One Paragraph of project description goes here
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.
# United States of America Python Dictionary to translate States, | |
# Districts & Territories to Two-Letter codes and vice versa. | |
# | |
# Canonical URL: https://gist.github.com/rogerallen/1583593 | |
# | |
# Dedicated to the public domain. To the extent possible under law, | |
# Roger Allen has waived all copyright and related or neighboring | |
# rights to this code. Data originally from Wikipedia at the url: | |
# https://en.wikipedia.org/wiki/ISO_3166-2:US | |
# |
var fs = require('fs'); | |
var request = require('request-promise'); | |
var moment = require('moment') | |
// Globals | |
global.timestamp = moment().unix() | |
global.allPlaybacks = []; | |
global.geojson = {}; | |
global.geojson['type'] = 'FeatureCollection'; | |
global.geojson['features'] = []; |
#! /usr/bin/env ruby | |
# NOTE: Requires Ruby 2.1 or greater. | |
# This script can be used to parse and dump the information from | |
# the 'html/contact_info.htm' file in a Facebook user data ZIP download. | |
# | |
# It prints all cell phone call + SMS message + MMS records, plus a summary of each. | |
# | |
# It also dumps all of the records into CSV files inside a 'CSV' folder, that is created |
To colaborate on a gist:
git remote add-url cindy https://gist.github.com/cindy/df03bdacaef75a80f310
git fetch cindy/master
git merge cindy/master
git push origin/master
# Prepare world data | |
# First up, we need to load the built-up area data that we’re going to be plotting. We download this from the European Commission’s Global Human Settlement Data portal [https://ghsl.jrc.ec.europa.eu/datasets.php] — specifically using the links from this page [http://cidportal.jrc.ec.europa.eu/ftp/jrc-opendata/GHSL/GHS_BUILT_LDSMT_GLOBE_R2015B/]. We want the 250m-resolution rasters for 1975 and 2015 (GHS_BUILT_LDS1975_GLOBE_R2016A_54009_250 and GHS_BUILT_LDS2014_GLOBE_R2016A_54009_250). | |
# Once you’ve downloaded these (they’re BIG, so might take a little while...), we can save ourselves a lot of hassle later on by re-projecting them into the same co-ordinate space as the other data we’re going to be using. Specifically we want to change their units from metres to lat/lon. We do this by: | |
# 1) Unzipping the archive, and then | |
# 2) Running the following script on the command-line: | |
# gdalwarp -t_srs EPSG:4326 -tr 0.01 0.01 path/to/your/built-up-area.tif path/to/your/built-up-area_reprojected. |
Short version: I strongly do not recommend using any of these providers. You are, of course, free to use whatever you like. My TL;DR advice: Roll your own and use Algo or Streisand. For messaging & voice, use Signal. For increased anonymity, use Tor for desktop (though recognize that doing so may actually put you at greater risk), and Onion Browser for mobile.
This mini-rant came on the heels of an interesting twitter discussion: https://twitter.com/kennwhite/status/591074055018582016
This list of resources is all about acquring and processing aerial imagery. It's generally broken up in three ways: how to go about this in Photoshop/GIMP, using command-line tools, or in GIS software, depending what's most comfortable to you. Often these tools can be used in conjunction with each other.