I really should try to get and save as many of the election district maps from county rest servers as possible before the year is up because with redistricting they will be changing the lines and for certain projects it sure would be nice to have the old ones to compare to new ones, especially in an automated fashion by using join by location in QGIS.
Mapping
ArcGIS
Been doing a lot of reading of some of the ERSI ArcGIS tutorials not because I’m interested in learning more about the commercial software but more seeking out more skills and terminology I can use to do neat new projects with QGIS.
Landsat 8 Image Classification using QGIS
Panchromatic Imagery And Its Band Combination In Remote Sensing
A panchromatic band (black and white band) is one band that usually contains a couple of hundred nanometers bandwidth. The bandwidth enables it to hold a high signal-noise, making the panchromatic data available at a high spatial resolution. This images can be gathered with a higher resolution since the spectral range give the smaller detectors allowance to be utilized while sustaining the high signal-noise ratio.
This capability allows the smaller portion to be seen and still acquire strong signals. Therefore the Panchromatic usually resembles a wide band that has a lower spatial resolution (mostly a half less than the multispectral band) that the exploration of the imagery details.
Learn GIS for Free – GIS Lounge
Discovering “REST/Services” that are put out by county governments is one of the best things I’ve found on the Interwebs in a long time
Discovering “REST/Services” that are put out by county governments is one of the best things I’ve found on the Interwebs in a long time.
Grass, Smoothing Shapefiles, Polygonizing Raster Data
I’ve been working on doing some new Google Maps for my blog with QGIS. Here are some areas I’ve been exploring that I thought might be useful to the mappers of the world.
Simplification and Smoothing of Shapefiles
Sometimes we need a simplified version of a vector, to have a smaller file size and get rid of unnecessary details. Many tools do this in a very rough way, and miss the adjacency and sometimes the topological correctness of polygons. GRASS is the ideal tool for this: being a topological GIS, adjacency and correctness are preserved even at very high simplification levels. In our case, we have a vector resulting from a raster, thus showing a “saw” pattern at borders.
Applying a simplification results in straight lines:
GRASS ‣ v.generalize [Maximal tolerance value: 30 m]
We can also do the reverse, and make a layer more complex, smoothing out sharp corners:
GRASS ‣ v.generalize [method: chaiken]
This v.generalize tutorial also has many helpful tips on the various options of the library to get better smoothing results and reduce file sizes. It’s fantastic how much of the power of GRASS has been integrated into Quantum GIS.
Converting Raster Data Into Stepped Vectors
In QGIS 3.4.1, there is a Reclassify by table tool which is located under Processing toolbox -> Raster analysis -> Reclassify by table.
After reclassify the data, you can use Vectorize tool to convert the raster into vector data. The Vectorize tool exists in both QGIS 2.18 and 3.4.
This is very helpful for converting a raster image within a certain area into a polygon for creating a Google Map or other map.