This page explains and demonstrates with working scripts how to obtain and read SRTM elevation data for use in an on-line map or similar geo-app.
Before play there is work, getting the data. Although free, and tolerably well documented, the number of small files that have to be downloaded, as opposed to just a few big ones, turns obtaining SRTM data into something of a chore. Here are the most important links concerning SRTM data:
SRTM data comes in several resolutions, but only the two most detailed are covered here, 1 arc second2 (approximately 30m2 at the equator) and 3 arc second2 (~90m2). For both, the data is held in files called tiles, one for every degree2 of longitude v latitude where there is some land (areas that are all sea have no tiles). For the 1" data, each tile contains 3601×3601 pixels, for the 3" data, each tile contains 1201×1201 pixels. Note in each case the extra row and column, which allow the rows and columns at the edges of each tile to repeat the corresponding data from neighbouring tiles, thus making it easier programmatically to scan from tile to tile. Each pixel consists of a two-byte binary value in big-endian order (high byte followed by low byte), where -32768 (0x80,0x00) represents a data void, any other value a genuine elevation relative to the WGS84/EGM96 geoid, for which average global sea-level is approximately zero. Note also that within each tile the data is stored in row-major order (x longitude within y latitude), and, like an image, from the top of the tile to the bottom.
Obviously, you must download enough of the actual data to cover your area of interest, but, due to the density of it, you will probably want to stop at that, as server space is usually a constraint.
This section gives metadata for the SRTM tiles covering all of the British Isles, by which is meant England, Scotland including all the remote islands, Wales, all of Ireland, The Isle Of Man, and The Channel Islands, but excluding Rockall in tile N57W014:
* SRTM data gives out at 60°N, which unfortunately for us in the UK is half-way up The Shetlands. The 1 arc second data doesn't include 60N tiles at all (hence it has 3 fewer), while the 3 arc second data includes them, but their data is incomplete and incompletely processed to remove noise. See the section 60°N below for further details.
|1 arc second2 (~30m2)||3 arc second2 (~90m2)|
There are no SRTM 1" tiles for latitude 60°N, while the 3" tiles have no valid data north of latitude 60.385°N, and the sea south of that line contains noise which in other tiles lying within the main SRTM band of coverage would have been removed, and further this noise is also present in the top, shared, line of pixels of those tiles from 59°N which have neighbours to the north at 60°N. Thus, in the UK, the five land tiles (one is all sea) that cover The Shetlands are affected: N59W002, N59W003, N60W001, N60W002, N60W003. For most purposes in this area, raw SRTM data would be unusable, and alternative data, for example from OS's Terrain 50, must be used instead, either as from source, or else to construct replacement SRTM tiles. To illustrate, the affected tiles are here converted into images - that on the left is raw SRTM, that in the middle is made from tiles created from Terrain 50, while that on the right compares the two:
The two numbered sections shown below demonstrate what this does to profiles returned by the scripts:
Section 1 between (60.25N,1.25W) and (60.5N,1.25W) demonstrates the biggest problem, the total loss of data north of 60.385N. The first profile is from raw SRTM, the second from tiles made from Terrain 50:
Section 2 between (60N,1.325W) and (60.385N,1.325W) demonstrates the second problem, the noisy sea. Again, the first profile is from raw SRTM, the second from tiles made from Terrain 50. Although after averaging the image doesn't show it that clearly, the noise in the first gives points in the sea that are up to 8m below sea-level:
Replacement Shetland tiles made from OS Terrain 50 data: SRTM3-OST50-Shetlands.zip
This table gives estimates of some of the metadata for the SRTM tiles covering the world, but if you want to see coverage at a finer detail you will have to look at the coverage map
|1 arc second2 (~30m2)||3 arc second2 (~90m2)|
These are two versions of fundamentally the same underlying Python script. The first is
designed to run as a standard CGI script on a
webserver, the second as a Google App. By default, both use SRTM 3" (90m) tiles, but can
be altered to use 1" (30m) tiles by changing all references in the following lines 163/167ff
from SRTM3 to SRTM1:
# Relative path to tiles
By default, either set of tiles, or the zips containing them, are expected to be in a sub-directory
named SRTM beneath that where the script is hosted. Debugging output is HTML5
compliant and requires two other files, an HTML
template, which varies at least slightly from script to script and therefore is named after the
script to distinguish it from others1, and an invariant
CSS stylesheet, by default named Minimal.css.
Path = SRTM3Path
# Unzipped file name template
FName = SRTM3FileName
# Zipped file name template
ZName = SRTM3ZipName
# Tile width (sample points)
X = SRTM3Cols
# Tile height (sample points)
Y = SRTM3Rows
# Angular resolution (radians)
ARes = SRTM3AngRes
1 As it happens, here the only difference between these two HTML templates is the line that loads the stylesheet.
Obviously, in both cases these defaults can be changed to suit individual requirements, but the scripts (for the SRTM data and template paths) and/or the templates (for the stylesheet path) then must be edited accordingly.
Both scripts are self-documented. Instructions for use are included as leading comments, and also are displayed in response to errors in calling them.
If using one of these scripts, and scarcity of available server or web space so demands, the tiles can be left zipped, as, when looking for a tile, the scripts will look first for an unzipped version of it, but if that is not found they will then look for a zipped version. Inevitably however, leaving the data in its original zips will slow things down a little.
A profile point is returned for each intermediate SRTM cell up to 100 (the empirically determined maximum realistically displayable using a URL to the Google Charts API to draw the profile). If a profile path crosses more than 100 cells, then each of the 100 points returned is the average, or maximum if given the mx switch, of the cells crossed by the path that are closest to that sample point - that is, the profile returned is derived from all the cells it crosses, not just a sample of them.
The profiles returned have been shown to follow a geodesic to within 1m up to about 70km, further has not been tested.
For both script / template versions the stylesheet lists as follows:
It is beyond the scope of this article to document and support CGI. If required,
novices are referred to their webhost's online documentation and support for how to enable
Python CGI on their webservers. This article merely gives the basics for setting
up this CGI script. However, two points to note are to ensure that the
'shebang', the first commented line containing the path to the Python interpreter, is
correctly set, and that on Linux-hosted systems the execute attribute is set on the script
file, for example by using
chmod +x <path to file>.
By default the script would normally be put in the /cgi-bin directory off the site root. The default expected directory structure is therefore …
/cgi-bin/SRTM/<all the SRTM data *.hgt or *.zip files>
By default this is expected to be in the directory /cgi-bin off site root. The webserver CGI version lists as follows:
By default this is expected to be in the directory /Resources/Templates off site root and have the same base name as the Python script with an .html extension. The webserver CGI version lists as follows:
Right-click this link and choose Save As for a zip of the three files required for Server-side CGI: SRTMServerCGI.zip
It is beyond the scope of this article to document and support Google Apps. Novices are referred to Google's online documentation and the self-help groups they host. This article merely gives the basics for setting up this Google App, assuming you have already created a default app called <tag>srtm where <tag> is an id of your own choosing.
You may wish to investigate using the app's free quota, 5GB at the time of writing, of Google Cloud Storage (GCS) to store the tiles, so that they can be shared between app versions rather than having a separate copy of invariant data for each one. However, GCS is significantly slower than local file storage, particularly where a path goes over a sea area with no tiles, though this particular case could probably be significantly improved by adjusting retry parameters.
In addition to the default contents of the app's app.yaml file, it will
will need to import both the jinja2 and webapp2 libraries,
and to declare a static handler for the CSS file, as follows:
- name: jinja2
- name: webapp2
- url: /Resources/(.*\.css)
By default the app script would normally be put in the root directory of the app space, giving a default expected directory structure of …
/SRTM/<all the SRTM data *.hgt or *.zip files>
By default this is expected to be in the root directory of the Google App space. The Google App version lists as follows:
By default this is expected to be in the directory /Resources/Templates off root of the Google App space and have the same base name as the Python script with an .html extension. The Google App version lists as follows:
Right-click this link and choose Save As for a zip of the three files required for a Google App: SRTMGoogleApp.zip
Unfortunately, the only convenient way that I know of displaying a profile, the Google Static Image Charts API, has been deprecated since 2012. As per this discussion in their forum, they have made soothing noises, but these remain unofficial, and there is still no definite word on any possible replacement. If it were to go, this wouldn't be the first time that they've broken my work in this manner, and, as I don't suppose it will be the last, ideally what is needed is some sort of standard library that can be installed on one's own site, but I don't know of anything remotely comparable to the ease of just feeding Google a suitable URL.
However, at the time of writing in June 2015, it's still running, so here's how to use the service. It really is as simple as taking the URL returned by either Python script, replacing ~Width~ and ~Height~ by suitable dimensions (pixels), ensuring that the two when multiplied together come to less than Google's limit of 300,000, and then making the result the src attribute of an img tag in your web-page. Here's a demo, which, incidentally, also demonstrates the result of remaking the Shetland tiles - previously this profile had an entirely spurious cliff in the terrain at the point where the original SRTM data ended …
var imgWidth = 650;
var imgHeight = 250;
function callBack( data )
profData = data;
profData.url = profData.url.replace("~Width~",""+ imgWidth +"").replace("~Height~",""+ imgHeight +"");
var img = document.createElement("img");
img.id = "ProfImg"
img.style.width = imgWidth + "px"
img.style.height = imgHeight + "px"
img.src = profData.url
document.getElementById("ProfDiv").appendChild( img );