This page can always be found at: http://bit.ly/cdb-harvard
- Tour of dashboard
- Common data
- Uploading data
- Tour of table and map view
- Publishing maps
- Public profile
# examples from: http://kateto.net/network-visualization | |
library('igraph') | |
library('network') | |
library('sna') | |
library('ndtv') | |
library('visNetwork') | |
# load data | |
setwd('/Users/djq/Desktop/net-viz/data') |
library(idbr) # devtools::install_github('walkerke/idbr') | |
library(ggplot2) | |
library(animation) | |
library(dplyr) | |
library(ggthemes) | |
idb_api_key("") |
# ---- | |
# Background | |
# ---- | |
# | |
# Vectors: | |
# vectors consist of points, lines, polygons | |
# Within GeoDjango, data-types which are multipolygon and geometry also exist | |
# | |
# Projections: | |
# Projection systems facilitate translating data between a 3D and 2D space. |
This page can always be found at: http://bit.ly/cdb-harvard
# coding=utf-8 | |
# A simple demonstration of how to load a QGIS project and then | |
# show it in a widget. | |
# This code is public domain, use if for any purpose you see fit. | |
# Tim Sutton 2015 | |
import os | |
from qgis.core import QgsProject | |
from qgis.gui import QgsMapCanvas, QgsLayerTreeMapCanvasBridge |
# The blog post that started it all: https://neocities.org/blog/the-fcc-is-now-rate-limited | |
# | |
# Current known FCC address ranges: | |
# https://news.ycombinator.com/item?id=7716915 | |
# | |
# Confirm/locate FCC IP ranges with this: http://whois.arin.net/rest/net/NET-165-135-0-0-1/pft | |
# | |
# In your nginx.conf: | |
location / { |
download tarball (http://s3tools.org/download) | |
$ sudo python setup.py install | |
$ s3cmd --configure | |
Enter new values or accept defaults in brackets with Enter. | |
Refer to user manual for detailed description of all options. | |
Access key and Secret key are your identifiers for Amazon S3 |
# Hosts/domain names that are valid for this site; required if DEBUG is False | |
# See https://docs.djangoproject.com/en/1.5/ref/settings/#allowed-hosts | |
ALLOWED_HOSTS = [ | |
'yourdomain.tld', | |
'.compute-1.amazonaws.com', # allows viewing of instances directly | |
] | |
import requests | |
EC2_PRIVATE_IP = None | |
try: |
import re | |
from django.conf import settings | |
from django.core import cache as django_cache | |
from mock import patch | |
from rest_framework.permissions import SAFE_METHODS | |
from rest_framework.response import Response | |
class CachedResourceMixin (object): | |
@property |
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