{"id":1144,"date":"2015-08-13T01:29:56","date_gmt":"2015-08-13T01:29:56","guid":{"rendered":"http:\/\/blogs.lincoln.ac.nz\/gis\/?p=1144"},"modified":"2023-05-07T04:08:07","modified_gmt":"2023-05-07T04:08:07","slug":"getting-consistent-symbology-with-layer-files","status":"publish","type":"post","link":"https:\/\/blogs.lincoln.ac.nz\/gis\/getting-consistent-symbology-with-layer-files\/","title":{"rendered":"Getting Consistent Symbology with Layer Files"},"content":{"rendered":"

This post covers how you can get consistent symbology across several layers using layer files.<\/em><\/p>\n

So the good people in ERST310\/607 have been doing some fun analysis lately (though they may disagree), getting some high-resolution elevation models from LiDAR data (more to follow on that topic).  Using three separate datasets, they’re creating DEMs for three different points in time and using them to look at topographic changes as a result of the earthquakes.  In the image below, you can see the DEM (2 m resolution) from September 2010, just after the first major earthquake on the Greendale Fault.<\/p>\n

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

In the Table of Contents you can see the legend for the other two from February and December.  Notice the differences in the maximum and minimum values.  By default, ArcMap has shown the DEM as a “stretched” greyscale image, so even though there’s not much variation between the rasters, the highs of September will be shown as the same colour as the highs of December, even though the actual values are quite different.<\/p>\n

Is there a way to symbolise each to a consistent scale?  Yes, by using Layer files.  These are nothing more than files that save the symbology in a reusable way.  We can often end up putting lots of time into symbolising data to get an effective map and layer files provide us with a way to save those settings and reuse them.<\/p>\n

So first I’m going to judiciously choose a layer to symbolise , one that has maximum and minimum values that are the greatest and least, respectively so that the full range of values is covered.  That would be September (it’s got the highest maximum value and the lowest minimum value of the three).  I’ll  first open up the Symbology tab for that layer:<\/p>\n

\"Symbology1\"<\/a><\/p>\n

Change the “Show:” selection from Stretched to Classified:<\/p>\n

\"Symbology1A\"<\/a><\/p>\n

I’ll set up some custom ranges for the classes by clicking the Classify button – here I can set the number of classes I want to show and manually set my class ranges (among other techniques):<\/p>\n

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

The location of each break can be dragged left or right with a left-click and hold.  With an “OK” I’m back to the Symbology tab and can select a new colour ramp to emphasise the differences:<\/p>\n

\"Symbology2\"<\/a><\/p>\n

Here’s the result upon clicking “OK”:<\/p>\n

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

 <\/p>\n

Wow!  That jumps out at you a bit but is a bit of an improvement over a greyscale colour ramp.  If I’m happy with that effect, my next step is to save the symbology into a Layer file.  Right-click on the layer name and go to “Save as a Layer file”:<\/p>\n

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

The new file will have a “.lyr” extension.  Save it somewhere safe.  Now we’ll open up the Symbology tab for one of my other grids, February, switch it to a Classified render and import the layer file.<\/p>\n

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

From the Import button you can then point the raster to the layer file and the symbology from September gets applied to February:<\/p>\n

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

Yes, it pretty much looks the same, and, well, that’s the point!  The extent of the February grid is different because the extent of the original LiDAR data was different.  But with consistent symbology, we can now compare the two visually<\/em> <\/span>to detect any changes.  The layer file retains the information on the class ranges so I don’t need to fuss with redoing my classes for each grid.<\/p>\n

One really important thing to recognise here is that all we’ve done is change the way the data look<\/em><\/strong> rather than the data themselves.  The underlying data have not changed.  If we want to go a step further and carry out some analysis, we might need to reclassify the rasters or run some raster calculations.<\/p>\n

In this case, layer files have given us a way to keep our symbology consistent across several layers.  Layer files work with vector layers as well, so keep them in mind when next you want some consistent symbology across several layers.<\/p>\n

C<\/p>\n

 <\/p>\n","protected":false},"excerpt":{"rendered":"

This post covers how you can get consistent symbology across several layers using layer files. So the good people in ERST310\/607 have been doing some fun analysis lately (though they may disagree), getting some high-resolution elevation models from LiDAR data (more to follow on that topic).  Using three separate datasets, they’re creating DEMs for three […]<\/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-1144","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/blogs.lincoln.ac.nz\/gis\/wp-json\/wp\/v2\/posts\/1144","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=1144"}],"version-history":[{"count":1,"href":"https:\/\/blogs.lincoln.ac.nz\/gis\/wp-json\/wp\/v2\/posts\/1144\/revisions"}],"predecessor-version":[{"id":4022,"href":"https:\/\/blogs.lincoln.ac.nz\/gis\/wp-json\/wp\/v2\/posts\/1144\/revisions\/4022"}],"wp:attachment":[{"href":"https:\/\/blogs.lincoln.ac.nz\/gis\/wp-json\/wp\/v2\/media?parent=1144"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blogs.lincoln.ac.nz\/gis\/wp-json\/wp\/v2\/categories?post=1144"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blogs.lincoln.ac.nz\/gis\/wp-json\/wp\/v2\/tags?post=1144"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}