Latest Contributions by PeterWilson

‎02-01-2016

Hi Zdenek, I propose that you use the following: sqlprikaz = "Layer LIKE '%PLOCH%' AND NAME NOT LIKE '%_'" I recommend you have a look at AddFieldDelimiters and Regular Expressions. Regards

‎02-01-2016

I posted the following article: HEC-GeoHMS: Importing HEC-GeoHMS Toolbox asking for assistance in how to import HEC-GeoHMS into python. I received an email a while back from Christine Dartiguenave from the Arc Hydro Team, suggesting to run the following: import arcpy import arcpy.toolbox_code arcpy.toolbox_code.generate_toolbox_module (r'C:\Program Files (x86)\ArcGIS\Desktop10.2\ArcToolbox\Toolboxes\GeoHMS Tools.tbx', r'C:\Projects\GeoHMSTools.py',False, False,True,'geohms') When I try to import GeoHMSTools within Python I receive the following error message: import GeoHMSTools Runtime error Traceback (most recent call last): File "<string>", line 1, in <module> ImportError: No module named GeoHMSTools I'm not sure if I'm meant to copy the python script that is created under C:\Projects i.e. GeoHMSTools.py into another directory, before trying to import it into Python.

‎01-31-2016

I need assistance in importing HEC-GeoHMS Toolbox into Python. I haven't been able to find any examples of the correct syntax to import and use the tools within the HEC-GeoHMS Toolbox. The code below is based on export a model from ModelBuilder with one of the HEC-GeoHMS tools within it. It keeps telling me that there are no arguments. Any help will be appreciated. ''' Created on Feb 1, 2016 @author: PeterW ''' import arcpy # import HEC-GeoHMS toolbox arcpy.ImportToolbox(r"C:\Program Files (x86)\ArcGIS\Desktop10.2\ArcToolbox\Toolboxes\GeoHMS Tools.tbx") # set input arguments Subbasin = r"E:\Python\ModelBuilder\Model01.gdb\Layers\Watershed" Centroid = r"E:\Python\ModelBuilder\Model01.gdb\Layers\Centroid" LongestFlowPath = r"E:\Python\ModelBuilder\Model01.gdb\Layers\LongestFlowPath_2D" Output_Centroidal_Longest_Flow_Path = r"E:\Python\ModelBuilder\Model01.gdb\Layers\CentroidalLongestFlowPath2" # determine the centroidal longest flowpath arcpy.AddMessage("Processing Centroidal Longest Flowpath") arcpy.CentroidalLongestFlowpath_geohms(Subbasin, Centroid, LongestFlowPath, Output_Centroidal_Longest_Flow_Path) #@UndefinedVariable The error message that I receive is attached below:

‎01-30-2016

I have found a solution to incorporating the road network into my Path Distance analysis that determines the time is takes to traverse a terrain using Toblers Hiking Function. In my previous model I provided no Cost Raster as input to the Path Distance analysis tool. By not providing an input Cost Raster, the cost of 1 per-unit distance will be used, which is the same as applying a cost raster with values of all 1's. The effort to move through the terrain is being determined by the vertical raster (elevation) and the vertical factor table (Toblers Hiking Function). I created an Euclidean Distance raster from my road network, matching my cell size to the elevation DEM as well as ensuring that they aligned. I then reclassified my road network cost raster into the following classes and new cost values: 10m: 1 25m 2 50m 3 100m 4 >100m 10 I used the following cost raster of my road network in conjunction with my Toblers Hiking Function and the initial results are looking good already. I will simulate different cost values for the road network cost raster to obtain more realistic results of the effort required to move through the terrain along the road network versus the terrain itself. I hope the following assists anyone else trying to solve a similar problem.

‎01-28-2016

I've generated a Python script that determines the service areas for either schools (points) or informal settlements (polygons) based Toblers Hiking Function from the article published by Kaitlin Yanchar using Path Distance Analysis. The input cost raster to the Path Distance tool is the slope grid that is used in combination with the elevation grid and the vertical factor table based on Toblers Hiking Function. I would like to include the road network as part of the cost raster, but not sure how to proceed. The input cost raster has to be the slope grid and cant be a weighted cost raster as one would if you combined multiple criteria such as slope, road networks, landuse etc as the vertical factor is used to determine the time is would take to traverse the terrain based on the slope and elevation grid. Any suggestion in how to incorporate the road network as more preferable than walking over the hillslope will be appreciated.

‎01-23-2016

I've successfully created a python script that generates a map package for each data driven page. The only stumbling block that I still have is that the extent parameter for package map is based on the active data frame extent and not individually for each data frame. This is a shame as a lot of maps have a data frame that represents a inset of your study area. I'd like to clip my data to the extent of each data frame before creating a map package as to reduce the data being replicated for each map package. I've attached my python script if anyone is interested.

‎01-20-2016

I came across the following sample code that Chris Fox from esri wrote as a way to create a new mxd for each Data Driven Page: mxdPath = r"C:\Project\DDPMap.mxd" mxd = arcpy.mapping.MapDocument(mxdPath) mxdDir = os.path.dirname(mxdPath) for pageNum in range(1, mxd.dataDrivenPages.pageCount + 1): mxd.dataDrivenPages.currentPageID = pageNum mxdName = os.path.join(mxdDir, "DDPMap", + str(pageNum) + ".mxd") mxd.saveACopy(mxdName) del mxd Is there a way to create a map package for each Data Driven Page instead of having to save it out first as a new mxd. arcpy package map sample: for mxd in arcpy.ListFiles("*.mxd"): arcpy.AddMessage("Packaging: {}".format(mxd)) arcpy.PackageMap_management(mxd, os.path.splittext(mxd) [0] + ".mpk", "PRESERVE", "CONVERT_ARCSDE", "DISPLAY", "ALL")

‎01-20-2016

Hi Chad Indeed, TauDEM is exceptionally fast. its the primary reason why I'm currently looking into using it to derive hydrological characteristics as my study areas are get larger and larger. My current project that I'm working on is with South Sudan, Ethiopia and Kenya, where my DSM is over 500 million cells. TauDEM is not as feature rich as ArcHydro so I'm trying to combine the two applications to achieve the most efficient solution. TauDEM to the best of my knowledge doenst deal with non-dendritic systems as it tries to fill the DSM until it flows out the lowest position. I'm currently discussing the following with Prof Tarboton to see if there is any work around.

‎01-12-2016

Hi Dan Thanks for reminding me about the reclass by table tool, clean forgot about it. Regards, Peter Wilson

‎01-12-2016

I wasn't able to generate my own comparison tool, so I ended up utilizing FME Software.

‎01-12-2016

Hi Nicola Thanks for the following, much appreciated.

‎01-12-2016

Hi Dan I've finally got started with TauDEM and emailed Prof Tarboton to confirm workflows and functionality. TauDEM at this stage is unable to determine the following characteristics that I listed above. I have still found that TauDEM is beneficial due to its multi-thread processing capability. I have incorporated TauDEM into my current ArcHydro python models to replace certain ArcHydro functions. Although ArcHydro is 64bit, its not multi-threaded so its not capable of using more that one core of your processor. TauDEM is multi-threaded and utilizes all the cores available. The functions that take the longest to process are Flow Direction and Flow Accumulation using the D8 flow routing algorithm. These functions are available within TauDEM and drastically reduce the processing time to complete the following, especially in very large study areas. I'm currently still comparing the results generated by TauDEM with those produced by ArcHydro.

‎01-12-2016

I'm currently using ArcGIS 10.2.2 (Advanced). I need to generate a new raster from an existing raster by comparing the cell values to a list where an new cell value will be listed against the old value. The existing unique list of values: 1 8 7 6 5 4 3 2 The new cell values are: 1 - 1 2 - 8 4 - 7 8 - 6 16 - 5 32 - 4 64 - 3 128 - 2 I'm looking for advice in how I can achieve creating a new raster based on comparing the existing cell values and replacing them with the new cell values using python. I could create a map algebra function to achieve the following using if statements, but feel that there should be a better method using Python. I was wondering if numpy arrays to achieve the following is suitable, but I have used them before so any help in getting started will be appreciated. Any other methods using python are also welcome.

‎12-01-2015

Dear ESRI Community I'd like to find out if anyone has made use of TauDEM for Hydrological Modeling? I'm keen to find out if its possible to determine the following using TauDEM: Longest Flow Path (Subwatershed or Watershed) Slope 10/85 Length to Centroid (Centroidal Longest Flowpath) Regards

‎09-06-2015

I've spent the last week reviewing ESRI Videos, Help Documentation and read through a great portion of Konstantin's book "Spatial Statistical Data Analysis for GIS Users". I have a few questions to validate my understanding of the geostatistical tools and workflows and how I can use them to model uncertainty propagation from SRTM DSM (Digital Surface Models) for hydrological modelling: Is there anyway of producing equally probable realisations using the Empirical Bayesian Kriging using the PREDICTION_STANDARD_ERROR output? The reason for looking to see if its possible to create equally probable realisations from the Empirical Bayesian Kriging interpolation is that its already creating numerous simulations and determining the best fit semivariogram based on the input points. I'd have to convert the SRTM DSM into points to be able to model the uncertainty within the SRTM DSM based on ground control points from a LiDAR Survey. Is it possible to using the Empirical Bayesian Kriging PREDICTION as input to Gaussian Geostatistical Simulations to generate equally probable realisations of my DEM's? The reason for seeing if its possible to use the output PREDICTION raster from Empirical Bayesian Kriging as input to Gaussian Geostatistical Simulations is that it would contain the least error in converting the SRTM DSM to a Geostatistical Layer Is there any workflow in getting around the current limitation of the raster cell size (2049 X 2049) ? My hydrological watershed study areas are definitely going to be larger than 4.2 million cells Summary: I'm trying to make use of the tools within Geostatistical Analyst to accomplish my goals of generating equally probable realisations of the SRTM 30m , 90m and hydroSHEDS that I then can use to generate watersheds, stream networks and longest flow paths . The results from each simulation will be used to generate a probability distribution of the derived watersheds, stream networks and longest flow paths in order to quantify and visualise the uncertainty. Your advice and guidance to achieve the following will be appreciated. Regards Peter Wilson

Online Status	Offline
Date Last Visited	‎03-04-2021 12:50 PM

My Ideas

Latest Contributions by PeterWilson

Re: quotes and double quotes in an SQL expression

Python: Create Python Module from existing Python Toolbox

HEC-GeoHMS: Importing HEC-GeoHMS Toolbox

Re: Path Distance Analysis: Toblers Hiking Function + Road Network

Path Distance Analysis: Toblers Hiking Function + Road Network

Re: ArcPy: Data Driven Pages to Individual Map Packages

ArcPy: Data Driven Pages to Individual Map Packages

Re: TauDEM

Re: Create a new Raster, determining new cell values based on list

Re: Python hashlib to compare shapefiles\feature classes

Re: Python Script: Convert KML to AutoCAD(DWG\DXF)

Re: TauDEM

Create a new Raster, determining new cell values based on list

TauDEM

Uncertainty Popagation Analysis of SRTM DSMs

Editing: Autocomplete Polygon

Re: Python: Geo-HMS "Centroidal Longest Flowpath"

Re: I am learning python from a book, programming ...

Re: How to pass arguments to main function in modu...

Re: Does anyone have a good file system hierarchy ...