Ross Edwards – Discovering Open Source

Testing NASA AMES Stereo Pipeline

By admin on November 17, 2020November 17, 2020Leave a Comment

Whilst looking for the best available open source solution to generate terrain heightmaps from satellite stereo pairs, I stumbled upon the results of an international IARPA ‘Multiple view Stereo 3D Mapping challenge‘. The entries that secured 2nd and 3rd place used variation’s of Ames Stereo Pipeine (ASP) NASA’s automated, open-source pipeline for mass production of digital elevation models (DEMs) from very high-resolution commercial stereo satellite imagery. I couldn’t wait to dig deeper and review it’s capabilities. I started by setting up a QGIS project file which allowed me to load up my results from numerous test runs covering every key permutation available for the 2 most successful algorithms, this enabled quick comparison of sometimes subtle differences in results:

SGM (Semi-Global Matching) – a proven stereo algorithm with widesread popularity.

MGM (More Global Matching) – is a variation of SGM that can produce superior output at the cost of longer run-time and higher memory usage.

I added a red background on every resulting raster to highlight area’s where the algorithm had not been able to process. Click below image to see animated testing:

Simulating snow on any terrain

By admin on November 16, 2020November 22, 2020Leave a Comment

Using Blender (2.90) I created a node group that can add procedural snow to any imported terrain. The node group can be applied with only a few adjustments required to each new environment. This can be controlled on X,Y and Z axis, this is particularly important for the Z axis in order to keep the snow off of the sea.

Open below juxtapose at full resolution

See below the node group required to generate a snow layer:

Stitching DEM’s spanning CRS projections in QGIS

By admin on November 25, 2019November 27, 2019Leave a Comment

I didn’t think this was going to be so troublesome! but wanted to note down the steps to resolve.

The ‘Build Virtual Raster‘ process in QGIS will not bring together multiple rasters if they span across 2 CRS projections

Following my initial post of the issue on GIS stackexchange:
https://gis.stackexchange.com/questions/342830/cant-join-multiple-dems-using-qgis-build-virtual-raster-if-they-span-2-crss
A users tip re unifying the projections for loaded data sent me in the right direction.

Virtual Terrain in Sketchfab

By admin on August 7, 2019September 19, 2019Leave a Comment

Despite the limit of 50mb per model uploaded on Sketchfab’s free service, you are able to get a surprising number of Tris within that limit. My Lyme Regis example below has 1.6million!

Flown imagery sourced from Bing, and DEM generated from Defra data.

Looks like Sketchfab are pushing the streaming tech with their new ‘MASSIVE‘ service allowing for 80million Tris+. Obviously this is on a paid service given the underlying models will be huge.

Creating Virtual Terrains with ‘Armory’ Blender plugin

By admin on May 1, 2019November 18, 2019Leave a Comment

Armory3d is a completely open source game engine that is fully integrated into Blender. Below is my first attempt at stitching a terrain mesh, layered with satellite/flown imagery, making use of the excellent BlenderGIS plugin. You can then simply export the project to an HTML5 application which can run on any browser.

See below a second attempt with some slightly higher resolution sat data, with some improvements to control methods (detailed below). Use WASD keys & left mouse button for controlling camera, sun direction and shadows can also be adjusted with keys – T,Y,G,H,B,N:

Object detection with Tensorflow & Yolo

By admin on April 16, 2019April 27, 2019Leave a Comment

Having installed Anaconda on Ubuntu to allow clean separation of python environments, I got hooked on the idea of Yolo’s image recognition capabilities.

So decided to install it – here’s my first attempts:

This blog post describes install steps concisely for YOLO v2.

Following image tests above, I then ran Tensorflow on an mp4 video file:

Testing flyby on Isle of Wight terrain

By admin on April 11, 2019January 6, 2023Leave a Comment

Examples from a project of mine showing what the RV4 (Arma 3) engine can produce:

Semi Automatic Classification Plugin (SCP)

By admin on April 3, 2019October 6, 2019Leave a Comment

Testing supervised classification using another QGIS plugin SCP.

Example showing Maximum Likelihood classifier:

SCP comes with the following classifiers:
– Minimum Distance – Euclidean distance
– Maximum Likelihood – Bayes’ theorem
– Spectral Angle Mapping

Supervised & unsupervised classification with Orfeo ToolBox (OTB)

By admin on March 15, 2019August 24, 2019Leave a Comment

Having discovered Orfeo ToolBox and it’s very handy QGIS plugin, I set about reviewing each of OTB’s supervised classifiers, to see which one performs the best with the goal of generating a perfect surface mask that I can use in my terrain project within RV4 engine.

Example showing source raster + libsvm_linear classifier:

Real world data QGIS to RV4

By admin on January 13, 2019May 5, 2019Leave a Comment

I recently finished off a tutorial covering steps required to get real world data into Arma 3 (RV4 Engine) using only open source tools:
https://github.com/rossoe/Arma3_QGIS

Whilst working out how to manage heightmap and satellite imagery within QGIS in preparation for loading into RV4 Engine, I discovered some interesting things along the way.

The first major issue reared it’s head following a GDAL update affecting the gdalwarp command, which broke a step I had been relying on – ‘Clip to raster by mask layer‘ I asked the question on gdal’s github page, and it was confirmed that I had to switch to use full extents, instead of the easier shapefile mask layer. See below original pipeline which mainly relied upon QGIS GUI config.

This lead me to invest more time learning the construct of the GDAL commands within QGIS’s python console. There is of course a lot more flexibility within command line than using the GUI.