| #cloud-boothook | |
| #!/bin/bash | |
| set -x | |
| # This EC2 user-data file will run a Mapserver docker container. | |
| # Still working on getting it to reboot properly. See this link for more info on user-data scripts | |
| # http://docs.aws.amazon.com/AWSEC2/latest/UserGuide/user-data.html#user-data-shell-scripts | |
| # Because this setup uses data stored in an S3 bucket located in the standard region, it needs to be run in us-east-1 (Virginia Region). | |
| # It mounts S3 data by using danilop/yas3fs. USDA CONUS NAIP data, Mapfile and shapefile indexes are made available to Mapserver in this way. | |
| # Just running this instance will give you access to all of the NAIP data via the EC2 instance's filesystem. | |
| # One caveat is that the combination of mapfile and UTM projected geotifs only supports WMS requests near native 1m/pixel resolution or level 17, |
This is functional but is merely a workaround until we get vsis3 - you can try out preliminary vsis3 support with GDAL 2.1 and rasterio 0.32a1
Goal: Based on the GeoTiff and TIFF specs, manually parse out tags to allow for the most IO-efficient reading of georeferencing information.
It works almost the same as rio info --bounds but gives a json array, and it's fast
$ time rio info --bounds R4C1.tif
153.984375 24.2578125 154.072265625 24.345703125
Open the browser developer console - ctrl + shift + k on Firefox or ctrl + shift + i on Chrome.
Type the following into the browser console: window.api.map.addLayer(L.tileLayer('http://tileify-ags.herokuapp.com/tiles/{z}/{x}/{y}?url=https%3A%2F%2Fgis.apfo.usda.gov%2Farcgis%2Frest%2Fservices%2FNAIP%2FGeorgia_2015_1m%2FImageServer&renderingRule=%7B%20%20%20%22rasterFunction%22%20%3A%20%22NDVI%22%2C%20%20%20%22rasterFunctionArguments%22%20%3A%20%7B%20%20%20%20%20%22VisibleBandID%22%20%3A%202%2C%20%20%20%20%20%22InfraredBandID%22%20%3A%203%20%20%20%7D%2C%20%20%20%22variableName%22%20%3A%20%22Raster%22%20%7D'));
Try replacing the ArcGIS Image Service URL with a different URL from here. Be sure to encode the URL correctly. For help encoding go here
[More info on ArcGIS Image Service Raster
