{"id":2193,"date":"2018-09-14T11:59:24","date_gmt":"2018-09-13T23:59:24","guid":{"rendered":"http:\/\/blogs.lincoln.ac.nz\/gis\/?p=2193"},"modified":"2023-05-07T00:48:44","modified_gmt":"2023-05-07T00:48:44","slug":"some-very-cool-data","status":"publish","type":"post","link":"https:\/\/blogs.lincoln.ac.nz\/gis\/some-very-cool-data\/","title":{"rendered":"Some Very Cool Data"},"content":{"rendered":"

This post reviews LiDAR data available for the southern continent and the Dry Valleys in particular.\u00a0 From the raw data we derive a high resolution DEM.<\/em><\/p>\n

I hate to say this, but some data are cooler than others\u00a0(Ed. What a geeky thing to say…)\u00a0<\/em>\u00a0and LiDAR data<\/a> certainly fit into that category.\u00a0 We’ve talked about LiDAR\u00a0earlier<\/a>\u00a0– safe to say this it is revolutionising geospatial data one DEM at a time.\u00a0 I’ve been doing a bit of reading on that rather large continent to our south and wondered if the LiDAR revolution had arrived on its shores.\u00a0 The short answer is yes.<\/p>\n

With a bit of help, I found the Polar Geospatial Center<\/a> (sic), which “provides\u00a0geospatial support, mapping, and GIS\/remote sensing solutions<\/span>\u00a0to researchers and logistics groups in the polar science community”.\u00a0 Be still my beating heart…!\u00a0 Under “Data + Services > Elevation” there’s a section on the McMurdo Dry Valleys LiDAR (could someone call a doctor please?) which\u00a0includes this image:<\/p>\n

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WE NEED 50 CCs OF EPINEPHRINE STAT!<\/p>\n

So, once I was revived, I followed this inviting looking link:\u00a0\"\"<\/a><\/p>\n

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Some potentially nice looking stuff in here – tifs, maps, docs.<\/p>\n

When working with LiDAR data a common file format is “las” files.<\/p>\n

So that’s my next stop:<\/p>\n

Lately I’ve been a bit interested it the Dry Valleys<\/a> and the Wright Valley in particular and the image above suggested I look in a folder called “Northern_DV_South”.\u00a0 This folder contained no less than 359 las files and (gulp) 39.3 Gb of data.\u00a0 Okay, I couldn’t resist – don’t tell ITS<\/em> – but I downloaded the whole lot using an FTP client:<\/p>\n

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Three days later (no, more like three hours really) I had these on my hot little hard drive (Ed. that sounds quite risque – can you tone it down please?)<\/em>.\u00a0 Each of these las files is a subset of the original data, broken down into rectangular tiles roughly\u00a01 km by\u00a01 km in size.\u00a0 This is quite standard for packaging up LiDAR data – this has its pluses and minuses but as a next step I needed to know where all these tiles are.\u00a0 I found one in the docs directly and downloaded it as a shapefile (there are 4062 tiles, shown below in ArcGIS Pro):<\/p>\n

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I’ll focus in on the upper end of the Wright Valley for these next stages – I’m aiming at creating a high resolution DEM.<\/p>\n

In this image I’m zoomed in on the upper Wright Valley with one of the tiles selected:<\/p>\n

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I’m going to need to know which tiles relate to this area which will be a bit of a trick, given the complex file names.\u00a0 Also note the Pt_Count (number of LiDAR points) in the las file for this tile: 3,202,421!\u00a0 And that’s just one tile!\u00a0 Also note the Pt_Spacing (average distance between LiDAR points) of 0.5588 m.\u00a0 That’s a lotta points…\u00a0 So, to make a long story short, I’ve identified all the tiles I want to use for my DEM (225) and created a LAS Dataset<\/a> – this is a data structure that makes it a lot easier to manage all those points – there will be 901,999,433 in total to work with – I’m worried I’m going to break something…<\/p>\n

First step is to create my LAS Dataset using the aptly named “Create LAS Dataset” tool (who comes up with these names?).\u00a0 When displayed, it doesn’t look like much:<\/p>\n

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That’s because the points only display once we zoom in beyond a certain scale, around 1:5,000.\u00a0 The image below is around 1:2,000 to give you a sense of the density of points:<\/p>\n

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(Purple Rain<\/a> anyone?)<\/p>\n

Here it is in ArcScene:<\/p>\n

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This is nice for being able to visualise the data but to make it much more useful we really need is a raster DEM.\u00a0 I won’t go through the excruciating details (and several hours of processing time) but the raster output is shown below with a bit of transparency and a hillshade in a 3D Scene in Pro:<\/p>\n

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Sorry, but I just fell off my chair…there’s some exquisite detail in this DEM.\u00a0 Here’s Don Juan Pond<\/a>, perhaps the most saline\u00a0water body on the face of the earth:<\/p>\n

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And here’s a view looking east from the top of the valley roughly 20 km to the end of the dataset – awesome:<\/p>\n

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If you’re interested in playing around with this dataset, let me know and I’ll make it available on J: in all its glory.<\/p>\n

As a final Antarctic note, a new 8m resolution DSM of all of Antarctica<\/a> has recently been released and it’s stunning.\u00a0 This New York Times article<\/a> gives you an overview.<\/p>\n

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Most data are cool, but some data are cooler than others – and these are particularly good examples.<\/p>\n

C<\/p>\n

\n","protected":false},"excerpt":{"rendered":"

This post reviews LiDAR data available for the southern continent and the Dry Valleys in particular.\u00a0 From the raw data we derive a high resolution DEM. I hate to say this, but some data are cooler than others\u00a0(Ed. What a geeky thing to say…)\u00a0\u00a0and LiDAR data certainly fit into that category.\u00a0 We’ve talked about LiDAR\u00a0earlier\u00a0– […]<\/p>\n","protected":false},"author":3,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-2193","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/blogs.lincoln.ac.nz\/gis\/wp-json\/wp\/v2\/posts\/2193","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/blogs.lincoln.ac.nz\/gis\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blogs.lincoln.ac.nz\/gis\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blogs.lincoln.ac.nz\/gis\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/blogs.lincoln.ac.nz\/gis\/wp-json\/wp\/v2\/comments?post=2193"}],"version-history":[{"count":1,"href":"https:\/\/blogs.lincoln.ac.nz\/gis\/wp-json\/wp\/v2\/posts\/2193\/revisions"}],"predecessor-version":[{"id":4018,"href":"https:\/\/blogs.lincoln.ac.nz\/gis\/wp-json\/wp\/v2\/posts\/2193\/revisions\/4018"}],"wp:attachment":[{"href":"https:\/\/blogs.lincoln.ac.nz\/gis\/wp-json\/wp\/v2\/media?parent=2193"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blogs.lincoln.ac.nz\/gis\/wp-json\/wp\/v2\/categories?post=2193"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blogs.lincoln.ac.nz\/gis\/wp-json\/wp\/v2\/tags?post=2193"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}