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jorrarro last won the day on January 23 2018

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  1. Technical term is generalization. Pretty much every GIS or cartography book ever written has a chapter dedicated to it. For example: https://www.geos.ed.ac.uk/~gisteac/gis_book_abridged/files/ch10.pdf And yes, it is valid.
  2. I suggest this topic: https://www.researchgate.net/post/How_does_one_calculate_the_percent_vegetation_cover_using_NDVI_method
  3. There is no "standard" workflow, as there are too many variables involved - source of data, quality of data, terrain differences, vegetation, building and of course the goals of analyses are also different. This is what I have done recently: 1. Filter the dataset with LASTools - extract terrain, vegetation and buildings. 2. Convert each separate dataset to grid using SAGA. Cell size depends on area size and resolution. 3. Fill in the gaps using B-spline interpolation (SAGA). The specific parameters and masks used depend on the dataset. For example, terrain should have full coverage, but building need only cover their footprints (from OSM for example).
  4. Follow this one: https://gis.stackexchange.com/questions/182359/is-it-possible-to-install-geoserver-on-google-cloud One method even has a video describing the installation.
  5. Should be like this: Create vector layer with tower locations with heights as Z values. Convert vector layer to raster with same extent as DEM raster. Add tower raster to DEM raster in Raster Calculator (same name in ArcGIS and QGIS).
  6. This is good news (more competition -> lower prices), but there is strong possibility that it will fizzle out. At this point we have Google, Microsoft and HERE offering excellent service with good documentation and occasional discounts. If you want to manage your stuff more hands-on, then you can build very good things with OpenStreetMap data using open source software. Sure, you need to manage your own servers, but you can also customize it however you want.
  7. I'm guessing ESRI product - so ArcMap or ArcGIS Pro. As far as official documentation goes, you can't. Unless you buy "Production mapping" extension. However, there are some workarounds - check here for Pro: https://community.esri.com/thread/189098-arcgis-pro-export-a-layout-with-a-world-file-for-georeferencing-unavailable Or here from ArcMap: https://community.esri.com/thread/32020
  8. Oh, the flashbacks... This is one of the factors that pushed me to QGIS. Anyway, you have to download correct ST_Geometry library from ESRI site. Thing is - ESRI lags behind PostgreSQL versions. So you can't use the latest or even second latest PGSQL. https://pro.arcgis.com/en/pro-app/help/data/databases/add-the-st-geometry-type-to-a-postgresql-database.htm EDIT: Most important question - what version of PGSQL do you have and has ESRI explicitly announced their support for it?
  9. Looks like the images are not georeferenced (no worldfile) or the projection does not match the worldfile. If you are using ArcGIS, this should help: http://desktop.arcgis.com/en/arcmap/10.3/manage-data/raster-and-images/fundamentals-for-georeferencing-a-raster-dataset.htm
  10. Set up you own PostGIS Tiger dataset. Pretty good guide is here - http://dracodoc.github.io/2015/11/17/Geocoding/.
  11. You can import shapefiles using Fiona and do all sorts of modifications with Shapely. For more information, look here: https://sgillies.net/2010/07/06/shapely-recipes.html
  12. This depends on where do you need to use this calculation. Mostly you can convert them to cartesian and then use application-specific methods to avoid errors. For example, in Excel you can use IFERROR function to default all divisions by zero (vertically aligned) to 0 or 180 degrees. In SQL you can use NULLIF on divisors equalling zero and then COALESCE to default value.
  13. First I used Excel to transform data to table. Data -> Text to columns. As I could not use space as delimiter (last column has spaces), I used fixed width so that all numbers went to separate fields. And then rewrote the header. As CSV, the data came out as follows (semicolon as delimiter): GID;Y;X;Z;text; 160501;1136981.309;427018.995;24.453;Tabtgået; 160502;1137117.536;426932.208;24.7;Spyd i jord m gul top; 160503;1137074.143;427167.529;25.276;Spyd i jord m gul top; 160504;1137270.694;427149.621;24.771;Spyd i jord m gul top; 160505;1137316.357;426982.35;24.863;Spyd i jord m gul top; 160506;1137372.847;427141.53;23.281;Spyd i jord m gul top; 160507;1137475.44;426979.949;22.596;Tabtgået; 160508;1137527.149;427215.072;21.179;Spyd i jord m gul top; 160509;1137611.641;427182.29;20.764;Spyd i jord m gul top; 160510;1137616.198;427041.391;20.413;Spyd i jord m gul top; 160511;1137740.069;427050.822;19.723;Spyd i jord m gul top; 160512;1137751.792;427132.87;19.216;Tabtgået; 161004;1137048.141;427149.171;25;Spyd i jord m gul top; 161003;1137126.893;427110.19;25.517;Tabtgået; 161002;1137182.808;427057.73;25.309;Tabtgået; 161001;1137220.373;427007.094;25.911;Spyd i jord m gul top; 170102;1137306.111;427120.132;24.574;Spyd i jord m gul top; 170103;1137301.109;427034.383;25.118;Spyd i jord m gul top; 170101;1137275.446;427044.6;25.784;Spyd i jord m gul top; 170104;1137393.761;427019.66;23.584;Spyd i jord m gul top; 170105;1137413.861;427022.837;23.365;Spyd i jord m gul top; 170106;1137419.946;427116.878;22.07;Spyd i jord m gul top; 170501;1137404.049;427054.017;21.139;Fast prisme i tunnel, prismekonstant;-17,5mm 170502;1137410.036;427080.694;21.107;Fast prisme i tunnel, prismekonstant;-17,5mm 170503;1137293.021;427063.412;20.908;Fast prisme i tunnel, prismekonstant;-17,5mm 170504;1137291.129;427086.338;20.879;Fast prisme i tunnel, prismekonstant;-17,5mm 170505;1137218.985;427024.099;20.888;Fast prisme i tunnel, prismekonstant;-17,5mm 170506;1137218.609;427019.445;20.795;Fast prisme i tunnel, prismekonstant;-17,5mm For ArcMap, I added the saved CSV (you could save it as XLSX and use it same way) file to data frame and under right click chose Display XY data. Arcmap detects X and Y automatically, just had to set Z to field Z. Under projection, click Edit and choose DKTM2 (Projected - National grids - Europe, search works too).
  14. It seems to me that the answer is in your dataset. In the text file SRS: DKTM2_DVR90 That means Danish system with metric coordinates. Use this as reference: https://epsg.io/4098 When importing the coordinates, be sure to notice that they are not XYZ but YXZ (northings before eastings).
  15. Usually Python libs work in Windows, installing them is the problem. Mostly there is somewhat cryptic error saying it cannot find vcvarsall.bat or some other file. However, if you install the prerequisites from the precompiled wheels, you can install the library using pip. For example, OSMpythonTools has a lot of prerequisites, such as lxml, pandas, matplotlib, ujson. Now just typing in "pip install osmpythontools" gives an error like this: " Running setup.py install for ujson ... error Complete output from command C:\Python34\python.exe -u -c "import setuptools, tokenize;__file__='C:\\Users\\Tanel\\AppData\\Local\\Temp\\pip-build-hrf5z5wi\\ujson\\setup.py';f=getattr(tokenize, 'open', open)(__file__);code=f.read().replace('\r\n', '\n');f.close();exec(compile(code, __file__, 'exec'))" install --record C:\Users\Test\AppData\Local\Temp\pip-tva4s83x-record\install-record.txt --single-version-externally-managed --compile: running install running build running build_ext building 'ujson' extension error: Unable to find vcvarsall.bat " So the solution is to download the precompiled wheel from here: http://www.lfd.uci.edu/~gohlke/pythonlibs/ And install the wheel "pip install C:\tmp\ujson-1.35-cp34-cp34m-win_amd64.whl". Then retry installing and if there is error with any packages, install corresponding wheels.
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