First off, let me say how much I appreciate this question. I have seen so many example of inappropriate colour palettes applied to digital elevation models that it's good to see that people are thinking about this. There are some really good answers here too, but here is my opinion. I doubt that there is a universally good palette but rather a group of ...
I'll take it as a little exercise in how to program a data reader. Have a look at the documentation:
SRTM data are distributed in two levels: SRTM1 (for the U.S. and its territories and possessions) with data sampled at one arc-second intervals in latitude and longitude, and SRTM3 (for the world) sampled at three arc-seconds.
Data are ...
Altimeters use barometric pressure to measure altitude or elevation. Your watch likely uses a Baro-Altimeter. The problem with that is that the barometric pressure also changes with the weather. As the barometric pressure goes down your altimeter watch will think you are going up in altitude even though you are solidly on the ground.
For such watch ...
Yes, doable. Normally I'd suggest a partially transparent buffer, but I see why you want to do this cartographically.
This could be slow, and you need to manually decide where you want the labels to go - but cartographically speaking, that's not a bad thing!
Here's a screenshot...
As you can see, no buffers. The raster underneath is unaffected. I've ...
As a geologist, I often use this technique to make geological cross section in pure Python. I presented a complete solution in Python: Using vector and raster layers in a geological perspective, without GIS software (in French)
I present here a summary in English:
to show you how to extract the elevation values of a DEM
how to treat these values
Imagine several satellites spread out evenly above you. Now pick just one satellite. Visualise a sphere centered around that satellite with a radius of your exact distance from it. Do the same for every satellite in view.
What you're seeing now is a bunch of spheres that intersect exactly where you're standing. That's how a GPS reading works, ...
My suggestions would be to utilize reverb at http://reverb.echo.nasa.gov/reverb/. First register if you have not already done so. In the search box type ASTER GDEM and Select Dataset --- note if you want a particular area this is the point where you select the box range in the map window to the left (very useful feature!).
ASTER GDEM Global Digital ...
I usually come at this question from the angle of "what is going to enhance, and not obscure, my data?".
Tufte talks about the some of the uses of colours in maps: to label, to measure, to represent, and to enliven. Choosing DEM colours is usually mostly for the latter (enlivening) - to make them look nice. For example, the default 'atlas coloring' of many ...
The elevation above the ellipsoid (ellipsoidal height) is the elevation above a mathematical model that approximates the shape of the earth. The current most common one is WGS84. These are the elevations that you'd get from a GPS.
Orthometric heights are measured above the geoid or equipotential surface, that is, the surface of equal gravity. MSL is "mean ...
You are searching Extensions > 3D Analyst > Interactive 3D analysis tools.
How to create a profile graph from digitized features of a surface
1.In ArcMap, click the Layer drop-down arrow on the 3D Analyst toolbar and click the
surface that you want to profile.
2.Click the Interpolate Line button Interpolate Line button.
3.Click the surface and digitize ...
Expanding on one of themes in Simbamangu's very good answer: the basic problem with elevation shading using any colours at all other than neutral greys is the inescapable tendency for us to interpret meaning from the colours. For example a common rendering technique is to use deep greens for the valley bottoms, progressively lighten as one travels upslope, ...
Here's a more programmatic way of using GDAL than @Aragon's answer. I've not tested it, but it is mostly boiler-plate code that has worked for me in the past. It relies on Numpy and GDAL bindings, but that's about it.
import osgeo.gdal as gdal
import osgeo.osr as osr
import numpy as np
from numpy import ma
dataset = gdal.Open(...
Following on from the comments, here's a version that works with perpendicular line segments. Please use with caution as I haven't tested it thoroughly!
This method is much more clunky than @whuber's answer - partly because I'm not a very good programmer, and partly because the vector processing is a bit of a faff. I hope it'll at least get you started if ...
Defining ridges vs hill/mountain tops is pretty scale-dependent. Jeff Jenness covers conceptually how to model topographic landforms in his article Some Thoughts on Analyzing Topographic Habitat Characteristics. If you poke around on his website, you can find his poster on this as well, under ArcGIS tools > Land Facet Corridor Designer. (Link is here)
Creating watersheds should help you locate both ridges and hill top. Then, I would define a hill top as a local maximum, while a point on a ridge is not the maximum (there is one other point higher or equal to this point). You can identify local maxima using the focal statistic tool.
another way to look at the problem is to analyse at the opposite of your ...
The GEOCONTEXT-PROFILER will create an elevation profile just like Google Earth and you can import a KML and export a CSV. It should give you the same results as Google Earth.
This is the license restriction page that the tool links to.
Briefly, USGS has application services (Option #1), but for some data sets it's also possible to generate direct download URLs (Option #2) to the public location of files.
Download Option #1: USGS Application Services
There's documentation here about the web services that are available:
If you're interested in ...
The highest elevation within 10 km is the neighborhood maximum value computed with a circular 10 km radius, so just extract a profile of this neighborhood maximum grid along the trajectory.
Here is a hillshaded DEM with a trajectory (black line running from bottom to top):
This image is approximately 17 by 10 kilometers. I chose a radius of just ...
The best all round tool here is a raster calculator.
gdal_calc is a GDAL raster calculator implemented in Python here, with some examples here.
If you e.g. wants to keep values above +50:
gdal_calc.py -A input.tif --outfile=result.tif --calc="A*(A>50)" --NoDataValue=0
You can specify several files -A to -Z, where each of them get a corresponding ...
Since 2013 there is the EU-DEM 25 m: new Digital Surface Model (DSM), representing the first surface as illuminated by the sensors. You can download the GeoTIFF files here: http://www.eea.europa.eu/data-and-maps/data/eu-dem#tab-gis-data
In 2014/2015 there will be the release of the worldwide SRTM 30m data as announced here: https://www1.nga.mil/MediaRoom/...
The minimum contour interval is the double vertical error (RMSE or standard deviation) of the height model. You can find that for ASTER GDEM in:
Lang, R. Harold, and Roy Welch. 1999. “Algorithm theoretical basis document for ASTER digital elevation models.”
It's defined by the "United States National Map Accuracy Standards (NMAS)"
For example: If your ...
If you are looking to convert DEMs to contour lines:
QGIS Plugin Contours
For converting scanned topo maps to vector contour lines, Arcscan is one of the easiest (and most sophisticated) programs out there. However, there are several opensource alternatives, including a promising GRASS approach:
Trace vector contours from a scanned map.
I would highly recommend going through the Contour lines to DEM tutorial, available from GRASS wiki. Essentially, they describe different interpolation methods used to produce a DEM. Avoid IDW interpolation using contour lines (i.e. described in one segment of the tutorial) since this is an inappropriate use of the interpolation method. The GRASS module ...
Download and use a plugin called "Profile tool".
load your grid
load your polyline (layer)
run plugin (Plugins/Profile tool/ Terrain profile)
in field called "Selection" (below the profile chart) choose "Selected polyline" and choose your line
To simply get all grid values along the line switch tab from "Profile" to "Table" and there you can copy all ...
For a local solution, GRASS can be scripted to do this:
# extract raster values at our points
# use cubic convolution for interpolation between DEM locations
v.drape in=my_pts out=pts_srtm_elev type=point rast=srtm_dem method=cubic
I ran an extended version of this for one of my use cases and performance of v.drape was no issue at all.
OS Terrain 50 contours (10m contours) for Great Britain (England, Scotland and Wales)
It is supplied both as a set of 50m gridded digital terrain model (OS
Terrain 50 grid) and 10m contours and spot heights (OS Terrain 50
Notice: OS Terrain 50 contours and OS Terrain 50 grid are now available as of 8th July 2013.
Tip: Opt for the OS ...
Hypsography concerns the land's elevation, altitude or height above sea-level or some other reference surface. (Hypso is derived from the Greek Ύψος for height.)
Topography concerns physical and cultural features of the land and so includes hypsography, hydrology, the built environment, major boundaries, communication channels, etc. (Topo is derived from ...
In 2016, the Japan Aerospace Exploration Agency (JAXA) released a new free 30 m (1 arcsec) resolution global topographic data set called ALOS Global Digital Surface Model "ALOS World 3D - 30m" (AW3D30) (http://www.eorc.jaxa.jp/ALOS/en/aw3d30/). It is stated as having a 5 m height accuracy and has been compiled from images taken with the Advanced Land ...