Juan Carlos Méndez dersteppenwolf

Making a big image zoomable

When you have a giant image and you want to make it easy to pan and zoom without downloading the whole 50MB image into someone's browser, a nice workaround is to cut that image into tiles at different zoom levels and view it as it were a map. An example where I've used this technique is The "Snowpiercer" Scenario.

One way to cut your big image into the requisite tiles is with gdal2tiles.py.

Alternatively, this Node script will do the cutting after you install node-canvas and mkdirp:

const fs = require("fs"),

`apk`

apk-tools 2.8.2, compiled for x86_64.

usage: apk COMMAND [-h|--help] [-p|--root DIR] [-X|--repository REPO] [-q|--quiet] [-v|--verbose] [-i|--interactive] [-V|--version] [-f|--force]
           [--force-binary-stdout] [--force-broken-world] [--force-non-repository] [--force-old-apk] [--force-overwrite] [--force-refresh] [-U|--update-cache]
           [--progress] [--progress-fd FD] [--no-progress] [--purge] [--allow-untrusted] [--wait TIME] [--keys-dir KEYSDIR] [--repositories-file REPOFILE]
           [--no-network] [--no-cache] [--cache-dir CACHEDIR] [--arch ARCH] [--print-arch] [ARGS]...

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Write your commit message in the imperative: "Fix bug" and not "Fixed
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Docker - How to cleanup (unused) resources

Once in a while, you may need to cleanup resources (containers, volumes, images, networks) ...

delete volumes

// see: https://github.com/chadoe/docker-cleanup-volumes

$ docker volume rm $(docker volume ls -qf dangling=true)

$ docker volume ls -qf dangling=true | xargs -r docker volume rm

CartoDB's MVT service + Mapbox GL

Check index.html for some examples. These use a beta feature of CartoDB's Maps API: fixed URLs. So there is no need to use cartodb.js and tiles can be consumed using a named map name.

cartodb.js example

Check cartodb.js.html to see the integration with cartodb.js and in particular with cartodb.core.js.

Mapbox GL resources

API reference

	import os,sys,arcpy;
	import xml.dom.minidom as DOM;

	###############################################################################
	# Alter the following constants as required
	###############################################################################

	project_name = "HydrologicUnits";
	ags_service = "HydrologicUnits";
	ags_folder = "Support";

	var polygon = ee.Geometry.Polygon([[
	[-119.33364769821117, 46.05123532178373],
	[-119.3233620672313, 45.869732769408905],
	[-119.04111088542663, 45.873079023065166],
	[-119.0396574679861, 46.045448840018565]
	]]);
	var landsat8 = ee.ImageCollection("LANDSAT/LC8_L1T_TOA_FMASK");

	//
	// Masking Clouds with Fmask

	<!DOCTYPE html>
	<html lang="en">
	<head>
	<meta charset="UTF-8">
	<title>Deep-Insights.js \| Highest Mountains</title>
	<link rel="shortcut icon" href="http://cartodb.com/assets/favicon.ico" />
	<meta name=viewport content="width=device-width initial-scale=1">
	<link rel="stylesheet" href="http://libs.cartocdn.com/di.js/v0/themes/css/deep-insights.css" />
	<script src=" http://libs.cartocdn.com/di.js/v0/deep-insights.uncompressed.js"></script>
	<style type="text/css">

	{
	"AWSEBDockerrunVersion": "1",
	"Image": {
	"Name": "<AWS_ACCOUNT_ID>.dkr.ecr.us-east-1.amazonaws.com/<NAME>:<TAG>",
	"Update": "true"
	},
	"Ports": [
	{
	"ContainerPort": "443"
	}