When in doubt follow Paul Ramsey's GeoTiff compression for dummies strategy.
-co COMPRESS=JPEG \
-co PHOTOMETRIC=YCBCR \
-co TILED=YES \
and if you need overviews too then add
--config COMPRESS_OVERVIEW JPEG \
--config PHOTOMETRIC_OVERVIEW YCBCR \
--config INTERLEAVE_OVERVIEW PIXEL \
For simplicity (because it was not mentioned in question) I am assuming the XYZ files are ready to be processed (i.e., no classification or filtering is needed) and that the content is suitable for whatever type of raster OP wants (DEM, DSM, etc.).
If one really wants/needs to work with ASCII files, one option to grid them is GDAL gdal_grid:
I was having problems with the QGIS and SAGA GUI tools mentioned in this thread (Raster values to points was failing for some reason and throwing unhelpful errors and the GRASS v.sample created a whole new layer which was not helpful). After failing with the GUI tools for a while, I tried doing this in the Field Calculator. It worked quite well and I was ...
A convenient way to get point cloud data to Python is to use the
PDAL Python extension. PDAL uses the concept of pipelines (much
like a GDAL VRT for point clouds instead of rasters) to allow users to orchestrate the processing of point cloud data. With the PDAL Python extension, you can
read a LAZ file into a Numpy array and then do whatever you need
There is very limited functionality for routing in QGIS. Using the Road Graph plugin.
There is extensive routing capability in PostgreSQL/PostGIS using pgRouting. This integrates with QGIS as well with the pgRoutingLayer plugin. However pgRouting is not a plug and play option, it requires quite a bit of setup to get a routeable network.
Finally there are ...
Since you will be using QGIS later on, QField is an option. You can create project in Qgis, prepare points layer with attributes needed for survey, add base layers...
after survey you only have to update project on your desktop to continue work with data.
Geopaparzzi and GvSig are good options also, simple interface. You would only have to manualy prepare ...
ESRI is great software, but, yes, be prepared to shell out a pretty penny. ESRI is a lot more user friendly and, in my opinion, when it comes to pretty maps, ESRI is on top. That being said, there are a few open source solutions out there that can compare to ESRI software. Some are easier to learn than others and some have a bit a steep learning curve.
According to this article Esri World Imagery can be used free of cost when all of the following conditions are met:
You have signed up for a free ArcGIS Developer account
You are not generating revenue from your app (in the form of advertisements or subscriptions)
Your users request < 1 million tiles/month
You properly attribute both Esri and all of ...
It appears that there isn't a single way approach to achieve the outcome you are seeking. However, that are several ways that you may be able to have the change to adjust the speed of your route animation.
Animate found route #101 is a suggestion from a user to add this feature -
Add an option to animate the display of a new route, such that it grows ...
Within GRASS GIS you can use r.neighbors which looks at each cell in a raster input file, and examines the values assigned to the cells in some user-defined "neighborhood" around it. It outputs a new raster map layer in which each cell is assigned a value that is some (user-specified) function of the values in that cell's neighborhood. Using the -c flag you ...
My currently preferred solution is Cesium Terrain Builder Docker. It is an extended version of the Cesium Terrain Builder with support for quantized-mesh-1.0 and can be easily run using Docker.
Processing steps are:
Reproject DEM tiles to EPSG:4326 (recommended), e.g. using gdalwarp
Create a Virtual Dataset (VRT) from the tiles using gdalbuildvrt
Kind of surprised that everyone recommended a software tool over what you wanted
I need an algorithm. Can anyone point me to a reference to such an algorithm, or to open source software that does this conversion?
Fairly well written is a lat/long to UTM conversion function written in Python - https://github.com/Turbo87/utm/blob/master/utm/conversion.py#...
maxcovr package in R: https://github.com/njtierney/maxcovr. This package implements the maximal coverage location problem model and supports a range of solvers (e.g. glpk and lpSolve). It is not in a GIS environment.
Location-allocation analysis in ArcMap (though not open-source):http://desktop.arcgis.com/en/arcmap/latest/extensions/network-analyst/location-...