gidden

This gist provides a minimal setup and example of the git collaborate exercise for SWC (e.g., here). Use setup.sh to get a minimal working repository example. A repos represent the master upstream version, B and C repos represent forks. *-remote directories represent Github repos (and forks), while ~*-local` directories correspond to local copies. exercise.sh goes through what students will see for both the PR execise and "experiencing a conflict".

briantjacobs

Storytelling from Space: Tools/Resources

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.

Acquiring Landsat & MODIS

Web Interface

• USGS Earth Explorer - Browser and data access (create a login)
  http://earthexplorer.usgs.gov/

• Landsat archive

meetar

##How to get started contributing to a Humanitarian OpenStreetMap Team task

###Overview

OpenStreetMap (OSM) is an open-source map of the world that anyone can edit. But like any map, it's incomplete.

The Humanitarian OpenStreetMap Team (HOT) helps organize people to improve the OSM map for crisis areas, mostly so aid workers can find their way around and make decisions about undermapped places. The data in these crisis areas is often very poor, or completely non-existent. Therefore any contribution you make at all will be a vast improvement, and could materially help people who are on the ground right now, looking at this data as you edit it, and deciding where to go and who to help.

There are many HOT tasks active at once. As of August 2014, the highest-priority tasks are Gaza and areas affected by the West African Ebola outbreak.

wrobstory

Python 2.6.9 |Continuum Analytics, Inc.| (unknown, Jan 10 2014, 13:33:57) 
[GCC 4.2.1 (Apple Inc. build 5577)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> import timeit
>>> from math import sqrt
>>> 
>>> n = 100
>>> sqrt_n = int(sqrt(n))
>>> 
>>> def with_set():

onyxfish

#!/usr/bin/env python

from collections import OrderedDict
import json

write_data = OrderedDict([
    ('a', '1'),
    ('b', '2'),
    ('c', '3')
])

mtayseer

import pkg_resources, pprint

requires = {p.key: [r.key for r in p.requires()] for p in pkg_resources.working_set}

def graph(pkg):
    if not requires[pkg]:
        return {pkg: {}}

    return {pkg: {k: v for p in requires[pkg] for k, v in graph(p).items() }}

rgbkrk

# Nova Client Settings
OS_AUTH_URL=https://identity.api.rackspacecloud.com/v2.0/
OS_VERSION=2.0
OS_AUTH_SYSTEM=rackspace
OS_REGION_NAME=IAD
OS_SERVICE_NAME=cloudserversOpenStack
OS_TENANT_NAME=<TENANT_ID>
OS_NO_CACHE=1
OS_USERNAME=<USERNAME>
OS_PASSWORD=<API_KEY>

peterkuma

#!/bin/python

import os
from flask import Flask, Response, request, abort, render_template_string, send_from_directory
import Image
import StringIO

app = Flask(__name__)

WIDTH = 1000

celoyd

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

barnabemonnot

var vv = window,
    w = vv.innerWidth,
    h = vv.innerHeight;

var svg = d3.select("#animviz")
		    .append("svg")
		    .attr("width", w)
		    .attr("height", h);

svg.append("g").attr("class", "links");