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BathymetricHigh.TPI_LMITool.pyt.xml
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<?xml version="1.0"?>
<metadata xml:lang="en"><Esri><CreaDate>20201208</CreaDate><CreaTime>09504100</CreaTime><ArcGISFormat>1.0</ArcGISFormat><SyncOnce>TRUE</SyncOnce><ModDate>20240624</ModDate><ModTime>11115700</ModTime><scaleRange><minScale>150000000</minScale><maxScale>5000</maxScale></scaleRange><ArcGISProfile>ItemDescription</ArcGISProfile></Esri><tool name="TPI_LMITool" displayname="TPI LMI Tool Bathymetric High" toolboxalias="BathymetricHigh" xmlns=""><arcToolboxHelpPath>c:\program files\arcgis\pro\Resources\Help\gp</arcToolboxHelpPath><parameters><param name="bathyRas" displayname="Input Bathymetry Raster" type="Required" direction="Input" datatype="Raster Layer" expression="bathyRas"><dialogReference><DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN STYLE="font-weight:bold;">This is the input bathymetry raster.</SPAN></P></DIV></DIV></DIV></dialogReference><pythonReference><DIV STYLE="text-align:Left;"><DIV><P><SPAN STYLE="font-weight:bold;">This is the input bathymetry raster.</SPAN></P></DIV></DIV></pythonReference></param><param name="tpiRas" displayname="Output TPI Raster" type="Required" direction="Output" datatype="Raster Dataset" expression="tpiRas"><dialogReference><DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN STYLE="font-weight:bold;">This is the output TPI raster.</SPAN><SPAN STYLE="font-weight:bold;"> After the first run, the TPI raster will be copied to the temporary workspace. This TPI raster will be re-used in the subsequent runs to save time as long as the raster name entered matches the one in the temporary workspace.</SPAN></P><P><SPAN /></P></DIV></DIV></DIV></dialogReference><pythonReference><DIV STYLE="text-align:Left;"><DIV><P><SPAN STYLE="font-weight:bold;">This is the output TPI raster.</SPAN><SPAN STYLE="font-weight:bold;"> After the first run, the TPI raster will be copied to the temporary workspace. This TPI raster will be re-used in the subsequent runs to save time as long as the raster name entered matches the one in the temporary workspace.</SPAN></P></DIV></DIV></pythonReference></param><param name="outFeat" displayname="Output Feature" type="Required" direction="Output" datatype="Feature Class" expression="outFeat"><dialogReference><DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN STYLE="font-weight:bold;">This is </SPAN><SPAN STYLE="font-weight:bold;">the output</SPAN><SPAN STYLE="font-weight:bold;"> feature class delineates the bathymetric high features.</SPAN></P></DIV></DIV></DIV></dialogReference><pythonReference><DIV STYLE="text-align:Left;"><DIV><P><SPAN STYLE="font-weight:bold;">This is </SPAN><SPAN STYLE="font-weight:bold;">the output</SPAN><SPAN STYLE="font-weight:bold;"> feature class delineates the bathymetric high features.</SPAN></P></DIV></DIV></pythonReference></param><param name="areaThreshold" displayname="Area Threshold" type="Required" direction="Input" datatype="Areal Unit" expression="areaThreshold"><dialogReference><DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN STYLE="font-weight:bold;">The threshold of polygon area. All resulted bathymetric high feature polygons should have areas greater than this threshold. </SPAN></P></DIV></DIV></DIV></dialogReference><pythonReference><DIV STYLE="text-align:Left;"><DIV><P><SPAN STYLE="font-weight:bold;">The threshold of polygon area. All resulted bathymetric high feature polygons should have areas greater than this threshold. </SPAN></P></DIV></DIV></pythonReference></param><param name="tpiRadius" displayname="TPI Circle Radius (unit: cell)" type="Required" direction="Input" datatype="Long" expression="tpiRadius"><dialogReference><DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN STYLE="font-weight:bold;">This is the radius used to calculate the output TPI raster.</SPAN></P></DIV></DIV></DIV></dialogReference><pythonReference><DIV STYLE="text-align:Left;"><DIV><P><SPAN STYLE="font-weight:bold;">This is the radius used to calculate the output TPI raster.</SPAN></P></DIV></DIV></pythonReference></param><param name="tpiSTDScaleLarge" displayname="TPI STD Scale Large" type="Optional" direction="Input" datatype="Double" expression="{tpiSTDScaleLarge}"><dialogReference><DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN STYLE="font-weight:bold;">This is the constant value (c) applied to the standard deviation (STD) of the output TPI raster to calculate the </SPAN><SPAN STYLE="font-weight:bold;">(large) </SPAN><SPAN STYLE="font-weight:bold;">TPI threshold. </SPAN></P><P><SPAN STYLE="font-weight:bold;">TPI threshold = </SPAN><SPAN STYLE="font-weight:bold;">mean_TPI + c * STD_TPI</SPAN><SPAN STYLE="font-weight:bold;">, where mean</SPAN><SPAN STYLE="font-weight:bold;">_</SPAN><SPAN STYLE="font-weight:bold;">TPI is the mean of the output TPI raster.</SPAN><SPAN STYLE="font-weight:bold;"> This constant value must be larger than the </SPAN><SPAN STYLE="font-weight:bold;">'TPI STD Scale Small' parameter</SPAN><SPAN STYLE="font-weight:bold;">.</SPAN></P><P><SPAN /></P></DIV></DIV></DIV></dialogReference><pythonReference><DIV STYLE="text-align:Left;"><P><SPAN STYLE="font-weight:bold;">This is the constant value (c) applied to the standard deviation (STD) of the output TPI raster to calculate the </SPAN><SPAN STYLE="font-weight:bold;">(large) </SPAN><SPAN STYLE="font-weight:bold;">TPI threshold. </SPAN></P><P><SPAN STYLE="font-weight:bold;">TPI threshold = </SPAN><SPAN STYLE="font-weight:bold;">mean_TPI + c * STD_TPI</SPAN><SPAN STYLE="font-weight:bold;">, where mean</SPAN><SPAN STYLE="font-weight:bold;">_</SPAN><SPAN STYLE="font-weight:bold;">TPI is the mean of the output TPI raster.</SPAN><SPAN STYLE="font-weight:bold;"> This constant value must be larger than the </SPAN><SPAN STYLE="font-weight:bold;">'TPI STD Scale Small' parameter</SPAN><SPAN STYLE="font-weight:bold;">.</SPAN></P></DIV></pythonReference></param><param name="tpiSTDScaleSmall" displayname="TPI STD Scale Small" type="Optional" direction="Input" datatype="Double" expression="{tpiSTDScaleSmall}"><dialogReference><DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN STYLE="font-weight:bold;">This is the constant value (c) applied to the standard deviation (STD) of the output TPI raster to calculate the </SPAN><SPAN STYLE="font-weight:bold;">(small) </SPAN><SPAN STYLE="font-weight:bold;">TPI threshold. </SPAN></P><P><SPAN STYLE="font-weight:bold;">TPI threshold = </SPAN><SPAN STYLE="font-weight:bold;">mean_TPI + c * STD_TPI</SPAN><SPAN STYLE="font-weight:bold;">, where mean</SPAN><SPAN STYLE="font-weight:bold;">_</SPAN><SPAN STYLE="font-weight:bold;">TPI is the mean of the output TPI raster.</SPAN><SPAN STYLE="font-weight:bold;"> This constant value must be smaller than the </SPAN><SPAN STYLE="font-weight:bold;">'TPI STD Scale Large' parameter</SPAN><SPAN STYLE="font-weight:bold;">.</SPAN></P></DIV></DIV></DIV></dialogReference><pythonReference><DIV STYLE="text-align:Left;"><P><SPAN STYLE="font-weight:bold;">This is the constant value (c) applied to the standard deviation (STD) of the output TPI raster to calculate the </SPAN><SPAN STYLE="font-weight:bold;">(small) </SPAN><SPAN STYLE="font-weight:bold;">TPI threshold. </SPAN></P><P><SPAN STYLE="font-weight:bold;">TPI threshold = </SPAN><SPAN STYLE="font-weight:bold;">mean_TPI + c * STD_TPI</SPAN><SPAN STYLE="font-weight:bold;">, where mean</SPAN><SPAN STYLE="font-weight:bold;">_</SPAN><SPAN STYLE="font-weight:bold;">TPI is the mean of the output TPI raster.</SPAN><SPAN STYLE="font-weight:bold;"> This constant value must be smaller than the </SPAN><SPAN STYLE="font-weight:bold;">'TPI STD Scale Large' parameter</SPAN><SPAN STYLE="font-weight:bold;">.</SPAN></P></DIV></pythonReference></param><param name="lmiWeightFile" displayname="LMI Weight File" type="Required" direction="Input" datatype="File" expression="lmiWeightFile"><dialogReference><DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN STYLE="font-weight:bold;">This is the kernel (weight) file used to define a NbrWeight neighborhood required for the calculation the LMI raster.</SPAN></P></DIV></DIV></DIV></dialogReference><pythonReference><DIV STYLE="text-align:Left;"><DIV><P><SPAN STYLE="font-weight:bold;">This is the kernel (weight) file used to define a NbrWeight neighborhood required for the calculation the LMI raster.</SPAN></P></DIV></DIV></pythonReference></param><param name="lmiSTDScale" displayname="LMI STD Scale" type="Optional" direction="Input" datatype="Double" expression="{lmiSTDScale}"><dialogReference><DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN STYLE="font-weight:bold;">This is the constant value (c) applied to the standard deviation (STD) of the </SPAN><SPAN STYLE="font-weight:bold;">LMI </SPAN><SPAN STYLE="font-weight:bold;">raster to calculate the </SPAN><SPAN STYLE="font-weight:bold;">LMI </SPAN><SPAN STYLE="font-weight:bold;">threshold. </SPAN></P><P><SPAN STYLE="font-weight:bold;">LMI </SPAN><SPAN STYLE="font-weight:bold;">threshold = </SPAN><SPAN STYLE="font-weight:bold;">mean_LMI + c * STD_LMI</SPAN><SPAN STYLE="font-weight:bold;">, where mean</SPAN><SPAN STYLE="font-weight:bold;">_</SPAN><SPAN STYLE="font-weight:bold;">LMI</SPAN><SPAN STYLE="font-weight:bold;"> is the mean of the </SPAN><SPAN STYLE="font-weight:bold;">LM</SPAN><SPAN STYLE="font-weight:bold;">I raster.</SPAN></P><P><SPAN /></P></DIV></DIV></DIV></dialogReference><pythonReference><DIV STYLE="text-align:Left;"><P><SPAN STYLE="font-weight:bold;">This is the constant value (c) applied to the standard deviation (STD) of the </SPAN><SPAN STYLE="font-weight:bold;">LMI </SPAN><SPAN STYLE="font-weight:bold;">raster to calculate the </SPAN><SPAN STYLE="font-weight:bold;">LMI </SPAN><SPAN STYLE="font-weight:bold;">threshold. </SPAN></P><P><SPAN STYLE="font-weight:bold;">LMI </SPAN><SPAN STYLE="font-weight:bold;">threshold = </SPAN><SPAN STYLE="font-weight:bold;">mean_LMI + c * STD_LMI</SPAN><SPAN STYLE="font-weight:bold;">, where mean</SPAN><SPAN STYLE="font-weight:bold;">_</SPAN><SPAN STYLE="font-weight:bold;">LMI</SPAN><SPAN STYLE="font-weight:bold;"> is the mean of the </SPAN><SPAN STYLE="font-weight:bold;">LM</SPAN><SPAN STYLE="font-weight:bold;">I raster.</SPAN></P></DIV></pythonReference></param><param name="tempWS" displayname="Temporary Workspace" type="Required" direction="Input" datatype="Workspace" expression="tempWS"><dialogReference><DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN STYLE="font-weight:bold;">This is the location of the temporary workspace to store the intermediate datasets.</SPAN></P></DIV></DIV></DIV></dialogReference><pythonReference><DIV STYLE="text-align:Left;"><DIV><P><SPAN STYLE="font-weight:bold;">This is the location of the temporary workspace to store the intermediate datasets.</SPAN></P></DIV></DIV></pythonReference></param></parameters><summary><DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>This tool maps bathymetric high features from a bathymetric data using a </SPAN><SPAN>combination of </SPAN><SPAN>Topographic Position Index (TPI) </SPAN><SPAN>(Weiss, 2001) </SPAN><SPAN>and Local Moran's I (LMI) </SPAN><SPAN>(Moran, 1950) </SPAN><SPAN>method.</SPAN><SPAN> </SPAN><SPAN>Positive TPI usually indicates bathymetric high location. </SPAN><SPAN>Positive LMI usually indicates a spatial pattern of positive (higher than average) local autocorrelation (e.g., in this case a similar local pattern of higher bathymetry values). </SPAN><SPAN>The followings are the key steps</SPAN><SPAN> of this tool</SPAN><SPAN>.</SPAN></P><OL><LI><P><SPAN>Calculate TPI from the input bathymetry raster using the "TPI Circle Radius" parameter.</SPAN></P></LI><LI><P><SPAN>Calculate the TPI threshold</SPAN><SPAN>s</SPAN><SPAN> using this equation: TPI threshold = mean_TPI + c * STD_TPI, where c is the "TPI STD Scale</SPAN><SPAN> Large</SPAN><SPAN>" parameter</SPAN><SPAN> or the "TPI STD Scale Small" parameter</SPAN><SPAN>, mean_TPI and STD_TPI are the mean and standard deviation statistics of the TPI raster. </SPAN></P></LI><LI><P><SPAN>Select </SPAN><SPAN>the first set of areas </SPAN><SPAN>that have TPI values greater than the </SPAN><SPAN>"TPI STD Scale Large" </SPAN><SPAN>threshold.</SPAN></P></LI><LI><P><SPAN>Select </SPAN><SPAN>the second set of areas </SPAN><SPAN>that have TPI values greater than the </SPAN><SPAN>"TPI STD Scale Small" </SPAN><SPAN>threshold.</SPAN></P></LI><LI><P><SPAN>These two sets of areas and the bathymetry data are used together to select the 'core' areas of bathymetric high features, through GIS overlay and selection analyses. </SPAN></P></LI><LI><P><SPAN>These 'core' areas are substracted from the bathymetry data.</SPAN></P></LI><LI><P><SPAN>Calculate LMI from the substracted bathymetry raster using the "LMI Weight File" parameter.</SPAN></P></LI><LI><P><SPAN>Calculate the </SPAN><SPAN>LMI</SPAN><SPAN> threshold</SPAN><SPAN>s</SPAN><SPAN> using this equation: </SPAN><SPAN>LMI</SPAN><SPAN> threshold = mean_</SPAN><SPAN>LMI</SPAN><SPAN> + c * STD_</SPAN><SPAN>LMI</SPAN><SPAN>, where c is the "</SPAN><SPAN>LMI</SPAN><SPAN> STD Scale" parameter</SPAN><SPAN> </SPAN><SPAN>, mean_</SPAN><SPAN>LM</SPAN><SPAN>I and STD_</SPAN><SPAN>LM</SPAN><SPAN>I are the mean and standard deviation statistics of the </SPAN><SPAN>LMI</SPAN><SPAN> raster. </SPAN></P></LI><LI><P><SPAN>Select locations from the LMI raster that have LMI values greater than the LMI threshold. These locations (areas) are regarded as the remaining parts of bathymetric high features.</SPAN></P></LI><LI><P><SPAN>Merge the 'core' areas and the 'remaining' parts of bathymetric high features to form individual bathymetric high features.</SPAN></P></LI><LI><P><SPAN>Remove </SPAN><SPAN>the </SPAN><SPAN>feature </SPAN><SPAN>polygons with areas smaller than the "Area Threshold" parameter</SPAN><SPAN> to obtain the final set of bathymetric high features.</SPAN><SPAN> </SPAN></P></LI></OL><P><SPAN>The TPI radius should be large enough to capture the largest bathymetric high features in the dataset. For example, for a 5m resolution bathymetry raster, a radius of 50 cells should be used to capture any bathymetric high features that is smaller than 500 m in length. Users should also experiment the "TPI STD Scale</SPAN><SPAN> Large</SPAN><SPAN>"</SPAN><SPAN>, the "TPI STD Scale Small", the "LMI STD Scale"</SPAN><SPAN> and the "Area Threshold" parameters to obtain an optimal output solution. </SPAN></P><P><SPAN>Moran, P.A.P., 1950. Notes on continuous stochastic phenomena, Biometrica, 37, 17-33.</SPAN></P><P><SPAN><SPAN>Weiss, A.D. (2001). Topographic Position and Landforms Analysis. In, </SPAN></SPAN><SPAN STYLE="font-style:italic;"><SPAN>ESRI International User Conference</SPAN></SPAN><SPAN>. San Diego, CA</SPAN></P></DIV></DIV></DIV></summary><scriptExamples><scriptExample><title>Python script code sample</title><code>import arcpy
from arcpy import env
from arcpy.sa import *
arcpy.CheckOutExtension("Spatial")
# import the python toolbox
arcpy.ImportToolbox("C:/semi_automation_tools/User_Guide/Tools/BathymetricHigh.pyt")
env.workspace = 'C:/semi_automation_tools/testSampleCode/Gifford.gdb'
env.overwriteOutput = True
# specify input and output parameters of the tool
inBathy = 'gifford_bathy'
outTPI = 'gifford_tpi100'
outFeat = 'tpi100_1_05std_lmi_1std_30km2_BH'
areaT = '30 SquareKilometers'
tpiRadius = 100
tpiSTDLarge = 1.0
tpiSTDSmall = 0.5
weightFile = 'C:/semi_automation_tools/User_Guide/Tools/weight_3.txt'
lmiSTD = 1.0
tempWorkspace = 'C:/Users/u56061/Documents/ArcGIS/Projects/UserGuide/UserGuide.gdb'
# execute the tool
arcpy.BathymetricHigh.TPI_LMITool(inBathy,outTPI,outFeat,areaT,tpiRadius,tpiSTDLarge,tpiSTDSmall,weightFile,lmiSTD,tempWorkspace)</code></scriptExample></scriptExamples></tool><dataIdInfo><idCitation><resTitle>TPI LMI Tool Bathymetric High</resTitle></idCitation><searchKeys><keyword>This tool maps bathymetric high features from a bathymetric data using a combination of Topographic Position Index (TPI) and Local Moran's I (LMI) method.</keyword></searchKeys><idCredit>(c) Commonwealth of Australia (Geoscience Australia) 2024</idCredit><resConst><Consts><useLimit><DIV STYLE="text-align:Left;"><DIV><P><SPAN><SPAN>Creative Commons Attribution 4.0 International Licence</SPAN></SPAN></P></DIV></DIV></useLimit></Consts></resConst></dataIdInfo><distInfo><distributor><distorFormat><formatName>ArcToolbox Tool</formatName></distorFormat></distributor></distInfo><mdHrLv><ScopeCd value="005"/></mdHrLv><mdDateSt Sync="TRUE">20240624</mdDateSt><Binary><Thumbnail><Data EsriPropertyType="PictureX">/9j/4AAQSkZJRgABAQEAeAB4AAD/2wBDAAMCAgMCAgMDAwMEAwMEBQgFBQQEBQoHBwYIDAoMDAsK
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