Grass and ArcGIS use different conventions for the flow direction rasters created when processing a DEM to create watersheds. I need to convert a GRASS flow direction raster to the ArcGIS convention. Here’s how I did it.
A bike trip out to the wadi where a few small acacia seedlings are struggling to survive showed, not surprisingly, that they were pretty dried up. We’ve learned to expect that in our 40+ degree temperatures thru the summer. But I took measurements of the seedling that I’m following, and the results reinforced my optimism:
Acacia Seedling dataPhysiological measurements of this tree
located at: Longitude 35d10'18.533"E and Latitude 30d47'33.321"N
Elevation -40 m
canopy width (cm.)
trunk diameter (cm.)
I’ll look forward to another visit thru the winter – hopefully after some rainfall – when I expect to see even more growth.
We have a large set of LIDAR data, in separate *.las file, each covering a small rectangular area. I wanted to create a polygon shapefile of the coverage of each tile for reference so I know which files to choose when we need a subset of the whole region. Using a bash “one-liner” and a simple function in Spatialite I had my polygon layer.
Nearly every new phone or tablet these days comes GPS enabled. And you can choose any of a slew of apps to capture GPS waypoints and tracks. But how do you get these data into a GIS system? Several apps save the GPS data into an sqlite database, so using Spatialite to convert the locations to spatial layers is a piece of cake.
Last week the Bank of Israel published drafts of the set of new currency to be put into circulation soon. For this print cycle it was decided to showcase Israeli poets, instead of the usual political figures. What’s more, a stanza from each poet’s work will be printed on the new bills. The four writers that will appear on the 20, 50, 100, and 200 shekel bills include Rachel (Bluwstein) the poet, Shaul Tchernehovsky, Leah Goldberg, and Natan Alterman. Nice touch bringing a wiff of culture into the markets and fast food stands.
Our regional Drainage Authority prepared a reservoir at the mouth of a small dry riverbed to catch and regulate flood water coming from a mountain canyon. This reservoir was to act as a buffer to prevent flooding of agricultural fields and residential areas further down the valley. After a sudden rainstorm last week, the reservoir bravely fulfilled (pun intended ) it’s duty. Now we want to know how much water was actually captured, and to create a depth volume curve for the small “lake” that was formed. Here’s how I did this using GRASS.
The new labeling setup in QGIS has been around for over a year now, and in the upcoming version it will become the default, replacing the old labeling. This new engine brings some advanced options that are quite worth learning, such as bulding labels from expressions, and conditional labeling. I’ll expand on some of these tricks that have already appeared in other QGIS blogs
In hydrology, a stream network is composed of segments or “reaches” which are arranged in a hierachy. There are several systems of ordering the stream reaches, the most popular of which is the Strahler or Horton number. GRASS GIS offers, alongside the watershed delineation tool r.watershed (discussed here), a set of addons for stream network analysis. We’ll examine how to use these addons, and how to use strahler ordering to improve the visual effect of a stream network map.
I returned from a short bike outing with my ride captured as a GPS track. Along the way, I also grabbed the rest stops as waypoints. Both of these were downloaded from the GPS as *.gpx files. So I have tracks.gpx and waypoints.gpx. Now I want to push these layers straight into Spatialite, and do some calculations.