</dialogReference></param><param name="nCPU" displayname="Number of CPU processors used for multiprocessing" type="Required" direction="Input" datatype="Long" expression="nCPU"><dialogReference>&lt;DIV STYLE="text-align:Left;"&gt;&lt;DIV&gt;&lt;DIV&gt;&lt;P&gt;&lt;SPAN STYLE="font-weight:bold;"&gt;Enter the desirable number of CPU processors used for multiprocessing.&lt;/SPAN&gt;&lt;SPAN STYLE="font-weight:bold;"&gt; The default if half of the available CPU processors&lt;/SPAN&gt;&lt;SPAN STYLE="font-weight:bold;"&gt; minus 1&lt;/SPAN&gt;&lt;SPAN STYLE="font-weight:bold;"&gt;.&lt;/SPAN&gt;&lt;/P&gt;&lt;/DIV&gt;&lt;/DIV&gt;&lt;/DIV&gt;</dialogReference></param></parameters><summary>&lt;DIV STYLE="text-align:Left;"&gt;&lt;DIV&gt;&lt;DIV&gt;&lt;P&gt;&lt;SPAN&gt;This tool incorporates multiprocessing capability to speed up the calculation performance. It is thus more efficient in generating &lt;/SPAN&gt;&lt;SPAN&gt;topographic &lt;/SPAN&gt;&lt;SPAN&gt;attributes for each bathymetric high feature. Essentially, this tool opens multiple Python windows depending on the "Number of CPU processors" parameter. Each of this Python window processes a subset of input features.  After completing the multiprocessing, the results are merged as the final output.&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;This tool add a number of &lt;/SPAN&gt;&lt;SPAN&gt;topographic &lt;/SPAN&gt;&lt;SPAN&gt;attributes to the input &lt;/SPAN&gt;&lt;SPAN&gt;bathymetric high &lt;/SPAN&gt;&lt;SPAN&gt;feature class. The following attributes are &lt;/SPAN&gt;&lt;SPAN&gt;calculated&lt;/SPAN&gt;&lt;SPAN&gt; from the bathymetry &lt;/SPAN&gt;&lt;SPAN&gt;grid &lt;/SPAN&gt;&lt;SPAN&gt;to describe &lt;/SPAN&gt;&lt;SPAN&gt;the topographic properties &lt;/SPAN&gt;&lt;SPAN&gt;of each bathymetric high feature&lt;/SPAN&gt;&lt;SPAN&gt;.&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;1&lt;/SPAN&gt;&lt;SPAN&gt;. m&lt;/SPAN&gt;&lt;SPAN&gt;inDepth&lt;/SPAN&gt;&lt;SPAN&gt;: the minimum water depth within the feature polygon&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;2&lt;/SPAN&gt;&lt;SPAN&gt;. &lt;/SPAN&gt;&lt;SPAN&gt;maxDepth&lt;/SPAN&gt;&lt;SPAN&gt;: the maximum water depth within the feature polygon&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;3&lt;/SPAN&gt;&lt;SPAN&gt;. &lt;/SPAN&gt;&lt;SPAN&gt;depthRange&lt;/SPAN&gt;&lt;SPAN&gt;: the difference in water depth within the feature polygon, which is calculated as &lt;/SPAN&gt;&lt;SPAN&gt;(&lt;/SPAN&gt;&lt;SPAN&gt;maxDepth - minDepth&lt;/SPAN&gt;&lt;SPAN&gt;)&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;4&lt;/SPAN&gt;&lt;SPAN&gt;. &lt;/SPAN&gt;&lt;SPAN&gt;meanDepth&lt;/SPAN&gt;&lt;SPAN&gt;: the mean water depth within the feature polygon&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;5&lt;/SPAN&gt;&lt;SPAN&gt;. &lt;/SPAN&gt;&lt;SPAN&gt;stdDepth&lt;/SPAN&gt;&lt;SPAN&gt;: the standard deviation of the water depths within the feature polygon&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;6. medianDepth: &lt;/SPAN&gt;&lt;SPAN&gt;the &lt;/SPAN&gt;&lt;SPAN&gt;median &lt;/SPAN&gt;&lt;SPAN&gt;water depth within the feature polygon&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;7. relativeHeight: is the relative height of the feature, calculated as the difference between the water depth of the 97.5th percentile and the water depth of the 2.5th percentile&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;8&lt;/SPAN&gt;&lt;SPAN&gt;. &lt;/SPAN&gt;&lt;SPAN&gt;minGradient&lt;/SPAN&gt;&lt;SPAN&gt;: the minimum slope-gradient within the feature polygon&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;9&lt;/SPAN&gt;&lt;SPAN&gt;. &lt;/SPAN&gt;&lt;SPAN&gt;maxGradient&lt;/SPAN&gt;&lt;SPAN&gt;: the maximum slope-gradient within the feature polygon&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;10&lt;/SPAN&gt;&lt;SPAN&gt;. &lt;/SPAN&gt;&lt;SPAN&gt;gradientRange&lt;/SPAN&gt;&lt;SPAN&gt;: the difference in slope-gradient within the feature polygon, which is calculated as &lt;/SPAN&gt;&lt;SPAN&gt;(&lt;/SPAN&gt;&lt;SPAN&gt;maxGradient - minGradient&lt;/SPAN&gt;&lt;SPAN&gt;)&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;11&lt;/SPAN&gt;&lt;SPAN&gt;. &lt;/SPAN&gt;&lt;SPAN&gt;meanGradient&lt;/SPAN&gt;&lt;SPAN&gt;: the mean slope-gradient within the feature polygon&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;1&lt;/SPAN&gt;&lt;SPAN&gt;2&lt;/SPAN&gt;&lt;SPAN&gt;. &lt;/SPAN&gt;&lt;SPAN&gt;stdGradient&lt;/SPAN&gt;&lt;SPAN&gt;: the standard deviation of the slope-gradients within the feature polygon&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;13. medianGradient: &lt;/SPAN&gt;&lt;SPAN&gt;the &lt;/SPAN&gt;&lt;SPAN&gt;median &lt;/SPAN&gt;&lt;SPAN&gt;slope-gradient within the feature polygon&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;14. surfaceArea: the surface area of the feature polygon, &lt;/SPAN&gt;&lt;SPAN&gt;calculated from the surface area grid (Jenness, 2004)&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;15. volume:&lt;/SPAN&gt;&lt;SPAN&gt; the volume of the feature, calculated as the difference between the feature surface and the reference surface (e.g, the &lt;/SPAN&gt;&lt;SPAN&gt;bottom &lt;/SPAN&gt;&lt;SPAN&gt;base of the feature) using the 3D analyst extension&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;16. sArea:&lt;/SPAN&gt;&lt;SPAN&gt; the surface area of the feature polygon, calculated using the 3D analyst extension&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;Note that for a very small (narrow) feature, the volume and sArea attributes could not be calculated. &lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;The key reference for this tool is the following journal article: &lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;Huang, Z., Nanson, R., McNeil, M., Wenderlich, M., Gafeira, J., Post, A, Nichol, S., 2023. Rule-based semi-automated tools for mapping seabed morphology from bathymetry data&lt;/SPAN&gt;&lt;SPAN STYLE="font-style:italic;"&gt;&lt;SPAN&gt;, Frontiers in Marine Science&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;SPAN&gt;, 10, 1236788.&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;Other reference:&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN /&gt;&lt;SPAN&gt;Jenness, J.S., 2004. Calculating landscape surface area from digital elevation model. Wildlife Society Bulletin, 32, 829-839.&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN /&gt;&lt;/P&gt;&lt;/DIV&gt;&lt;/DIV&gt;&lt;/DIV&gt;</summary><scriptExamples><scriptExample><para>&lt;DIV STYLE="text-align:Left;"&gt;&lt;DIV&gt;&lt;DIV&gt;&lt;P&gt;&lt;SPAN&gt;This tool can not be called from Python script or Python comman&lt;/SPAN&gt;&lt;SPAN&gt;d&lt;/SPAN&gt;&lt;SPAN&gt; line window.&lt;/SPAN&gt;&lt;/P&gt;&lt;/DIV&gt;&lt;/DIV&gt;&lt;/DIV&gt;</para></scriptExample></scriptExamples></tool><dataIdInfo><idCitation><resTitle>Add Topographic Attributes High Tool Fast</resTitle></idCitation><idCredit>(c) Commonwealth of Australia (Geoscience Australia) 2026</idCredit><searchKeys><keyword>This tool offers multiprocessing capability and thus is more efficient in generating topographic attributes for each bathymetric high feature.</keyword></searchKeys><resConst><Consts><useLimit>&lt;DIV STYLE="text-align:Left;"&gt;&lt;DIV&gt;&lt;DIV&gt;&lt;P&gt;&lt;SPAN&gt;Creative Commons Attribution 4.0 International Licence&lt;/SPAN&gt;&lt;/P&gt;&lt;/DIV&gt;&lt;/DIV&gt;&lt;/DIV&gt;</useLimit></Consts></resConst></dataIdInfo><distInfo><distributor><distorFormat><formatName>ArcToolbox Tool</formatName></distorFormat></distributor></distInfo><mdHrLv><ScopeCd value="005"/></mdHrLv><mdDateSt Sync="TRUE">20260616</mdDateSt><Binary><Thumbnail><Data EsriPropertyType="PictureX">/9j/4AAQSkZJRgABAQEAeAB4AAD/2wBDAAMCAgMCAgMDAwMEAwMEBQgFBQQEBQoHBwYIDAoMDAsK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</Data></Thumbnail></Binary></metadata>