{"id":2397,"date":"2019-05-30T10:20:26","date_gmt":"2019-05-29T22:20:26","guid":{"rendered":"http:\/\/blogs.lincoln.ac.nz\/gis\/?p=2397"},"modified":"2023-05-07T03:24:03","modified_gmt":"2023-05-07T03:24:03","slug":"wavelengths","status":"publish","type":"post","link":"https:\/\/blogs.lincoln.ac.nz\/gis\/wavelengths\/","title":{"rendered":"Wavelength(s)"},"content":{"rendered":"<p><em>Remotely sensed images are incredibly useful sources of GIS data.\u00a0 In this post we begin looking at using satellite images to create useful GIS data.<\/em><\/p>\n<p>Without giving too much away about myself, one of my top five absolute favourite <a href=\"https:\/\/en.wikipedia.org\/wiki\/Van_Morrison\" target=\"_blank\" rel=\"noopener noreferrer\">Van Morrison<\/a> songs is Wavelength, from the 1978 (egads!) <a href=\"https:\/\/www.allmusic.com\/album\/wavelength-mw0000651367\" target=\"_blank\" rel=\"noopener noreferrer\">album of the same name<\/a>.\u00a0 It might well be number one but please don&#8217;t force me to make such an important decision.\u00a0 I will always remember seeing him play this song on Saturday Night Live as a young lad and being forever changed after that (in a good way, I think).<\/p>\n<p><em>(I can&#8217;t find that video anymore but here&#8217;s one from Belfast `79)<\/em><\/p>\n<p><iframe loading=\"lazy\" title=\"Van Morrison - Wavelength - 2\/1\/1979 - Belfast (OFFICIAL)\" width=\"900\" height=\"506\" src=\"https:\/\/www.youtube.com\/embed\/CsEdUH3j1KU?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen><\/iframe><\/p>\n<p>This isn&#8217;t a post about Van Morrison, but it is one about wavelengths and how important they can be to GIS.\u00a0 I&#8217;m talking here about the use of remotely sensed images (from planes, satellites and UAVs) as a source of data, much of which depends on the wavelengths of light (well, more precisely, electromagnetic energy) captured in such images.\u00a0 Before we go too much further, we need to delve into the <a href=\"https:\/\/www.miniphysics.com\/electromagnetic-spectrum_25.html\" target=\"_blank\" rel=\"noopener noreferrer\">electromagnetic spectrum<\/a>:<\/p>\n<figure id=\"attachment_2398\" aria-describedby=\"caption-attachment-2398\" style=\"width: 1024px\" class=\"wp-caption alignnone\"><a href=\"https:\/\/www.miniphysics.com\/electromagnetic-spectrum_25.html\"><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-2398 size-full\" src=\"https:\/\/d-blogs.lincoln.ac.nz\/gis\/wp-content\/uploads\/sites\/3\/2019\/05\/electromagneticspectrum.jpg\" alt=\"\" width=\"1024\" height=\"454\" srcset=\"https:\/\/blogs.lincoln.ac.nz\/gis\/wp-content\/uploads\/sites\/3\/2019\/05\/electromagneticspectrum.jpg 1024w, https:\/\/blogs.lincoln.ac.nz\/gis\/wp-content\/uploads\/sites\/3\/2019\/05\/electromagneticspectrum-300x133.jpg 300w, https:\/\/blogs.lincoln.ac.nz\/gis\/wp-content\/uploads\/sites\/3\/2019\/05\/electromagneticspectrum-768x341.jpg 768w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/a><figcaption id=\"caption-attachment-2398\" class=\"wp-caption-text\"><em>https:\/\/www.miniphysics.com\/electromagnetic-spectrum_25.html<\/em><\/figcaption><\/figure>\n<p>Does this bring back memories of that high school physics class?\u00a0 The electromagnetic energy we&#8217;re probably most familiar with is the visible light our sophisticated remote sensors (eyes) are tuned to.\u00a0 But that&#8217;s just a small portion of the spectrum which covers several orders of magnitude of wavelengths.\u00a0 We are literally bathed in energy, much of it from the sun but just as much human-made.\u00a0 At one end of the spectrum are gamma rays &#8211; high frequency, short wavelength energy that is deadly &#8211; exposure to this stuff can damage your DNA and lead very quickly to death.\u00a0 Most everyone knows the benefits of lower frequency, longer wavelength X-rays\u00a0and of course there&#8217;s visible light that we rely on.\u00a0\u00a0When you feel the warmth of the sun on your arm, you&#8217;re experiencing invisible infrared energy.\u00a0 Yet lower frequency, even longer wavelength micro- and radio waves are also well known.\u00a0 In covering the spectrum we move from nanometres (10^-9 metres- a thousand- millionth of a metre!) through to metres and kilometres of wavelength.\u00a0 Practically speaking, GIS\u00a0makes the most use of\u00a0the narrow band between roughly 400 nanometres and 1000 micrometres &#8211; from blue through to thermal infrared (sensible heat).\u00a0 How do we work with these wavelengths?\u00a0 Mostly through aerial photos and satellite images.<\/p>\n<p>For example, here&#8217;s an aerial photo of Quail Island in Lyttelton Harbour:<\/p>\n<p><a href=\"https:\/\/d-blogs.lincoln.ac.nz\/gis\/wp-content\/uploads\/sites\/3\/2019\/05\/QICOLOUR.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-2410\" src=\"https:\/\/d-blogs.lincoln.ac.nz\/gis\/wp-content\/uploads\/sites\/3\/2019\/05\/QICOLOUR.jpg\" alt=\"\" width=\"2090\" height=\"1759\" srcset=\"https:\/\/blogs.lincoln.ac.nz\/gis\/wp-content\/uploads\/sites\/3\/2019\/05\/QICOLOUR.jpg 2090w, https:\/\/blogs.lincoln.ac.nz\/gis\/wp-content\/uploads\/sites\/3\/2019\/05\/QICOLOUR-300x252.jpg 300w, https:\/\/blogs.lincoln.ac.nz\/gis\/wp-content\/uploads\/sites\/3\/2019\/05\/QICOLOUR-1024x862.jpg 1024w, https:\/\/blogs.lincoln.ac.nz\/gis\/wp-content\/uploads\/sites\/3\/2019\/05\/QICOLOUR-768x646.jpg 768w, https:\/\/blogs.lincoln.ac.nz\/gis\/wp-content\/uploads\/sites\/3\/2019\/05\/QICOLOUR-1536x1293.jpg 1536w, https:\/\/blogs.lincoln.ac.nz\/gis\/wp-content\/uploads\/sites\/3\/2019\/05\/QICOLOUR-2048x1724.jpg 2048w\" sizes=\"auto, (max-width: 2090px) 100vw, 2090px\" \/><\/a><\/p>\n<p>This image was taken by a\u00a0slightly high-end (well, it was at the time) digital camera from an airplane at low altitude and has a resolution (pixel size) of about 0.72 m on the ground.\u00a0 It&#8217;s a raster image as you can see if we zoom in far enough to see the individual pixels:<\/p>\n<p><a href=\"https:\/\/d-blogs.lincoln.ac.nz\/gis\/wp-content\/uploads\/sites\/3\/2019\/05\/pixels.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-2405\" src=\"https:\/\/d-blogs.lincoln.ac.nz\/gis\/wp-content\/uploads\/sites\/3\/2019\/05\/pixels.jpg\" alt=\"\" width=\"514\" height=\"464\" srcset=\"https:\/\/blogs.lincoln.ac.nz\/gis\/wp-content\/uploads\/sites\/3\/2019\/05\/pixels.jpg 514w, https:\/\/blogs.lincoln.ac.nz\/gis\/wp-content\/uploads\/sites\/3\/2019\/05\/pixels-300x271.jpg 300w\" sizes=\"auto, (max-width: 514px) 100vw, 514px\" \/><\/a><\/p>\n<p>You&#8217;ll notice that the borders of the image are not straight &#8211; that&#8217;s because some of distortions in the image have been corrected &#8211; but more on that another time.\u00a0 There&#8217;s a lot that can be gleaned from this image &#8211; we could use it as a base map to create some digital layers of features that are visible.\u00a0 If we took several of these images over time we could track how the land cover is changing.\u00a0 Looking at this image with a bit more detail, we could note that it is in <a href=\"https:\/\/jpeg.org\/jpeg\/\" target=\"_blank\" rel=\"noopener noreferrer\">JPEG format<\/a> (i.e. the image name ends in .jpg).\u00a0 This is a very standard format for images that I suspect most of us are familiar with.\u00a0 If we look at the image in ArcCatalog, we can further note that\u00a0it is actually made up of three layers, or as we&#8217;ll come to refer to them more correctly, bands:<\/p>\n<p><a href=\"https:\/\/d-blogs.lincoln.ac.nz\/gis\/wp-content\/uploads\/sites\/3\/2019\/05\/Bands3.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-2411\" src=\"https:\/\/d-blogs.lincoln.ac.nz\/gis\/wp-content\/uploads\/sites\/3\/2019\/05\/Bands3.jpg\" alt=\"\" width=\"937\" height=\"491\" srcset=\"https:\/\/blogs.lincoln.ac.nz\/gis\/wp-content\/uploads\/sites\/3\/2019\/05\/Bands3.jpg 937w, https:\/\/blogs.lincoln.ac.nz\/gis\/wp-content\/uploads\/sites\/3\/2019\/05\/Bands3-300x157.jpg 300w, https:\/\/blogs.lincoln.ac.nz\/gis\/wp-content\/uploads\/sites\/3\/2019\/05\/Bands3-768x402.jpg 768w\" sizes=\"auto, (max-width: 937px) 100vw, 937px\" \/><\/a><\/p>\n<p>JPGs work off of a colour model known as <a href=\"https:\/\/en.wikipedia.org\/wiki\/RGB_color_model\" target=\"_blank\" rel=\"noopener noreferrer\">RGB<\/a>, for Red, Green and Blue.\u00a0 A digital camera has a separate sensor for each of these bands of energy and captures the various shades of intensities\u00a0for each colour in three separate images.\u00a0 When added to ArcMap, the software knows how to render these three bands as natural colour.\u00a0 (If you have a look at the image yourself, preview each band and see how the intensities change between the bands.)<\/p>\n<p>Let&#8217;s step things up a notch and look at a satellite image we recently acquired of Mt Grand Station near Lake Hawea:<\/p>\n<p><a href=\"https:\/\/d-blogs.lincoln.ac.nz\/gis\/wp-content\/uploads\/sites\/3\/2019\/05\/MtGrandPan.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-2402\" src=\"https:\/\/d-blogs.lincoln.ac.nz\/gis\/wp-content\/uploads\/sites\/3\/2019\/05\/MtGrandPan.jpg\" alt=\"\" width=\"1442\" height=\"868\" srcset=\"https:\/\/blogs.lincoln.ac.nz\/gis\/wp-content\/uploads\/sites\/3\/2019\/05\/MtGrandPan.jpg 1442w, https:\/\/blogs.lincoln.ac.nz\/gis\/wp-content\/uploads\/sites\/3\/2019\/05\/MtGrandPan-300x181.jpg 300w, https:\/\/blogs.lincoln.ac.nz\/gis\/wp-content\/uploads\/sites\/3\/2019\/05\/MtGrandPan-1024x616.jpg 1024w, https:\/\/blogs.lincoln.ac.nz\/gis\/wp-content\/uploads\/sites\/3\/2019\/05\/MtGrandPan-768x462.jpg 768w\" sizes=\"auto, (max-width: 1442px) 100vw, 1442px\" \/><\/a><\/p>\n<p>This is from the <a href=\"https:\/\/www.satimagingcorp.com\/satellite-sensors\/geoeye-1\/\" target=\"_blank\" rel=\"noopener noreferrer\">Geoeye-1<\/a> satellite with a 2.4 m resolution (Cost: ~$700 + GST).\u00a0 <strong><em>Lots<\/em><\/strong> of things to talk about here but let&#8217;s start by looking at this image in ArcCatalog:<\/p>\n<p><a href=\"https:\/\/d-blogs.lincoln.ac.nz\/gis\/wp-content\/uploads\/sites\/3\/2019\/05\/PanAC.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-2403\" src=\"https:\/\/d-blogs.lincoln.ac.nz\/gis\/wp-content\/uploads\/sites\/3\/2019\/05\/PanAC.jpg\" alt=\"\" width=\"964\" height=\"623\" srcset=\"https:\/\/blogs.lincoln.ac.nz\/gis\/wp-content\/uploads\/sites\/3\/2019\/05\/PanAC.jpg 964w, https:\/\/blogs.lincoln.ac.nz\/gis\/wp-content\/uploads\/sites\/3\/2019\/05\/PanAC-300x194.jpg 300w, https:\/\/blogs.lincoln.ac.nz\/gis\/wp-content\/uploads\/sites\/3\/2019\/05\/PanAC-768x496.jpg 768w\" sizes=\"auto, (max-width: 964px) 100vw, 964px\" \/><\/a><\/p>\n<p>Unlike the Quail Island image, it&#8217;s in <a href=\"https:\/\/www.techopedia.com\/definition\/2093\/tagged-image-file-format-tiff\" target=\"_blank\" rel=\"noopener noreferrer\">TIFF format<\/a> and has four bands: red, green, blue and an additional band with near infrared data (not all TIFs have four bands).\u00a0 Since it&#8217;s got data beyond just red, green and blue, an image like this is &#8220;multispectral&#8221;.\u00a0 And this extra band opens up a whole new realm of useful data that we can glean from this image.\u00a0 Plants are particularly active in the red and infrared bands &#8211; we can use this extra information in some image analysis to convert the pixels over to landcover.\u00a0 In this way, the image becomes more than just a good basemap &#8211; it&#8217;s a platform from which we can extract a variety of useful data, all relying on the wavelengths of energy captured.\u00a0 And there are more bands to be had.\u00a0 Below is previewed an image captured by one of the <a href=\"https:\/\/landsat.gsfc.nasa.gov\/\" target=\"_blank\" rel=\"noopener noreferrer\">Landsat satellites<\/a> &#8211; this one packs a whopping\u00a06 bands:<\/p>\n<p><a href=\"https:\/\/d-blogs.lincoln.ac.nz\/gis\/wp-content\/uploads\/sites\/3\/2019\/05\/SixBands.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-2406\" src=\"https:\/\/d-blogs.lincoln.ac.nz\/gis\/wp-content\/uploads\/sites\/3\/2019\/05\/SixBands.jpg\" alt=\"\" width=\"963\" height=\"622\" srcset=\"https:\/\/blogs.lincoln.ac.nz\/gis\/wp-content\/uploads\/sites\/3\/2019\/05\/SixBands.jpg 963w, https:\/\/blogs.lincoln.ac.nz\/gis\/wp-content\/uploads\/sites\/3\/2019\/05\/SixBands-300x194.jpg 300w, https:\/\/blogs.lincoln.ac.nz\/gis\/wp-content\/uploads\/sites\/3\/2019\/05\/SixBands-768x496.jpg 768w\" sizes=\"auto, (max-width: 963px) 100vw, 963px\" \/><\/a><\/p>\n<p>We might refer to an image as &#8220;<a href=\"https:\/\/gisgeography.com\/multispectral-vs-hyperspectral-imagery-explained\/\" target=\"_blank\" rel=\"noopener noreferrer\">hyperspectral<\/a>&#8220;.\u00a0 The additional bands take us further into the thermal infrared range of the spectrum &#8211; that much more\u00a0grist for the mill in\u00a0image analysis.<\/p>\n<p>Before we go whole-hog into that topic, there&#8217;s a key bit of processing that we need to cover.\u00a0 While 2.4 m is pretty decent resolution, we have the ability to transform this image into a 0.5 m resolution image.\u00a0 And why wouldn&#8217;t we if we could?!?\u00a0 It&#8217;s certainly a truism with imagery that the finer the resolution the better, so long as you&#8217;ve got enough storage space and processing power.\u00a0 This post should set us up nicely for several follow ons covering pan-sharpening, image analysis and vegetation indicies.<\/p>\n<p>I&#8217;m sure you can&#8217;t wait&#8230;\u00a0 So tee up a bit of Van Morrison (or whatever) on your turntable (or the device of your choice) until we can get to that.<\/p>\n<p>C<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Remotely sensed images are incredibly useful sources of GIS data.\u00a0 In this post we begin looking at using satellite images to create useful GIS data. Without giving too much away about myself, one of my top five absolute favourite Van Morrison songs is Wavelength, from the 1978 (egads!) album of the same name.\u00a0 It might [&hellip;]<\/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-2397","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/blogs.lincoln.ac.nz\/gis\/wp-json\/wp\/v2\/posts\/2397","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=2397"}],"version-history":[{"count":2,"href":"https:\/\/blogs.lincoln.ac.nz\/gis\/wp-json\/wp\/v2\/posts\/2397\/revisions"}],"predecessor-version":[{"id":4967,"href":"https:\/\/blogs.lincoln.ac.nz\/gis\/wp-json\/wp\/v2\/posts\/2397\/revisions\/4967"}],"wp:attachment":[{"href":"https:\/\/blogs.lincoln.ac.nz\/gis\/wp-json\/wp\/v2\/media?parent=2397"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blogs.lincoln.ac.nz\/gis\/wp-json\/wp\/v2\/categories?post=2397"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blogs.lincoln.ac.nz\/gis\/wp-json\/wp\/v2\/tags?post=2397"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}