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 ...
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
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 ...
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 ...
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 ...
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)
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 ...
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 ...
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 1 ...
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 ...
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/...
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 ...
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 ...
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 ...
Basic steps to get elevation data in GPS points:
Obtain an elevation raster for your area of interest. You'll need a DEM (Digital Elevation Model) raster, which is a raster of pure elevation data without any labels or additional features. (Google terrain is not an elevation raster, it's a combination of a "hillshade" or "shaded relief" raster with ...
I use the "Buffer" option on the "Label setting" tab. (Using the labels button, not the old labels option on the layer properties dialog.) This does not wipe out the contour line, as I imagine you are wanting to do, but it does make the label legible.
In addition to what has been mentioned there are a few more things to consider. You can enhance the 3-dimensional impression of the map by not only varying the color hue but also the saturation, brightness and vibrance. Saturated colors will appear closer and are suitable for mountain tops while the lowlands and valleys can be colored rather unsaturated or ...
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 ...
I think I can answer it for you.
If you look at the precision vs. accuracy image on the link you provided, precision refers to the repeatability of the observation. For example, if I measure the distance from one point to another and it is always vaying only by a very small amount, then I am making measurements at a high precision.
But, basically, ...
One thing to keep in mind is that lat/long is geodetic and not geocentric:
If we were to calculate elevation as a radius from the center of the ellipse, our elevation lat/long would be different than our horizontal lat/long!
This is why there are two different datums. The horizontal datum is just a smooth ellipse, because it's easier to do trig functions ...
Building on Michael's excellent answer, I would recommend using the Con (Spatial Analyst) tool to take a "slice" out of your DEM. The first screenshot shows the parameters you would likely want to use. The second screenshot shows the results of the Con function (as stylized MDOW hillshades) derived from the resulting DEM's.
Subtract the trend surface from the DEM.
Linear trend (1st order polynomial)
2nd order polynomial trend
Per @radouxju's comment - the trend line can be shifted down to avoid negative values by adding the minimum value.
In the Raster Calculator:
"DEM" - Trend("DEM") + N
Where: N = Minimum raster value in the DEM
The easiest way is to import your points into a format that can be queried with SQL, like PostGIS, SQLite or Shapefile (using OGR).
Then you can query:
FROM [table] a, [table] b
WHERE a.[featureid] <> b.[featureid]
AND ST_Z(a.[geometry]) - ST_Z(b.[geometry]) >= 200;
Or you can query and make lines in one step:
Your elevation points are definitely regularly aligned and hence there is no need to bother about nearest neighbors. The value of the pixel in which your point fall into is always the value of the nearest neighbor.
1) Load all the raster in one command like this:
raster2pgsql -t 10x10 -I -C c:/temp/*.dem schema.table | psql -U postgresuser -d database
Your question title and content are a little ambiguous as to what you are asking. As for checking to see if a shapefile has z information, which seems to be your ultimate question, is as follows:
Open the shapefile in ArcMap, go to the layer properties (right-click -> properties, or simply double-click) and go to the source tab. Look under Data Source, ...