Tag Info

New answers tagged

1

So thanks to an answer from Mike T to this question, I used listgeo to create TFW files to replicate the geodata that already exists in the TIFs. listgeo -tfw x.tif # FTW Once I did that, MapInfo behaved like a post-Y2K piece of software (although "drag'n'drop" functionality is still beyond it).


0

You could do this easily enough in C++. The way I would do it is to send the path of the file you want to crop, the path of the output/cropped raster, the top left coordinates of the cropped raster and the width and height of the cropped raster. An outline for your code could look something like this. . . void crop(const char *inputPath, const char ...


1

So GeoTIFFs aren't just GeoTIFF's... Exactly what kind of GeoTIFF have you created? 8bit, 16bit, 24Bit, 32bit? Raster, Grid? ... Sofar MapInfo Pro only supports GeoTIFF Raster up to 24bit, as I recall.


1

Also, you could get the tree canopy volume using this web-based application: LiDARAlphaShape3D http://forest.moscowfsl.wsu.edu:3838/LiDARAlphaShape3D/


1

To visualize, you can check out these web-based applications: LiDARtreesModel3D http://forest.moscowfsl.wsu.edu:3838/csilva/LiDARtreesModel3D/ LiDARstand3D http://forest.moscowfsl.wsu.edu:3838/csilva/LiDARstand3D/


1

You can check out these web-based applicatons: LiDARTreeTop http://forest.moscowfsl.wsu.edu:3838/LiDARTreeTop/ LiDAR3DclusterTree http://forest.moscowfsl.wsu.edu:3838/LiDAR3DclusterTree/


0

I had the same problem "translating" geotiff files (downloaded from worldclim)to ASCII grid files in QGIS 2.6.1. I solved it by typing "-ot Int 32" after the translation command and before the file path: gdal_translate -of AAIGrid -ot Int 32 D:/.../lu_krs_attr.tif D:/.../grid/test_grid.asc The idea is from ...


-1

It really depends on how your files are structured, namely if the have multiple bands. Assuming that you have only one band in each file you can use the following code to make a rasterstack. Using the 'raster' library makes it easier. library(raster) datafiles <- Sys.glob("*.tif") #Or whatever identifies your files resultingStack <- stack() for(i in ...


2

A simple for loop will suffice. You can use readGDAL in the rgdal package but I would recommend raster in the raster package. You have to be a bit tricky and use strsplit in the assign function to strip off the ".tif" file extension. setwd("C:/rasters") rlist=list.files(getwd(), pattern="tif$", full.names=FALSE) for(i in rlist) { ...


1

A NaN is different than NA. The NaN often results from a divide by zero error whereas NA is the R value for no data. These values behave in specific ways and it would be good for you to read some R background material to understand the behavior. Two useful operators to be aware of are: is.na() and is.nan(). y=c(0,1,2,3,4,NA) x=c(0,1,2,3,4,NA) (d=x/y) ...


0

A pesky feature of rasters is the multitude of "no data" possibilities, and how software doesn't consistently deal with it. What I expect that GRASS is doing is assigning minus infinity to the missing values. While not the best of options, you could try to go about it the other way around, eg. identify all acceptable values and then assign NA to the ones ...


0

You can always inspect the GDAL utilities for how they do it. For example, if you just want to "chip out" a section of an image, you could use gdal_translate -srcwin. The simplest way would just be to invoke gdal_translate (e.g. with a system() call, or maybe a CreateProcess() call if you're on Windows). Otherwise, you'd could read the code for ...


2

Spectral mixture analysis / sub pixel analysis is designed for hyperspectral data, not a 3-band aerial photograph. However, you can try it and see if the output is useful. A tutorial can be found in this pdf and in this ppt/pdf. You will have to skip a significant number of the steps, as you don't have the same amount of information in your dataset. In ...


1

One strategy is to use a nan_to_num function from Numpy, however it always uses 0. for nan, and there are unfortunately no parameters to replace nans with custom values. $ gdal_calc.py -A nan.tif --outfile=result.tif --calc="nan_to_num(A)"


1

This might be totally tedious but if you convert to Esri ASC (GDAL_Translate -of AAIGRID) which is a text based format and then open in a really good text editor like Notepad++ or VI/VIm, or write a python script, you can replace bad values using find & replace. Then save & close the file and translate to a GeoTiff


1

You can use the flag --NoDataValue=NODATAVALUE to replace NoDataValue. See the third example here


1

I agree with @BradHards comment - it would be best for you to let us know more details. I'll assume you are new to the GIS space, and answer for ease of use. Check out Tilemill from mapbox. It is easy to start with and will allow you to visually set up bounding box, zoom levels, starting zoom, etc. and then you can directly export to .mbtiles


1

If you want to preserve the size of your raster, you have to specify that in the gdalwarp command line. Otherwise gdalwarp tries an own guess, based on the average of x and y source resolution preserving the extent, leading to square raster cells. It is pure coincidence that the pixel and line values are swapped in your case. You can force to preserve the ...


-1

Also, check LAStools: http://www.cs.unc.edu/~isenburg/lastools/ for rapid and clean processing of lidar data. This link will show you how lastools can be used in a workflow for tree crown calculations: http://rapidlasso.com/2014/10/23/discriminating-vegetation-from-buildings/


3

A literature search would provide you a wealth of information! Bob McGaughey with USFW-PNW in Seattle, is the developer of FUSION and I am sure would hand over the source code for watershed segmentation. Randy Wynne is at Virgina Tech and developed an IDL virtual machine program implementing a variable window filtering approach Popescu & Wynne (2004). ...



Top 50 recent answers are included