Here’s how to make animations like this one. It requires intermediate Unix command-line knowledge, to install some tools and to debug if they don’t work. You’ll need these utilities:
curl (or you can translate to wget)convert and montage, part of ImageMagickffmpeg, plus whatever codecsparallel, for iteration that’s nicer than shell for loops or xargszsh for leading 0s in numerical ranges to workOpen 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
| if ('serviceWorker' in navigator && !this.hasOwnProperty('ServiceWorkerGlobalScope')) { | |
| var ownUrl = new URL(document.currentScript.src); | |
| // Before the worker inits, keep tileserver URLs temporarily here | |
| var oldTileLayerProto = L.extend({}, L.TileLayer.prototype); | |
| L.TileLayer._urlsToWatch = []; | |
| L.TileLayer.prototype.initialize = function(url, options) { |
| var turf = require('turf'), | |
| flatten = require('geojson-flatten'), | |
| normalize = require('geojson-normalize'), | |
| tilebelt = require('tilebelt'); | |
| module.exports = function(tileLayers, tile, done) { | |
| // concat feature classes and normalize data | |
| var tigerRoads = normalize(tileLayers.tiger.tiger20062014); | |
| var osmData = normalize(tileLayers.osmdata.migeojson); |
Hello, visitors! If you want an updated version of this styleguide in repo form with tons of real-life examples… check out Trellisheets! https://github.com/trello/trellisheets
“I perfectly understand our CSS. I never have any issues with cascading rules. I never have to use !important or inline styles. Even though somebody else wrote this bit of CSS, I know exactly how it works and how to extend it. Fixes are easy! I have a hard time breaking our CSS. I know exactly where to put new CSS. We use all of our CSS and it’s pretty small overall. When I delete a template, I know the exact corresponding CSS file and I can delete it all at once. Nothing gets left behind.”
You often hear updog saying stuff like this. Who’s updog? Not much, who is up with you?
I've been interested in computer vision for a long time, but I haven't had any free time to make any progress until this holiday season. Over Christmas and the New Years I experimented with various methodologies in OpenCV to detect road signs and other objects of interest to OpenStreetMap. After some failed experiments with thresholding and feature detection, the excellent /r/computervision suggested using the dlib C++ module because it has more consistently-good documentation and the pre-built tools are faster.
After a day or two figuring out how to compile the examples, I finally made some progress:
dlib from Github to your local machine:| license: gpl-3.0 |
| require([ | |
| 'matchers/Topics', | |
| 'dojo/topic' | |
| ], function ( | |
| Topics, | |
| dojoTopic | |
| ) { |
This simple script will take a picture of a whiteboard and use parts of the ImageMagick library with sane defaults to clean it up tremendously.
The script is here:
#!/bin/bash
convert "$1" -morphology Convolve DoG:15,100,0 -negate -normalize -blur 0x1 -channel RBG -level 60%,91%,0.1 "$2"
This is my default career advice for people starting out in geo/GIS, especially remote sensing, adapted from a response to a letter in 2013.
I'm currently about to start a Geography degree at the University of [Redacted] at [Redacted] with a focus in GIS, and I've been finding that I have an interest in working with imagery. Obviously I should take Remote Sensing and other similar classes, but I'm the type of person who likes to self learn as well. So my question is this: What recommendations would you give to a student who is interested in working with imagery? Are there any self study paths that you could recommend?
I learned on my own and on the job, and there are a lot of important topics in GIS that I don’t know anything about, so I can’t give comprehensive advice. I haven’t arrived anywhere; I’m just ten minutes ahead in the convoy we’re both in. Take these recommendations critically.
Find interesting people. You’ll learn a lot more from a great professor (or mentor, or friend, or conference) o