ࡱ> wZRoot EntryRoot Entry ~x@Version 8ContentsVATool0 5A  !"$%&'()*+,-./0123456789:;<>?@ABCDEFGHIJKLMNOPQRSTUVWXY\]^_`abcdefghijklmnopqrstuvwxyz{|}~Tool1 -HTool2 RGTool3  >Tool4  FTool5  5ETool6 [PTool7 =%8Tool8  #53Tool9 6hugeFileSortSpatialCoherence huge file sort spatial coherenceThis LAStools pipeline sorts huge LAS or LAZ files into a more coherent point order using a tile-based multi-core pipeline. The input file is first tiled using lastile with the specified tile size. All tiles are then sorted into a spatially coherent z-order (e.g. space-filling curve). The sorted tiles are then merged back into a single file and all temporary tiles are deleted. The LiDAR input can be LAS, LAZ, BIN, SHP, ASC, or TXT. The LiDAR output can be in LAS, LAZ, BIN, or TXT format. 5scripts_pipelines\huge_file_sort_spatial_coherence.pyo1?GW:.N_ input_file input file* +DkbVDEFileFileFile Data Typex/ DING4 L-lazlasbinshptxtascbildtm\:A= DEFileo1?GW:.N_ tile_size tile size* +DkbVGPDoubleDoubleDouble Data Typex/ DAW+OIF)tEL7n]wMgTƻ2@@o1?GW:.N_ bucket_size bucket size* +DkbVGPDoubleDoubleDouble Data Typex/ DAW+OIF)A"[2&j@tEL7n]wMgTƻ2I@o1?GW:.N_corescores* +DkbVGPLongLong Long integer Data Typex/ DAW+OIF)A"[2&?0@G0Lz tGz4gACAo1?GW:.N_empty_temp_directoryempty temp directory* +DkbVDEFolderFolderFolder Data Typex/ DIN 20120326125745001.0TRUE20140518183101ItemDescriptionC:\Program Files (x86)\ArcGIS\help\gpThe input is usually in LAS or LAZ format but also BIN, SHP, TXT, ASC, BIL, or DTM are supported.The input is usually in LAS or LAZ format but also BIN, SHP, TXT, ASC, BIL, or DTM are supported.The size of the temporary tiles that the huge file will be decomposed into. Needs to be small enough such that there are no more than 50 millions points per tile.The size of the temporary tiles that the huge file will be decomposed into. Needs to be small enough such that there are no more than 50 millions points per tile.Within each tile the order is based on a z-ordered spatial sort (i.e. space-filling curve) and the bucket size is the side length of the square units that the points get sorted into. Values should be 5 to 50 times smaller than the tile size.Within each tile the order is based on a z-ordered spatial sort (i.e. space-filling curve) and the bucket size is the side length of the square units that the points get sorted into. Values should be 5 to 50 times smaller than the tile size.The number of cores to use for parallelizing the tile-based multi-core processing. Do not choose more cores than your computer has. The number of cores to use for parallelizing the tile-based multi-core processing. Do not choose more cores than your computer has. An *empty* directory with sufficient storage space that the LAStools pipeline can use to store temporary results.An *empty* directory with sufficient storage space that the LAStools pipeline can use to store temporary results.<DIV STYLE="text-align:Left;"><DIV><P><SPAN>Specifies both, the file name and the format for the generated output LiDAR points. </SPAN></P></DIV></DIV>Specifies the output format. Usually this will be LAZ or LAS but also BIN and various ASCII formats are supported.<DIV STYLE="text-align:Left;"><DIV><P><SPAN>Specifies the output format. Usually this will be the LAS or the LAZ format, but the BIN format and various TXT formats are also supported.</SPAN></P></DIV></DIV>Specifies the output format. Usually this will be LAZ or LAS but also BIN and various ASCII formats are supported.<DIV STYLE="text-align:Left;"><DIV><P><SPAN>If checked, more control information will appear in the console.</SPAN></P></DIV></DIV><DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>Uses lasground.exe to extract the bare-earth by classifying LIDAR points into ground points (class = 2) and unclassified points (class = 1).</SPAN></P><P><SPAN>The LiDAR input can be LAS, LAZ, BIN, SHP, ASC, or TXT. The LiDAR output can be in LAS, LAZ, BIN, or TXT format.</SPAN></P></DIV></DIV></DIV>This LAStools pipeline sorts huge LAS or LAZ files into a more coherent point order using a tile-based multi-core pipeline. The input file is first tiled using lastile with the specified tile size. All tiles are then sorted into a spatially coherent z-order (e.g. space-filling curve). The sorted tiles are then merged back into a single file and all temporary tiles are deleted.huge file sort spatial coherenceMartin Isenburgrapidlasso GmbH010martin@rapidlasso.comMartin Isenburg, LASSO - rapid tools to catch reality, http://rapidlasso.comThis LAStools pipeline sorts huge LAS or LAZ files into a more coherent point order using a tile-based multi-core pipeline. The input file is first tiled using lastile with the specified tile size. All tiles are then sorted into a spatially coherent z-order (e.g. space-filling curve). The sorted tiles are then merged back into a single file and all temporary tiles are deleted.LiDARLASLAZground classificationbare-earth extractionclassificationground filteringThere might be artifacts when using an unlicensed version if you go over the point limits. Watch the control output when LAStools Pipelines are running. The tools will inform you when this happens. Please read the LICENSE.txt file.005LiDARclassificationbare-earthgroundLASLAZlarge filesbig dataArcToolbox Tool class ToolValidator: """Class for validating a tool's parameter values and controlling the behavior of the tool's dialog.""" def __init__(self): """Setup the Geoprocessor and the list of tool parameters.""" import arcgisscripting as ARC self.GP = ARC.create(9.3) self.params = self.GP.getparameterinfo() def initializeParameters(self): """Refine the properties of a tool's parameters. This method is called when the tool is opened.""" return def updateParameters(self): """Modify the values and properties of parameters before internal validation is performed. This method is called whenever a parmater has been changed.""" return def updateMessages(self): """Modify the messages created by internal validation for each tool parameter. This method is called after internal validation.""" return x\de LAS or LAZ files by operating with a chunk-based multi-core pipeline (i.e. bucket sort). The input file is first split into different GPS segments using lassplit withhugeFileSortGpsTimehuge file sort GPS timeThis LAStools pipeline sorts a huge LAS or LAZ files by operating with a chunk-based multi-core pipeline (i.e. bucket sort). The input file is first split into different GPS segments using lassplit with the specified duration in seconds. The points of each chunk are then sorted based on their GPS time stamps. The sorted chunks are then merged back into a single and all temporary chunks are deleted. The LiDAR input can be LAS, LAZ, BIN, SHP, ASC, or TXT. The LiDAR output can be in LAS, LAZ, BIN, or TXT format. ,scripts_pipelines\huge_file_sort_GPS_time.pyo1?GW:.N_ input_file input file* +DkbVDEFileFileFile Data Typex/ DING4 L-lazlasbinshptxtascbildtm\:A= DEFileo1?GW:.N_split_into_chunks_of_n_secondssplit into chunks of n seconds* +DkbVGPDoubleDoubleDouble Data Typex/ DAW+OIF)tEL7n]wMgTƻ2Y@o1?GW:.N_corescores* +DkbVGPLongLong Long integer Data Typex/ DAW+OIF)A"[2&?0@G0Lz tGz4gACAo1?GW:.N_empty_temp_directoryempty temp directory* +DkbVDEFolderFolderFolder Data Typex/ DIN 20120326125745001.0TRUE20140518160413ItemDescriptionC:\Program Files (x86)\ArcGIS\help\gpThe input is usually in LAS or LAZ format but also BIN, SHP, TXT, ASC, BIL, or DTM are supported.The input is usually in LAS or LAZ format but also BIN, SHP, TXT, ASC, BIL, or DTM are supported.The input file is split into chunks containing those points that have similar GPS time stamps. This value specifies how many continuous seconds worth of GPS time goes into each chunk.The input file is split into chunks containing those points that have similar GPS time stamps. This value specifies how many continuous seconds worth of GPS time goes into each chunk.The number of cores to use for parallelizing the tile-based multi-core processing. Do not choose more cores than your computer has. The number of cores to use for parallelizing the tile-based multi-core processing. Do not choose more cores than your computer has. An *empty* directory with sufficient storage space that the LAStools pipeline can use to store temporary results.An *empty* directory with sufficient storage space that the LAStools pipeline can use to store temporary results.<DIV STYLE="text-align:Left;"><DIV><P><SPAN>Specifies both, the file name and the format for the generated output LiDAR points. </SPAN></P></DIV></DIV>Specifies the output format. Usually this will be LAZ or LAS but also BIN and various ASCII formats are supported.<DIV STYLE="text-align:Left;"><DIV><P><SPAN>Specifies the output format. Usually this will be the LAS or the LAZ format, but the BIN format and various TXT formats are also supported.</SPAN></P></DIV></DIV>Specifies the output format. Usually this will be LAZ or LAS but also BIN and various ASCII formats are supported.<DIV STYLE="text-align:Left;"><DIV><P><SPAN>If checked, more control information will appear in the console.</SPAN></P></DIV></DIV><DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>Uses lasground.exe to extract the bare-earth by classifying LIDAR points into ground points (class = 2) and unclassified points (class = 1).</SPAN></P><P><SPAN>The LiDAR input can be LAS, LAZ, BIN, SHP, ASC, or TXT. The LiDAR output can be in LAS, LAZ, BIN, or TXT format.</SPAN></P></DIV></DIV></DIV>This LAStools pipeline sorts a huge LAS or LAZ files by operating with a chunk-based multi-core pipeline (i.e. bucket sort). The input file is first split into different GPS segments using lassplit with the specified duration in seconds. The points of each chunk are then sorted based on their GPS time stamps. The sorted chunks are then merged back into a single and all temporary chunks are deleted.huge file sort GPS timeMartin Isenburgrapidlasso GmbH010martin@rapidlasso.comMartin Isenburg, LASSO - rapid tools to catch reality, http://rapidlasso.comThis LAStools pipeline sorts a huge LAS or LAZ files by operating with a chunk-based multi-core pipeline (i.e. bucket sort). The input file is first split into different GPS segments using lassplit with the specified duration in seconds. The points of each chunk are then sorted based on their GPS time stamps. The sorted chunks are then merged back into a single and all temporary chunks are deleted.LiDARLASLAZground classificationbare-earth extractionclassificationground filteringThere might be artifacts when using an unlicensed version if you go over the point limits. Watch the control output when LAStools Pipelines are running. The tools will inform you when this happens. Please read the LICENSE.txt file.005LiDARclassificationbare-earthgroundLASLAZlarge filesbig dataArcToolbox Tool class ToolValidator: """Class for validating a tool's parameter values and controlling the behavior of the tool's dialog.""" def __init__(self): """Setup the Geoprocessor and the list of tool parameters.""" import arcgisscripting as ARC self.GP = ARC.create(9.3) self.params = self.GP.getparameterinfo() def initializeParameters(self): """Refine the properties of a tool's parameters. This method is called when the tool is opened.""" return def updateParameters(self): """Modify the values and properties of parameters before internal validation is performed. This method is called whenever a parmater has been changed.""" return def updateMessages(self): """Modify the messages created by internal validation for each tool parameter. This method is called after internal validation.""" return x\d a tile-based multi-core pipeline. The input file is first tiled using lastile with the specified tilhugeFileRemoveDuplicateshuge file remove duplicatesThis LAStools pipeline removes duplicate points from huge LAS or LAZ files by operating with a tile-based multi-core pipeline. The input file is first tiled using lastile with the specified tile size. All tiles are then checked for XY or XYZ duplicates which are then deleted. The remaining points are merged back into a single file in their original order and all temporary tiles are deleted. The LiDAR input can be LAS, LAZ, BIN, SHP, ASC, or TXT. The LiDAR output can be in LAS, LAZ, BIN, or TXT format. 0scripts_pipelines\huge_file_remove_duplicates.pyo1?GW:.N_ input_file input file* +DkbVDEFileFileFile Data Typex/ DING4 L-lazlasbinshptxtascbildtm\:A= DEFileo1?GW:.N_ tile_size tile size* +DkbVGPDoubleDoubleDouble Data Typex/ DAW+OIF)tEL7n]wMgTƻ2@@o1?GW:.N_modemode* +DkbVGPStringStringString Data Typex/ DAW+OIF)qfK5Ydefaultlowest_zunique_xyz34jgJ$ default34jgJ$ lowest_z34jgJ$ unique_xyz34jgJ$ defaulto1?GW:.N_corescores* +DkbVGPLongLong Long integer Data Typex/ DAW+OIF)A"[2&?0@G0Lz tGz4gACAo1?GW:.N_empty_temp_directoryempty temp directory* +DkbVDEFolderFolderFolder Data Typex/ DIN 20120326125745001.0TRUE20140518183555ItemDescriptionC:\Program Files (x86)\ArcGIS\help\gpThe input is usually in LAS or LAZ format but also BIN, SHP, TXT, ASC, BIL, or DTM are supported.The input is usually in LAS or LAZ format but also BIN, SHP, TXT, ASC, BIL, or DTM are supported.The size of the temporary tiles that the huge file will be decomposed into. Needs to be small enough such that there are no more than 50 millions points per tile.The size of the temporary tiles that the huge file will be decomposed into. Needs to be small enough such that there are no more than 50 millions points per tile.By default all points are removed that have the same X and Y coordinates. And by default the first occurance is kept. Select mode 'lowest_z' to keep the point with the lowest Z coordinate from all points with the same X and Y coordinates. Select mode 'unique_xyz' to only remove points that have the same X, Y, and Z coordinates.By default all points are removed that have the same X and Y coordinates. And by default the first occurance is kept. Select mode 'lowest_z' to keep the point with the lowest Z coordinate from all points with the same X and Y coordinates. Select mode 'unique_xyz' to only remove points that have the same X, Y, and Z coordinates.The number of cores to use for parallelizing the tile-based multi-core processing. Do not choose more cores than your computer has. The number of cores to use for parallelizing the tile-based multi-core processing. Do not choose more cores than your computer has. An *empty* directory with sufficient storage space that the LAStools pipeline can use to store temporary results.An *empty* directory with sufficient storage space that the LAStools pipeline can use to store temporary results.<DIV STYLE="text-align:Left;"><DIV><P><SPAN>Specifies both, the file name and the format for the generated output LiDAR points. </SPAN></P></DIV></DIV>Specifies the output format. Usually this will be LAZ or LAS but also BIN and various ASCII formats are supported.<DIV STYLE="text-align:Left;"><DIV><P><SPAN>Specifies the output format. Usually this will be the LAS or the LAZ format, but the BIN format and various TXT formats are also supported.</SPAN></P></DIV></DIV>Specifies the output format. Usually this will be LAZ or LAS but also BIN and various ASCII formats are supported.<DIV STYLE="text-align:Left;"><DIV><P><SPAN>If checked, more control information will appear in the console.</SPAN></P></DIV></DIV><DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>Uses lasground.exe to extract the bare-earth by classifying LIDAR points into ground points (class = 2) and unclassified points (class = 1).</SPAN></P><P><SPAN>The LiDAR input can be LAS, LAZ, BIN, SHP, ASC, or TXT. The LiDAR output can be in LAS, LAZ, BIN, or TXT format.</SPAN></P></DIV></DIV></DIV>This LAStools pipeline removes duplicate points from huge LAS or LAZ files by operating with a tile-based multi-core pipeline. The input file is first tiled using lastile with the specified tile size. All tiles are then checked for XY or XYZ duplicates which are then deleted. The remaining points are merged back into a single file in their original order and all temporary tiles are deleted.huge file remove duplicatesMartin Isenburgrapidlasso GmbH010martin@rapidlasso.comMartin Isenburg, LASSO - rapid tools to catch reality, http://rapidlasso.comThis LAStools pipeline removes duplicate points from huge LAS or LAZ files by operating with a tile-based multi-core pipeline. The input file is first tiled using lastile with the specified tile size. All tiles are then checked for XY or XYZ duplicates which are then deleted. The remaining points are merged back into a single file in their original order and all temporary tiles are deleted.LiDARLASLAZground classificationbare-earth extractionclassificationground filteringThere might be artifacts when using an unlicensed version if you go over the point limits. Watch the control output when LAStools Pipelines are running. The tools will inform you when this happens. Please read the LICENSE.txt file.005LiDARclassificationbare-earthgroundLASLAZlarge filesbig dataArcToolbox Tool class ToolValidator: """Class for validating a tool's parameter values and controlling the behavior of the tool's dialog.""" def __init__(self): """Setup the Geoprocessor and the list of tool parameters.""" import arcgisscripting as ARC self.GP = ARC.create(9.3) self.params = self.GP.getparameterinfo() def initializeParameters(self): """Refine the properties of a tool's parameters. This method is called when the tool is opened.""" return def updateParameters(self): """Modify the values and properties of parameters before internal validation is performed. This method is called whenever a parmater has been changed.""" return def updateMessages(self): """Modify the messages created by internal validation for each tool parameter. This method is called after internal validation.""" return x\dflightlinesQualityReportflightlines quality reportGThis LAStools pipeline classifies very large LAS or LAZ files with tile-based multi-core processing.The input file is first tiled using lastile with the specified tile size. The specified buffer is used to avoid edge artifacts. All tiles are then ground classified using lasground marking points as ground (class 2) and non-gound (class 1). Next the height of all points above the ground is computed using lasheight with an optional removal of points above a specified height. Then buildings and vegetation are classified using lasclassify. Finally the processed tiles are rejoined back into a single file with points in their original order and all temporary files are deleted. The LiDAR input can be LAS, LAZ, BIN, SHP, BIL, ASC, DTM, or TXT. The raster output can be in TIF/IMG/BIL/ASC/XYZ format. The LiDAR output can be in LAS/LAZ./scripts_pipelines\flightlines_quality_report.py o1?GW:.N_ input_folder input folder* +DkbVDEFolderFolderFolder Data Typex/ DING4 L-xml\:A= validate.xmlvalidate.xmlDEFileo1?GW:.N_lasinfo_reportlasinfo report* +DkbVDEFileFileFile Data Typex/ DING4 L-txt\:A= info.txtinfo.txtDEFileo1?GW:.N_overlap_rasteroverlap raster* +DkbVDEFileFileFile Data Typex/ DING4 L-pngjpgtif\:A= overlap.pngoverlap.pngDEFileo1?GW:.N_expected_density_rasterexpected density raster* +DkbVDEFileFileFile Data Typex/ DING4 L-pngjpgtif\:A= *density_expected.png*density_expected.pngDEFileo1?GW:.N_excessive_density_rasterexcessive density raster* +DkbVDEFileFileFile Data Typex/ DING4 L-pngjpgtif\:A= ,density_excessive.png,density_excessive.pngDEFileo1?GW:.N_boundary_polygonboundary polygon* +DkbVDEFileFileFile Data Typex/ DING4 L-shptxtkml\:A= boundary.shpboundary.shpDEFileo1?GW:.N_verboseverbose* +DkbV GPBooleanBooleanBoolean data type Data Typex/ DAW+OIF)Yf^EkI6* 20120326125745001.0TRUE20140518115609ItemDescriptionC:\Program Files (x86)\ArcGIS\help\gpThe input directory that contains the raw flightlines in LAS or LAZ format.The input directory that contains the raw flightlines in LAS or LAZ format.The step size use for overlap and density rasters. Should be chosen such that there are at least expected 4 pulses per area (step x step).The step size use for overlap and density rasters. Should be chosen such that there are at least expected 4 pulses per area (step x step).The lowest LiDAR point of each flightline per area (step by step) is compared to the lowest point of all other flightlines covering the same area and the largest difference is color coded from plus this value (red) to minus this value (blue) with white meaning a perfect match (zero difference). Setting this value to 0.3, for example, lets elevation differences of 30 centimeter between the lowest point of each flightline in the same area show up as saturated red or saturated blue.The lowest LiDAR point of each flightline per area (step by step) is compared to the lowest point of all other flightlines covering the same area and the largest difference is color coded from plus this value (red) to minus this value (blue) with white meaning a perfect match (zero difference). Setting this value to 0.3, for example, lets elevation differences of 30 centimeter between the lowest point of each flightline in the same area show up as saturated red or saturated blue.The number of pulses per area (step by step) are counted by counting how many last returns are falling into each area. This number is then color coded with blue meaning zero pulses and red meaning the expected number of pulses specified here. The resulting image should be mostly red to fulfill the expected pulse density.The number of pulses per area (step by step) are counted by counting how many last returns are falling into each area. This number is then color coded with blue meaning zero pulses and red meaning the expected number of pulses specified here. The resulting image should be mostly red to fulfill the expected pulse density.The number of pulses per area (step by step) are counted by counting how many last returns are falling into each area. This number is then color coded with blue meaning zero pulses and red meaning the excessive number of pulses specified here. If the resulting image is mostly red, then the pulse density is excessive.The number of pulses per area (step by step) are counted by counting how many last returns are falling into each area. This number is then color coded with blue meaning zero pulses and red meaning the excessive number of pulses specified here. If the resulting image is mostly red, then the pulse density is excessive.The directory where all outputs are stored to.The directory where all outputs are stored to.The name of the XML file storing the lasvalidate report.The name of the XML file storing the lasvalidate report.The name of the TXT file storing the lasinfo report.The name of the TXT file storing the lasinfo report.The name of the image files storing the overlap visualizations.The name of the image files storing the overlap visualizations.The name of the image file storing the expected density visualization.The name of the image file storing the expected density visualization.The name of the image file storing the excessive density visualization.The name of the image file storing the excessive density visualization.The name of the polygon file storing the boundary polygon.The name of the polygon file storing the boundary polygon.<DIV STYLE="text-align:Left;"><DIV><P><SPAN>If checked, more control information will appear in the console.</SPAN></P></DIV></DIV><DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>Uses lastile.exe to tile a (potentially very large) LiDAR file into a number of square non-overlapping tiles of a user specified size. There is the option to also add a (removable) buffer around each tile.</SPAN></P><P><SPAN>The LiDAR input can be LAS, LAZ, BIN, SHP, ASC, or TXT. The LiDAR output can be in LAS, LAZ, BIN, or TXT format.</SPAN></P></DIV></DIV></DIV>This LAStools pipeline creates a quality report for a folder of LAS or LAZ files that are expected to contain flightlines. Produced are a validation report, a lasinfo report, visual overlap images detailing coverage and alignment of flightlines, visual density images to check the point distribution, and a polygonal boundary around the entire set of LiDAR points including potential holes.The LiDAR input can be LAS or LAZ.The output areTXT and XML files for the text, PNG, TIF, or JPG for the images, and SHP, WKT, KML, or TXT for the polygonal boundary.flightlines quality reportMartin Isenburgrapidlasso GmbH010martin@rapidlasso.comMartin Isenburg, LASSO - rapid tools to catch reality, http://rapidlasso.comThis LAStools pipeline creates a quality report for a folder of LAS or LAZ files that are expected to contain flightlines. Produced are a validation report, a lasinfo report, visual overlap images detailing coverage and alignment of flightlines, visual density images to check the point distribution, and a polygonal boundary around the entire set of LiDAR points including potential holes.LiDARLASLAZtilingtilesclippingbufferbufferedsmaller filessplitting.There might be artifacts when using an unlicensed version if you go over the point limits. Watch the control output when LAStools Pipelines are running. The tools will inform you when this happens. Please read the LICENSE.txt file.005LiDARDTMDSMclassificationbare-earthLASLAZflightlineslarge filesbig dataArcToolbox Tool class ToolValidator: """Class for validating a tool's parameter values and controlling the behavior of the tool's dialog.""" def __init__(self): """Setup the Geoprocessor and the list of tool parameters.""" import arcgisscripting as ARC self.GP = ARC.create(9.3) self.params = self.GP.getparameterinfo() def initializeParameters(self): """Refine the properties of a tool's parameters. This method is called when the tool is opened.""" return def updateParameters(self): """Modify the values and properties of parameters before internal validation is performed. This method is called whenever a parmater has been changed.""" return def updateMessages(self): """Modify the messages created by internal validation for each tool parameter. This method is called after internal validation.""" return x\d1excessive_number_of_pulses_per_area__step_x_step_8expected_density_rasterdensity_expected.pnghis LAStools pipeline turns a folder full of LAS or LAZ files (assumed to be raw flightlines) into a single pit-free CHM using the algorithms described by A. Khosravipour et al. flightlinesToSingleCHMpitFree$flightlines to single CHM (pit-free) This LAStools pipeline turns a folder full of LAS or LAZ files (assumed to be raw flightlines) into a single pit-free CHM using the algorithms described by A. Khosravipour et al. in Silvilaser 2013. The input file is first tiled using lastile with the specified tile size. The specified buffer is used to avoid edge artifacts. All tiles are then ground classified using lasground marking points as ground (class 2) and non-gound (class 1). Next the height of all points above the ground is computed using lasheight and used to height-normalize all the tiles in the sense that the height is used to replace the z coordinates. Using lasthin the tiles are then both thinned and splatted using the laser beam with in an attempt to widen the LiDAR returns a little bit. From these height-normalized and point-splatted tiles the partial CHMs are computed (as detailed in the poster, the extended abstract, and the paper) that are merged into a single CHM in the final step. LiDAR input: LAS/LAZ rasteroutput: TIF/IMG/BIL/DTM/ASC/FLT/XYZ7scripts_pipelines\flightlines_to_single_CHM_pit_free.py o1?GW:.N_ input_folder input folder* +DkbVDEFolderFolderFolder Data Typex/ DING4 L-tifimgbildtmascfltxyz\:A= DEFileo1?GW:.N_verboseverbose* +DkbV GPBooleanBooleanBoolean data type Data Typex/ DAW+OIF)Yf^EkI-$ 20120326125745001.0TRUE20140602214333ItemDescriptionC:\Program Files (x86)\ArcGIS\help\gpThe input directory that contains the raw flightlines in LAS or LAZ format.The input directory that contains the raw flightlines in LAS or LAZ format.The size of the temporary tiles that the flightlines will be tiled into. Needs to be small enough such that there are no more than 15 millions points per tile.<DIV STYLE="text-align:Left;"><DIV><P><SPAN>Specifies the square size of each tile in x and y direction using whatever units the input LiDAR file is in.</SPAN></P></DIV></DIV>The size of the temporary tiles that the flightlines will be tiled into. Needs to be small enough such that there are no more than 15 millions points per tile.The buffer size in units around each tile (to avoid edge artifacts along the tile boundaries).<DIV STYLE="text-align:Left;"><DIV><P><SPAN>Specifies an additional buffer around each tile. The buffer must be smaller than the tile size.</SPAN></P></DIV></DIV>The buffer size in units around each tile (to avoid edge artifacts along the tile boundaries).Describes the terrain and how large the expected man-made objects are. See the README file of lasground for what these options mean exactly.Describes the terrain and how large the expected man-made objects are. See the README file of lasground for what these options mean exactly.The approximate width of the laser beam (or smaller) when it hits the canopy.The approximate width of the laser beam (or smaller) when it hits the canopy.The resolution (e.g. gid cell size) of the produced CHM rasters.The resolution (e.g. gid cell size) of the produced CHM rasters.The number of cores to use for parallelizing the tile-based multi-core processing. Do not choose more cores than your computer has.The number of cores to use for parallelizing the tile-based multi-core processing. Do not choose more cores than your computer has.An (empty) directory for storing temporary files.An (empty) directory for storing temporary files.<DIV STYLE="text-align:Left;"><DIV><P><SPAN>If checked, more control information will appear in the console.</SPAN></P></DIV></DIV><DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>Uses lastile.exe to tile a (potentially very large) LiDAR file into a number of square non-overlapping tiles of a user specified size. There is the option to also add a (removable) buffer around each tile.</SPAN></P><P><SPAN>The LiDAR input can be LAS, LAZ, BIN, SHP, ASC, or TXT. The LiDAR output can be in LAS, LAZ, BIN, or TXT format.</SPAN></P></DIV></DIV></DIV>This LAStools pipeline turns a folder full of LAS or LAZ files (assumed to be raw flightlines) into a single pit-free CHM using the algorithms described by A. Khosravipour et al. in Silvilaser 2013. The input file is first tiled using lastile with the specified tile size. The specified buffer is used to avoid edge artifacts. All tiles are then ground classified using lasground marking points as ground (class 2) and non-gound (class 1). Next the height of all points above the ground is computed using lasheight and used to height-normalize all the tiles in the sense that the height is used to replace the z coordinates. Using lasthin the tiles are then both thinned and splatted using the laser beam with in an attempt to widen the LiDAR returns a little bit. From these height-normalized and point-splatted tiles the partial CHMs are computed (as detailed in the poster, the extended abstract, and the paper) that are merged into a single CHM in the final step.LiDAR input: LAS/LAZ raster output: TIF/IMG/BIL/DTM/ASC/FLT/XYZflightlines to single CHM (pit-free)Martin Isenburgrapidlasso GmbH010martin@rapidlasso.comMartin Isenburg, LASSO - rapid tools to catch reality, http://rapidlasso.comThis LAStools pipeline turns a folder full of LAS or LAZ files (assumed to be raw flightlines) into a single pit-free CHM using the algorithms described by A. Khosravipour et al. in Silvilaser 2013. The input file is first tiled using lastile with the specified tile size. The specified buffer is used to avoid edge artifacts. All tiles are then ground classified using lasground marking points as ground (class 2) and non-gound (class 1). Next the height of all points above the ground is computed using lasheight and used to height-normalize all the tiles in the sense that the height is used to replace the z coordinates. Using lasthin the tiles are then both thinned and splatted using the laser beam with in an attempt to widen the LiDAR returns a little bit. From these height-normalized and point-splatted tiles the partial CHMs are computed (as detailed in the poster, the extended abstract, and the paper) that are merged into a single CHM in the final step.LiDARLASLAZtilingtilesclippingbufferbufferedsmaller filessplitting.There might be artifacts when using an unlicensed version if you go over the point limits. Watch the control output when LAStools Pipelines are running. The tools will inform you when this happens. Please read the LICENSE.txt file.005LiDARDTMDSMclassificationbare-earthLASLAZflightlineslarge filesbig dataArcToolbox Tool class ToolValidator: """Class for validating a tool's parameter values and controlling the behavior of the tool's dialog.""" def __init__(self): """Setup the Geoprocessor and the list of tool parameters.""" import arcgisscripting as ARC self.GP = ARC.create(9.3) self.params = self.GP.getparameterinfo() def initializeParameters(self): """Refine the properties of a tool's parameters. This method is called when the tool is opened.""" return def updateParameters(self): """Modify the values and properties of parameters before internal validation is performed. This method is called whenever a parmater has been changed.""" return def updateMessages(self): """Modify the messages created by internal validation for each tool parameter. This method is called after internal validation.""" return x\dof tiled CHMs using a simple splatting and rasterization algorithm. The input file is tiled using lasflightlinesToCHMflightlines to CHMThis LAStools pipeline turns a folder full of LAS or LAZ files (assumed to be raw flightlines) into a folder of tiled CHMs using a simple splatting and rasterization algorithm. The input file is tiled using lastile with the specified tile size. The specified buffer is used to avoid edge artifacts. All tiles are then ground classified using lasground marking points as ground (class 2) and non-ground (class 1). Next the height of all points above the ground is computed using lasheight and used to height-normalize all the tiles in the sense that the height is used to replace the z coordinates. Using lasthin the tiles are then both thinned and splatted keeping the highest returns on a subgrid while using the laser beam width in an attempt to widen the LiDAR returns a little bit. From these height-normalized and point-splatted tiles containing the highest return on a subgrid the CHMs are computed by sampling a TIN from all the remaining points at the requested step size. LiDAR input: LAS/LAZ raster output: TIF/IMG/BIL/DTM/ASC/FLT/XYZ'scripts_pipelines\flightlines_to_CHM.py o1?GW:.N_ input_folder input folder* +DkbVDEFolderFolderFolder Data Typex/ DIN 20120326125745001.0TRUE20140602214227ItemDescriptionC:\Program Files (x86)\ArcGIS\help\gpThe input directory that contains the raw flightlines in LAS or LAZ format.The input directory that contains the raw flightlines in LAS or LAZ format.The size of the tiles that the flightlines will be tiled into. Needs to be small enough such that there are no more than 15 millions points per tile.<DIV STYLE="text-align:Left;"><DIV><P><SPAN>Specifies the square size of each tile in x and y direction using whatever units the input LiDAR file is in.</SPAN></P></DIV></DIV>The size of the tiles that the flightlines will be tiled into. Needs to be small enough such that there are no more than 15 millions points per tile.<DIV STYLE="text-align:Left;"><DIV><P><SPAN>Specifies an additional buffer around each tile. The buffer must be smaller than the tile size.</SPAN></P></DIV></DIV>The number of cores to use for parallelizing the tile-based multi-core processing. Do not choose more cores than your computer has.The number of cores to use for parallelizing the tile-based multi-core processing. Do not choose more cores than your computer has.The directory where all outputs are stored to.The directory where all outputs are stored to.<DIV STYLE="text-align:Left;"><DIV><P><SPAN>If checked, more control information will appear in the console.</SPAN></P></DIV></DIV><DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>Uses lastile.exe to tile a (potentially very large) LiDAR file into a number of square non-overlapping tiles of a user specified size. There is the option to also add a (removable) buffer around each tile.</SPAN></P><P><SPAN>The LiDAR input can be LAS, LAZ, BIN, SHP, ASC, or TXT. The LiDAR output can be in LAS, LAZ, BIN, or TXT format.</SPAN></P></DIV></DIV></DIV>This LAStools pipeline turns a folder full of LAS or LAZ files (assumed to raw flightlines) into a folder of tiled CHMs using a simple splatting and rasterization algorithm. The input file is tiled using lastile with the specified tile size. The specified buffer is used to avoid edge artifacts. All tiles are then ground classified using lasground marking points as ground (class 2) and non-ground (class 1). Next the height of all points above the ground is computed using lasheight and used to height-normalize all the tiles in the sense that the height is used to replace the z coordinates. Using lasthin the tiles are then both thinned and splatted keeping the highest returns on a subgrid while using the laser beam width in an attempt to widen the LiDAR returns a little bit. From these height-normalized and point-splatted tiles containing the highest return on a subgrid the CHMs are computed by sampling a TIN from all the remaining points at the requested step size.LiDAR input: LAS/LAZraster output: TIF/IMG/BIL/DTM/ASC/FLT/XYZflightlines to CHMMartin Isenburgrapidlasso GmbH010martin@rapidlasso.comMartin Isenburg, LASSO - rapid tools to catch reality, http://rapidlasso.comThis LAStools pipeline turns a folder full of LAS or LAZ files (assumed to raw flightlines) into a folder of tiled CHMs using a simple splatting and rasterization algorithm. The input file is tiled using lastile with the specified tile size. The specified buffer is used to avoid edge artifacts. All tiles are then ground classified using lasground marking points as ground (class 2) and non-ground (class 1). Next the height of all points above the ground is computed using lasheight and used to height-normalize all the tiles in the sense that the height is used to replace the z coordinates. Using lasthin the tiles are then both thinned and splatted keeping the highest returns on a subgrid while using the laser beam width in an attempt to widen the LiDAR returns a little bit. From these height-normalized and point-splatted tiles containing the highest return on a subgrid the CHMs are computed by sampling a TIN from all the remaining points at the requested step size.LiDARLASLAZtilingtilesclippingbufferbufferedsmaller filessplitting.There might be artifacts when using an unlicensed version if you go over the point limits. Watch the control output when LAStools Pipelines are running. The tools will inform you when this happens. Please read the LICENSE.txt file.005LiDARDTMDSMclassificationbare-earthLASLAZflightlineslarge filesbig dataArcToolbox Tool class ToolValidator: """Class for validating a tool's parameter values and controlling the behavior of the tool's dialog.""" def __init__(self): """Setup the Geoprocessor and the list of tool parameters.""" import arcgisscripting as ARC self.GP = ARC.create(9.3) self.params = self.GP.getparameterinfo() def initializeParameters(self): """Refine the properties of a tool's parameters. This method is called when the tool is opened.""" return def updateParameters(self): """Modify the values and properties of parameters before internal validation is performed. This method is called whenever a parmater has been changed.""" return def updateMessages(self): """Modify the messages created by internal validation for each tool parameter. This method is called after internal validation.""" return x\dflightlinesToDTMandDSMflightlines to DTM and DSMStarting from a folder of raw LiDAR flight lines in LAS or LAZ format, this pipeline uses several modules of the LAStools Production toolbox to tile and ground classify the raw LiDAR and generate flightlinesToDTMandDSMflightlines to DTM and DSMStarting from a folder of raw LiDAR flight lines in LAS or LAZ format, this pipeline uses several modules of the LAStools Production toolbox to tile and ground classify the raw LiDAR and generate DTM and DSM raster outputs in various formats as well as classified LAS or LAZ tiles./scripts_pipelines\flightlines_to_DTM_and_DSM.py o1?GW:.N_ input_folder input folder* +DkbVDEFolderFolderFolder Data Typex/ DIN 20120326125745001.0TRUE20140602214307ItemDescriptionC:\Program Files (x86)\ArcGIS\help\gpThe input folder containing the raw flightlines in LAS or LAZ format.The input folder containing the raw flightlines in LAS or LAZ format.The size of the tiles that the flightlines will be tiled into. Needs to be small enough such that there are no more than 15 millions points per tile.<DIV STYLE="text-align:Left;"><DIV><P><SPAN>Specifies the square size of each tile in x and y direction using whatever units the input LiDAR file is in.</SPAN></P></DIV></DIV>The size of the tiles that the flightlines will be tiled into. Needs to be small enough such that there are no more than 15 millions points per tile.The buffer around each tile used to avoid edge artifacts. Should correspond more or less to the horizontal extent of the largest building in the surveyed area.<DIV STYLE="text-align:Left;"><DIV><P><SPAN>Specifies an additional buffer around each tile. The buffer must be smaller than the tile size.</SPAN></P></DIV></DIV>The buffer around each tile used to avoid edge artifacts. Should correspond more or less to the horizontal extent of the largest building in the surveyed area.The resolution of the generated rasters.The resolution of the generated rasters.The number of cores to use for parallelizing the tile-based multi-core processing. Do not choose more cores than your computer has.The number of cores to use for parallelizing the tile-based multi-core processing. Do not choose more cores than your computer has.The directory where all outputs are stored to.The directory where all outputs are stored to.The file format that the generated rasters will be stored as. Should be TIF, BIL, IMG, ASC, or DTM.The file format that the generated rasters will be stored as. Should be TIF, BIL, IMG, ASC, or DTM.The file format that the generated LiDAR tiles will be stored as. Should be LAZ or LAS.The file format that the generated LiDAR tiles will be stored as. Should be LAZ or LAS.<DIV STYLE="text-align:Left;"><DIV><P><SPAN>If checked, more control information will appear in the console.</SPAN></P></DIV></DIV><DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>Uses lastile.exe to tile a (potentially very large) LiDAR file into a number of square non-overlapping tiles of a user specified size. There is the option to also add a (removable) buffer around each tile.</SPAN></P><P><SPAN>The LiDAR input can be LAS, LAZ, BIN, SHP, ASC, or TXT. The LiDAR output can be in LAS, LAZ, BIN, or TXT format.</SPAN></P></DIV></DIV></DIV>Starting from a folder of raw LiDAR flight lines in LAS or LAZ format, this pipeline uses several modules of the LAStools Production toolbox to tile and ground classify the raw LiDAR and generate DTM and DSM raster outputs in various formats as well as classified LAS or LAZ tiles.flightlines to DTM and DSMMartin Isenburgrapidlasso GmbH010martin@rapidlasso.comMartin Isenburg, LASSO - rapid tools to catch reality, http://rapidlasso.comStarting from a folder of raw LiDAR flight lines in LAS or LAZ format, this pipeline uses several modules of the LAStools Production toolbox to tile and ground classify the raw LiDAR and generate DTM and DSM raster outputs in various formats as well as classified LAS or LAZ tiles.LiDARLASLAZtilingtilesclippingbufferbufferedsmaller filessplitting.There might be artifacts when using an unlicensed version if you go over the point limits. Watch the control output when LAStools Pipelines are running. The tools will inform you when this happens. Please read the LICENSE.txt file.005LiDARDTMDSMclassificationbare-earthLASLAZflightlineslarge filesbig dataArcToolbox Tool class ToolValidator: """Class for validating a tool's parameter values and controlling the behavior of the tool's dialog.""" def __init__(self): """Setup the Geoprocessor and the list of tool parameters.""" import arcgisscripting as ARC self.GP = ARC.create(9.3) self.params = self.GP.getparameterinfo() def initializeParameters(self): """Refine the properties of a tool's parameters. This method is called when the tool is opened.""" return def updateParameters(self): """Modify the values and properties of parameters before internal validation is performed. This method is called whenever a parmater has been changed.""" return def updateMessages(self): """Modify the messages created by internal validation for each tool parameter. This method is called after internal validation.""" return x\dverboseFalse)*+,-./012356789:;<=>?@ABCDEFGHIJKLMNOPQRSTVWXYZ[\]^_`abcdefghijklmnopqrstu      !"#$%&'()*+,-./012346789:;<=>?@ABCDEFGHIJKLMNOPQRSTUWXYZ[\]^_`abcdefghijklmnopqrstuvhugeFileNomalizehuge file normalizeThis LAStools pipeline height-normalizes very large LAS or LAZ files by operating with a tile-based multi-core pipeline. The input file is first tiled using lastile with the specified tile size and the specified buffer around each tile to avoid edge artifacts. These tiles are then ground-classified using lasground on as many cores as specified. The tiles are then height-normalized using lasheight with optional removal of points that are too high above or too far below the ground points. Finally the height-normalized tiles are rejoined back into a single file with points in their original order and all temporary files are deleted. . The LiDAR input can be LAS, LAZ, BIN, SHP, ASC, or TXT. The LiDAR output can be in LAS, LAZ, BIN, or TXT format.(scripts_pipelines\huge_file_normalize.py o1?GW:.N_ input_file input file* +DkbVDEFileFileFile Data Typex/ DING4 L-lazlasbinshptxtascbildtm\:A= DEFileo1?GW:.N_ tile_size tile size* +DkbVGPDoubleDoubleDouble Data Typex/ DAW+OIF)tEL7n]wMgTƻ2@@o1?GW:.N_bufferbuffer* +DkbVGPDoubleDoubleDouble Data Typex/ DAW+OIF)tEL7n]wMgTƻ29@o1?GW:.N_ terrain_type terrain type* +DkbVGPStringStringString Data Typex/ DAW+OIF)qfK5Ywilderness forest or hillstowns or flats&city or warehousesmetropolis34jgJ$ wilderness34jgJ$  forest or hills34jgJ$ towns or flats34jgJ$ &city or warehouses34jgJ$ metropolis34jgJ$  forest or hillso1?GW:.N_ granularity granularity* +DkbVGPStringStringString Data Typex/ DAW+OIF)qfK5Ydefault fineextra fineultra fine34jgJ$ default34jgJ$  fine34jgJ$ extra fine34jgJ$ ultra fine34jgJ$  fineo1?GW:.N_drop_points_with_height_abovedrop points with height above* +DkbVGPDoubleDoubleDouble Data Typex/ DAW+OIF)tEL7n]wMgTƻ2o1?GW:.N_drop_points_with_height_belowdrop points with height below* +DkbVGPDoubleDoubleDouble Data Typex/ DAW+OIF)tEL7n]wMgTƻ2o1?GW:.N_corescores* +DkbVGPLongLong Long integer Data Typex/ DAW+OIF)A"[2&?0@G0Lz tGz4gACAo1?GW:.N_empty_temp_directoryempty temp directory* +DkbVDEFolderFolderFolder Data Typex/ DIN 20120326125745001.0TRUE20140518153702ItemDescriptionC:\Program Files (x86)\ArcGIS\help\gpThe input is usually in LAS or LAZ format but also BIN, SHP, TXT, ASC, BIL, or DTM are supported.The input is usually in LAS or LAZ format but also BIN, SHP, TXT, ASC, BIL, or DTM are supported.The size of the temporary tiles that the huge file will be decomposed into. Needs to be small enough such that there are no more than 15 millions points per tile.The size of the temporary tiles that the huge file will be decomposed into. Needs to be small enough such that there are no more than 15 millions points per tile.The size of the buffer around each tile that is used to avoid edge artifacts. Should be at least 10 to 20 meters but larger for terrains with man-made objects.The size of the buffer around each tile that is used to avoid edge artifacts. Should be at least 10 to 20 meters but larger for terrains with man-made objects.<DIV STYLE="text-align:Left;"><DIV><P><SPAN>Specifies what the expected building size is in the area that is ground classified. The bigger the buildings the bigger a city this setting needs to suggest. See the README.txt file of lasground.exe for details.</SPAN></P></DIV></DIV><DIV STYLE="text-align:Left;"><DIV><P><SPAN>Specifies how much computational effort to invest into finding the initial ground estimate. Should be set higher in very steep terrains. Is only really worthwhile when the ground is complex with many gullies, gorges, and banks. Makes little sense to set high for flat terrains.</SPAN></P></DIV></DIV>Points whose height is above the (optionally) specified height will be dropped from the output.Points whose height is above the (optionally) specified height will be dropped from the output.Points whose height is below the (optionally) specified height will be dropped from the output.Points whose height is below the (optionally) specified height will be dropped from the output.The number of cores to use for parallelizing the tile-based multi-core processing. Do not choose more cores than your computer has. The number of cores to use for parallelizing the tile-based multi-core processing. Do not choose more cores than your computer has. An *empty* directory with sufficient storage space that the LAStools pipeline can use to store temporary results.An *empty* directory with sufficient storage space that the LAStools pipeline can use to store temporary results.<DIV STYLE="text-align:Left;"><DIV><P><SPAN>Specifies both, the file name and the format for the generated output LiDAR points. </SPAN></P></DIV></DIV>Specifies the output format. Usually this will be LAZ or LAS but also BIN and various ASCII formats are supported.<DIV STYLE="text-align:Left;"><DIV><P><SPAN>Specifies the output format. Usually this will be the LAS or the LAZ format, but the BIN format and various TXT formats are also supported.</SPAN></P></DIV></DIV>Specifies the output format. Usually this will be LAZ or LAS but also BIN and various ASCII formats are supported.<DIV STYLE="text-align:Left;"><DIV><P><SPAN>If checked, more control information will appear in the console.</SPAN></P></DIV></DIV><DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>Uses lasground.exe to extract the bare-earth by classifying LIDAR points into ground points (class = 2) and unclassified points (class = 1).</SPAN></P><P><SPAN>The LiDAR input can be LAS, LAZ, BIN, SHP, ASC, or TXT. The LiDAR output can be in LAS, LAZ, BIN, or TXT format.</SPAN></P></DIV></DIV></DIV>huge file normalizeMartin Isenburgrapidlasso GmbH010martin@rapidlasso.comMartin Isenburg, LASSO - rapid tools to catch reality, http://rapidlasso.comThis LAStools pipeline height-normalizes very large LAS or LAZ files by operating with a tile-based multi-core pipeline. The input file is first tiled using lastile with the specified tile size and the specified buffer around each tile to avoid edge artifacts. These tiles are then ground-classified using lasground on as many cores as specified. The tiles are then height-normalized using lasheight with optional removal of points that are too high above or too far below the ground points. Finally the height-normalized tiles are rejoined back into a single file with points in their original order and all temporary files are deleted.LiDARLASLAZground classificationbare-earth extractionclassificationground filteringThere might be artifacts when using an unlicensed version if you go over the point limits. Watch the control output when LAStools Pipelines are running. The tools will inform you when this happens. Please read the LICENSE.txt file.ArcToolbox Tool class ToolValidator: """Class for validating a tool's parameter values and controlling the behavior of the tool's dialog.""" def __init__(self): """Setup the Geoprocessor and the list of tool parameters.""" import arcgisscripting as ARC self.GP = ARC.create(9.3) self.params = self.GP.getparameterinfo() def initializeParameters(self): """Refine the properties of a tool's parameters. This method is called when the tool is opened.""" return def updateParameters(self): """Modify the values and properties of parameters before internal validation is performed. This method is called whenever a parmater has been changed.""" return def updateMessages(self): """Modify the messages created by internal validation for each tool parameter. This method is called after internal validation.""" return x\d output_filenormalized.lazt file is first tiled using lastile with the specified tile size. The specified buffer hugeFileClassifyhuge file classify4This LAStools pipeline classifies very large LAS or LAZ files by operating with a tile-based multi- core pipeline. The input file is first tiled using lastile with the specified tile size. The specified buffer is used to avoid edge artifacts. All tiles are then ground classified using lasground marking points as ground (class 2) and non-gound (class 1). Next the height of all points above the ground is computed using lasheight with an optional removal of points above a specified height. Then buildings and vegetation are classified using lasclassify. Finally the processed tiles are rejoined back into a single file with points in their original order and all temporary files are deleted. The LiDAR input can be LAS, LAZ, BIN, SHP, BIL, DTM, ASC, or TXT. The LiDAR output can be in LAS, LAZ, BIN, or TXT format.'scripts_pipelines\huge_file_classify.py o1?GW:.N_ input_file input file* +DkbVDEFileFileFile Data Typex/ DING4 L-lazlasbinshptxtascbildtm\:A= DEFileo1?GW:.N_ tile_size tile size* +DkbVGPDoubleDoubleDouble Data Typex/ DAW+OIF)tEL7n]wMgTƻ2@@o1?GW:.N_bufferbuffer* +DkbVGPDoubleDoubleDouble Data Typex/ DAW+OIF)tEL7n]wMgTƻ29@o1?GW:.N_ terrain_type terrain type* +DkbVGPStringStringString Data Typex/ DAW+OIF)qfK5Ywilderness forest or hillstowns or flats&city or warehousesmetropolis34jgJ$ wilderness34jgJ$  forest or hills34jgJ$ towns or flats34jgJ$ &city or warehouses34jgJ$ metropolis34jgJ$  forest or hillso1?GW:.N_ granularity granularity* +DkbVGPStringStringString Data Typex/ DAW+OIF)qfK5Ydefault fineextra fineultra fine34jgJ$ default34jgJ$  fine34jgJ$ extra fine34jgJ$ ultra fine34jgJ$  fineo1?GW:.N_drop_points_with_height_abovedrop points with height above* +DkbVGPDoubleDoubleDouble Data Typex/ DAW+OIF)tEL7n]wMgTƻ2o1?GW:.N_corescores* +DkbVGPLongLong Long integer Data Typex/ DAW+OIF)A"[2&?0@G0Lz tGz4gACAo1?GW:.N_empty_temp_directoryempty temp directory* +DkbVDEFolderFolderFolder Data Typex/ DIN 20120326125745001.0TRUE20140602214348ItemDescriptionC:\Program Files (x86)\ArcGIS\help\gpThe input is usually in LAS or LAZ format but also BIN, SHP, TXT, ASC, BIL, or DTM are supported.The input is usually in LAS or LAZ format but also BIN, SHP, TXT, ASC, BIL, or DTM are supported.The size of the temporary tiles that the huge file will be decomposed into. Needs to be small enough such that there are no more than 15 millions points per tile.The size of the temporary tiles that the huge file will be decomposed into. Needs to be small enough such that there are no more than 15 millions points per tile.The size of the buffer around each tile that is used to avoid edge artifacts. Should be at least 10 to 20 meters but larger for terrains with man-made objects.The size of the buffer around each tile that is used to avoid edge artifacts. Should be at least 10 to 20 meters but larger for terrains with man-made objects.<DIV STYLE="text-align:Left;"><DIV><P><SPAN>Specifies what the expected building size is in the area that is ground classified. The bigger the buildings the bigger a city this setting needs to suggest. See the README.txt file of lasground.exe for details.</SPAN></P></DIV></DIV><DIV STYLE="text-align:Left;"><DIV><P><SPAN>Specifies how much computational effort to invest into finding the initial ground estimate. Should be set higher in very steep terrains. Is only really worthwhile when the ground is complex with many gullies, gorges, and banks. Makes little sense to set high for flat terrains.</SPAN></P></DIV></DIV>Points whose height is above the (optionally) specified height will be dropped from the output.Points whose height is above the (optionally) specified height will be dropped from the output.The number of cores to use for parallelizing the tile-based multi-core processing. Do not choose more cores than your computer has. The number of cores to use for parallelizing the tile-based multi-core processing. Do not choose more cores than your computer has. An *empty* directory with sufficient storage space that the LAStools pipeline can use to store temporary results.An *empty* directory with sufficient storage space that the LAStools pipeline can use to store temporary results.<DIV STYLE="text-align:Left;"><DIV><P><SPAN>Specifies both, the file name and the format for the generated output LiDAR points. </SPAN></P></DIV></DIV>Specifies the output format. Usually this will be LAZ or LAS but also BIN and various ASCII formats are supported.<DIV STYLE="text-align:Left;"><DIV><P><SPAN>Specifies the output format. Usually this will be the LAS or the LAZ format, but the BIN format and various TXT formats are also supported.</SPAN></P></DIV></DIV>Specifies the output format. Usually this will be LAZ or LAS but also BIN and various ASCII formats are supported.<DIV STYLE="text-align:Left;"><DIV><P><SPAN>If checked, more control information will appear in the console.</SPAN></P></DIV></DIV><DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>Uses lasground.exe to extract the bare-earth by classifying LIDAR points into ground points (class = 2) and unclassified points (class = 1).</SPAN></P><P><SPAN>The LiDAR input can be LAS, LAZ, BIN, SHP, ASC, or TXT. The LiDAR output can be in LAS, LAZ, BIN, or TXT format.</SPAN></P></DIV></DIV></DIV>This LAStools pipeline classifies very large LAS or LAZ files by operating with a tile-based multi- core pipeline. The input file is first tiled using lastile with the specified tile size. The specified buffer is used to avoid edge artifacts. All tiles are then ground classified using lasground marking points as ground (class 2) and non-gound (class 1). Next the height of all points above the ground is computed using lasheight with an optional removal of points above a specified height. Then buildings and vegetation are classified using lasclassify. Finally the processed tiles are rejoined back into a single file with points in their original order and all temporary files are deleted.huge file classifyMartin Isenburgrapidlasso GmbH010martin@rapidlasso.comMartin Isenburg, LASSO - rapid tools to catch reality, http://rapidlasso.comThis LAStools pipeline classifies very large LAS or LAZ files by operating with a tile-based multi- core pipeline. The input file is first tiled using lastile with the specified tile size. The specified buffer is used to avoid edge artifacts. All tiles are then ground classified using lasground marking points as ground (class 2) and non-gound (class 1). Next the height of all points above the ground is computed using lasheight with an optional removal of points above a specified height. Then buildings and vegetation are classified using lasclassify. Finally the processed tiles are rejoined back into a single file with points in their original order and all temporary files are deleted.LiDARLASLAZground classificationbare-earth extractionclassificationground filteringThere might be artifacts when using an unlicensed version if you go over the point limits. Watch the control output when LAStools Pipelines are running. The tools will inform you when this happens. Please read the LICENSE.txt file.005LiDARclassificationbare-earthgroundbuildingvegetationLASLAZlarge filesbig dataArcToolbox Tool class ToolValidator: """Class for validating a tool's parameter values and controlling the behavior of the tool's dialog.""" def __init__(self): """Setup the Geoprocessor and the list of tool parameters.""" import arcgisscripting as ARC self.GP = ARC.create(9.3) self.params = self.GP.getparameterinfo() def initializeParameters(self): """Refine the properties of a tool's parameters. This method is called when the tool is opened.""" return def updateParameters(self): """Modify the values and properties of parameters before internal validation is performed. This method is called whenever a parmater has been changed.""" return def updateMessages(self): """Modify the messages created by internal validation for each tool parameter. This method is called after internal validation.""" return x\dssifyhuge file ground-classifykThis LAStools pipeline ground-classifies very large LAS or LAZ files by operating with a tile-based multi-core pipeline. The input file is first tiled using lastile with the specified tile size andhugeFileGroundClassifyhuge file ground-classifykThis LAStools pipeline ground-classifies very large LAS or LAZ files by operating with a tile-based multi-core pipeline. The input file is first tiled using lastile with the specified tile size and the specified buffer to avoid edge artifacts. All tiles are then ground classified using lasground marking points as ground (class 2) and non-gound (class 1). Finally the ground-classified tiles are rejoined back into a single file with points in their original order and all temporary files are deleted. The LiDAR input can be LAS, LAZ, BIN, SHP, ASC, or TXT. The LiDAR output can be in LAS, LAZ, BIN, or TXT format..scripts_pipelines\huge_file_ground_classify.py o1?GW:.N_ input_file input file* +DkbVDEFileFileFile Data Typex/ DING4 L-lazlasbinshptxtascbildtm\:A= DEFileo1?GW:.N_ tile_size tile size* +DkbVGPDoubleDoubleDouble Data Typex/ DAW+OIF)tEL7n]wMgTƻ2@@o1?GW:.N_bufferbuffer* +DkbVGPDoubleDoubleDouble Data Typex/ DAW+OIF)tEL7n]wMgTƻ29@o1?GW:.N_ terrain_type terrain type* +DkbVGPStringStringString Data Typex/ DAW+OIF)qfK5Ywilderness forest or hillstowns or flats&city or warehousesmetropolis34jgJ$ wilderness34jgJ$  forest or hills34jgJ$ towns or flats34jgJ$ &city or warehouses34jgJ$ metropolis34jgJ$  forest or hillso1?GW:.N_ granularity granularity* +DkbVGPStringStringString Data Typex/ DAW+OIF)qfK5Ydefault fineextra fineultra fine34jgJ$ default34jgJ$  fine34jgJ$ extra fine34jgJ$ ultra fine34jgJ$  fineo1?GW:.N_corescores* +DkbVGPLongLong Long integer Data Typex/ DAW+OIF)A"[2&?0@G0Lz tGz4gACAo1?GW:.N_empty_temp_directoryempty temp directory* +DkbVDEFolderFolderFolder Data Typex/ DIN 20120326125745001.0TRUE20140518153719ItemDescriptionC:\Program Files (x86)\ArcGIS\help\gpThe input is usually in LAS or LAZ format but also BIN, SHP, TXT, ASC, BIL, or DTM are supported.The input is usually in LAS or LAZ format but also BIN, SHP, TXT, ASC, BIL, or DTM are supported.The size of the temporary tiles that the huge file will be decomposed into. Needs to be small enough such that there are no more than 15 millions points per tile.The size of the temporary tiles that the huge file will be decomposed into. Needs to be small enough such that there are no more than 15 millions points per tile.The size of the buffer around each tile that is used to avoid edge artifacts. Should be at least 10 to 20 meters but larger for terrains with man-made objects.The size of the buffer around each tile that is used to avoid edge artifacts. Should be at least 10 to 20 meters but larger for terrains with man-made objects.<DIV STYLE="text-align:Left;"><DIV><P><SPAN>Specifies what the expected building size is in the area that is ground classified. The bigger the buildings the bigger a city this setting needs to suggest. See the README.txt file of lasground.exe for details.</SPAN></P></DIV></DIV><DIV STYLE="text-align:Left;"><DIV><P><SPAN>Specifies how much computational effort to invest into finding the initial ground estimate. Should be set higher in very steep terrains. Is only really worthwhile when the ground is complex with many gullies, gorges, and banks. Makes little sense to set high for flat terrains.</SPAN></P></DIV></DIV>The number of cores to use for parallelizing the tile-based multi-core processing. Do not choose more cores than your computer has. The number of cores to use for parallelizing the tile-based multi-core processing. Do not choose more cores than your computer has. An *empty* directory with sufficient storage space that the LAStools pipeline can use to store temporary results.An *empty* directory with sufficient storage space that the LAStools pipeline can use to store temporary results.<DIV STYLE="text-align:Left;"><DIV><P><SPAN>Specifies both, the file name and the format for the generated output LiDAR points. </SPAN></P></DIV></DIV>Specifies the output format. Usually this will be LAZ or LAS but also BIN and various ASCII formats are supported.<DIV STYLE="text-align:Left;"><DIV><P><SPAN>Specifies the output format. Usually this will be the LAS or the LAZ format, but the BIN format and various TXT formats are also supported.</SPAN></P></DIV></DIV>Specifies the output format. Usually this will be LAZ or LAS but also BIN and various ASCII formats are supported.<DIV STYLE="text-align:Left;"><DIV><P><SPAN>If checked, more control information will appear in the console.</SPAN></P></DIV></DIV><DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>Uses lasground.exe to extract the bare-earth by classifying LIDAR points into ground points (class = 2) and unclassified points (class = 1).</SPAN></P><P><SPAN>The LiDAR input can be LAS, LAZ, BIN, SHP, ASC, or TXT. The LiDAR output can be in LAS, LAZ, BIN, or TXT format.</SPAN></P></DIV></DIV></DIV>This LAStools pipeline ground-classifies very large LAS or LAZ files by operating with a tile-based multi-core pipeline. The input file is first tiled using lastile with the specified tile size and the specified buffer to avoid edge artifacts. All tiles are then ground classified using lasground marking points as ground (class 2) and non-gound (class 1). Finally the ground-classified tiles are rejoined back into a single file with points in their original order and all temporary files are deleted.huge file ground-classifyMartin Isenburgrapidlasso GmbH010martin@rapidlasso.comMartin Isenburg, LASSO - rapid tools to catch reality, http://rapidlasso.comThis LAStools pipeline ground-classifies very large LAS or LAZ files by operating with a tile-based multi-core pipeline. The input file is first tiled using lastile with the specified tile size and the specified buffer to avoid edge artifacts. All tiles are then ground classified using lasground marking points as ground (class 2) and non-gound (class 1). Finally the ground-classified tiles are rejoined back into a single file with points in their original order and all temporary files are deleted.LiDARLASLAZground classificationbare-earth extractionclassificationground filteringThere might be artifacts when using an unlicensed version if you go over the point limits. Watch the control output when LAStools Pipelines are running. The tools will inform you when this happens. Please read the LICENSE.txt file.005LiDARclassificationbare-earthgroundLASLAZlarge filesbig dataArcToolbox Tool class ToolValidator: """Class for validating a tool's parameter values and controlling the behavior of the tool's dialog.""" def __init__(self): """Setup the Geoprocessor and the list of tool parameters.""" import arcgisscripting as ARC self.GP = ARC.create(9.3) self.params = self.GP.getparameterinfo() def initializeParameters(self): """Refine the properties of a tool's parameters. This method is called when the tool is opened.""" return def updateParameters(self): """Modify the values and properties of parameters before internal validation is performed. This method is called whenever a parmater has been changed.""" return def updateMessages(self): """Modify the messages created by internal validation for each tool parameter. This method is called after internal validation.""" return x\d)\ArcGIS\help\gp {705D8257-58FD-4874-8602-7B5FB125A7DB}2014050109372700TRUE20140502090751C:\Program Files (x86)\ArcGIS\help\gpLAStools PipelinesArcToolbox Toolbox #c8DæihugeFileGroundClassifyhuge file ground-classifykThis LAStools pipeline ground-classifies very large LAS or LAZ files by operating with a tile-based multi-core pipeline. The input file is first tiled using lastile with the specified tile size and the specified buffer to avoid edge artifacts. All tiles are then ground classified using lasground marking points as ground (class 2) and non-gound (class 1). Finally the ground-classified tiles are rejoined back into a single file with points in their original order and all temporary files are deleted. The LiDAR input can be LAS, LAZ, BIN, SHP, ASC, or TXT. The LiDAR output can be in LAS, LAZ, BIN, or TXT format.GKcILAStools Pipelines5ZqO:6D:\lastools\ArcGIS_toolbox|TOOLBOX: Workspace = \\RAPIDLASSO\D$\lastools\ArcGIS_toolbox;Toolbox DataZX|O:DATABASE6D:\lastools\ArcGIS_toolbox1#4*)G9gK#c8DæihugeFileClassifyhuge file classify4This LAStools pipeline classifies very large LAS or LAZ files by operating with a tile-based multi- core pipeline. The input file is first tiled using lastile with the specified tile size. The specified buffer is used to avoid edge artifacts. All tiles are then ground classified using lasground marking points as ground (class 2) and non-gound (class 1). Next the height of all points above the ground is computed using lasheight with an optional removal of points above a specified height. Then buildings and vegetation are classified using lasclassify. Finally the processed tiles are rejoined back into a single file with points in their original order and all temporary files are deleted. The LiDAR input can be LAS, LAZ, BIN, SHP, BIL, DTM, ASC, or TXT. The LiDAR output can be in LAS, LAZ, BIN, or TXT format.GKcI#c8DæihugeFileNomalizehuge file normalizeThis LAStools pipeline height-normalizes very large LAS or LAZ files by operating with a tile-based multi-core pipeline. The input file is first tiled using lastile with the specified tile size and the specified buffer around each tile to avoid edge artifacts. These tiles are then ground-classified using lasground on as many cores as specified. The tiles are then height-normalized using lasheight with optional removal of points that are too high above or too far below the ground points. Finally the height-normalized tiles are rejoined back into a single file with points in their original order and all temporary files are deleted. . The LiDAR input can be LAS, LAZ, BIN, SHP, ASC, or TXT. The LiDAR output can be in LAS, LAZ, BIN, or TXT format.GKcI#c8DæiflightlinesToDTMandDSMflightlines to DTM and DSMStarting from a folder of raw LiDAR flight lines in LAS or LAZ format, this pipeline uses several modules of the LAStools Production toolbox to tile and ground classify the raw LiDAR and generate DTM and DSM raster outputs in various formats as well as classified LAS or LAZ tiles.GKcI#c8DæiflightlinesToCHMflightlines to CHMThis LAStools pipeline turns a folder full of LAS or LAZ files (assumed to be raw flightlines) into a folder of tiled CHMs using a simple splatting and rasterization algorithm. The input file is tiled using lastile with the specified tile size. The specified buffer is used to avoid edge artifacts. All tiles are then ground classified using lasground marking points as ground (class 2) and non-ground (class 1). Next the height of all points above the ground is computed using lasheight and used to height-normalize all the tiles in the sense that the height is used to replace the z coordinates. Using lasthin the tiles are then both thinned and splatted keeping the highest returns on a subgrid while using the laser beam width in an attempt to widen the LiDAR returns a little bit. From these height-normalized and point-splatted tiles containing the highest return on a subgrid the CHMs are computed by sampling a TIN from all the remaining points at the requested step size. LiDAR input: LAS/LAZ raster output: TIF/IMG/BIL/DTM/ASC/FLT/XYZGKcI#c8DæiflightlinesToSingleCHMpitFree$flightlines to single CHM (pit-free) This LAStools pipeline turns a folder full of LAS or LAZ files (assumed to be raw flightlines) into a single pit-free CHM using the algorithms described by A. Khosravipour et al. in Silvilaser 2013. The input file is first tiled using lastile with the specified tile size. The specified buffer is used to avoid edge artifacts. All tiles are then ground classified using lasground marking points as ground (class 2) and non-gound (class 1). Next the height of all points above the ground is computed using lasheight and used to height-normalize all the tiles in the sense that the height is used to replace the z coordinates. Using lasthin the tiles are then both thinned and splatted using the laser beam with in an attempt to widen the LiDAR returns a little bit. From these height-normalized and point-splatted tiles the partial CHMs are computed (as detailed in the poster, the extended abstract, and the paper) that are merged into a single CHM in the final step. LiDAR input: LAS/LAZ rasteroutput: TIF/IMG/BIL/DTM/ASC/FLT/XYZGKcI#c8Dæi flightlinesQualityReportflightlines quality reportGThis LAStools pipeline classifies very large LAS or LAZ files with tile-based multi-core processing.The input file is first tiled using lastile with the specified tile size. The specified buffer is used to avoid edge artifacts. All tiles are then ground classified using lasground marking points as ground (class 2) and non-gound (class 1). Next the height of all points above the ground is computed using lasheight with an optional removal of points above a specified height. Then buildings and vegetation are classified using lasclassify. Finally the processed tiles are rejoined back into a single file with points in their original order and all temporary files are deleted. The LiDAR input can be LAS, LAZ, BIN, SHP, BIL, ASC, DTM, or TXT. The raster output can be in TIF/IMG/BIL/ASC/XYZ format. The LiDAR output can be in LAS/LAZ.GKcI#c8Dæi hugeFileRemoveDuplicateshuge file remove duplicatesThis LAStools pipeline removes duplicate points from huge LAS or LAZ files by operating with a tile-based multi-core pipeline. The input file is first tiled using lastile with the specified tile size. All tiles are then checked for XY or XYZ duplicates which are then deleted. The remaining points are merged back into a single file in their original order and all temporary tiles are deleted. The LiDAR input can be LAS, LAZ, BIN, SHP, ASC, or TXT. The LiDAR output can be in LAS, LAZ, BIN, or TXT format.GKcI #c8Dæi hugeFileSortGpsTimehuge file sort GPS timeThis LAStools pipeline sorts a huge LAS or LAZ files by operating with a chunk-based multi-core pipeline (i.e. bucket sort). The input file is first split into different GPS segments using lassplit with the specified duration in seconds. The points of each chunk are then sorted based on their GPS time stamps. The sorted chunks are then merged back into a single and all temporary chunks are deleted. The LiDAR input can be LAS, LAZ, BIN, SHP, ASC, or TXT. The LiDAR output can be in LAS, LAZ, BIN, or TXT format.GKcI #c8Dæi hugeFileSortSpatialCoherence huge file sort spatial coherenceThis LAStools pipeline sorts huge LAS or LAZ files into a more coherent point order using a tile-based multi-core pipeline. The input file is first tiled using lastile with the specified tile size. All tiles are then sorted into a spatially coherent z-order (e.g. space-filling curve). The sorted tiles are then merged back into a single file and all temporary tiles are deleted. The LiDAR input can be LAS, LAZ, BIN, SHP, ASC, or TXT. The LiDAR output can be in LAS, LAZ, BIN, or TXT format.GKcI  LAStools Pipelines