{"id":1055,"date":"2015-06-04T01:24:19","date_gmt":"2015-06-04T01:24:19","guid":{"rendered":"http:\/\/blogs.lincoln.ac.nz\/gis\/?p=1055"},"modified":"2023-05-07T04:09:00","modified_gmt":"2023-05-07T04:09:00","slug":"trekking-the-high-himalaya-for-data","status":"publish","type":"post","link":"https:\/\/blogs.lincoln.ac.nz\/gis\/trekking-the-high-himalaya-for-data\/","title":{"rendered":"Trekking the High Himalaya for Data"},"content":{"rendered":"

This post covers how a range of different remotely sense data sets can be acquired from around the world with a focus on Nepal<\/em><\/p>\n

In a recent post<\/a>, we looked at how Open Street Map<\/a> can be used to acquire some basic geospatial data for many parts of the world. \u00a0When we left off, we were still looking for some elevation data for Krishna and came upon the possibility of downloading contours from OSM as seen below on the Cycling map:<\/p>\n

\"OSMContours\"<\/a><\/p>\n

With a bit more digging, we determined that this wasn’t possible – but we were able to figure out where the contour\u00a0data came from. \u00a0And better still, we figured out how we could get a copy of it. \u00a0From the OSM Wiki<\/a>, we determined that the contours were derived from a DEM that had been derived from data collected on a space shuttle Endeavour mission in 2000. \u00a0The mission aim was to map the majority of the earth’s surface (~80%) using radar, thus enabling the creation of an almost complete global DEM. \u00a0This was the Shuttle Radar Topography Mission<\/a> (SRTM). \u00a0In the shuttle’s payload bay was a radar transmitter, sending out a strong radar signal. \u00a0Also in the bay was a receiver. \u00a0A \u00a060 metre boom extended out from the payload bay \u00a0with another receiver at the far end of it.\u00a0 The radar reflections were\u00a0received by the two antennae; the separation between the two allowed for a stereoscopic view of the earth’s surface which, after some pretty grunty computations, resulted in a reasonably high resolution DEM.<\/p>\n

\"shutscan\"<\/a><\/p>\n

And here’s a map of the coverage. \u00a0The colours indicate the number of times a particular area was covered (red means no coverage).<\/p>\n

\"srtm_covmap_lo\"<\/a><\/p>\n

Not too shabby. \u00a0This being a US funded project,\u00a0SRTM data for regions outside the United States were sampled for public release at 3 arc-seconds, which is 1\/1200th of a degree of latitude and longitude, or about 90 meters. \u00a0Those areas in the US were released at 1 arc-second, or roughly\u00a030 m. \u00a0Last year, NASA agreed to release the 30 m data for the rest of the world so things have suddenly gotten a whole lot finer. \u00a0A selfish look at the figure above indicated that Nepal had been covered at least once, so there was hope for Krishna. \u00a0Some more digging got us to the US Geological Survey’s Earth Explorer<\/a> website:<\/p>\n

\"EarthExplorerMain\"<\/a><\/p>\n

From here, we could pan the map over to the area we were interested in and then search for which data are available. \u00a0This is a warehouse of remotely sensed data so we’ll have a very quick look at what’s available, with a particular interest in elevation data. \u00a0Having navigated over to the Mustang district, we could use the cursor to click the four corners of a box around our area of interest:<\/p>\n

\"EarthExplorerJomsom\"<\/a><\/p>\n

Next, we’ll click on the Data Sets tab and see what’s out there.<\/p>\n

\"DataSets\"<\/a><\/p>\n

(One got cut off at the bottom – it’s vegetation monitoring.) \u00a0We could spend a few days going through each of these (and I invite you to browse) but for now let’s focus on the Digital Elevation entry. \u00a0When expanded, it looks like this:<\/p>\n

\"DigitalElevation\"<\/a><\/p>\n

So we can clearly see some SRTM entries, as well as a number of others. \u00a0If we stay focused on SRTM for now, we’ve got four to choose from: 1 Arc-Second Global (at ~30 m), Non-Void Filled (90 m), Void Filled (90 m) and Water Body Data (90 m). \u00a0 Clicking on the “i” takes you to a page with more information (metadata) on that layer. \u00a0I’m pretty keen on that 1 Arc-Second data so I’ll tick the box next to it and hit “Results” at the bottom of the page.\"Results\"<\/a>\u00a0We got a nice hit off of that – clicking the footprint button, \"Footprint\"<\/a>, displays its extent on the map (the larger, light red box) – we’re covered! \u00a0Next step is to download this. \u00a0You’ll see the “download options” button to the right of the footprint. \u00a0Note that you’ll need to register to get a username and password, but that’s no big deal.<\/p>\n

\"DownloadOptions\"<\/a><\/p>\n

Here\u00a0we’ve got three options. \u00a0Both BIL and DTED will require a bit of pre-processing before we can use them, but a GeoTIFF we can use almost<\/em> straightaway so let’s grab that.<\/p>\n

A GeoTIFF is an image format that also has geographical data built in, particularly a coordinate system. \u00a0This means that when I add it to a map, it will automatically be placed in its correct position (depending on the system), which is quite handy. \u00a0And even though it’s a TIFF, we can work with it as if it were a regular raster grid that we’re more used to working with. \u00a0Here it is added to an ArcMap map:<\/p>\n

\"DEMinAM\"<\/a><\/p>\n

Note the coordinates in decimal degrees (at lower right) and elevations ranging from 850 to 5033 m (in the legend). \u00a0Here’s a hillshade derived from this:<\/p>\n

\"Hillshade\"<\/a><\/p>\n

Almost there – before we can do much with this grid (e.g. slope, aspect) we need to project it from its current system, which is a geographic coordinate system (WGS84 to be exact, the one used by GPS) to a projected one. \u00a0So here goes.<\/p>\n