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#!/usr/bin/env python3

'''
pip install tqdm numpy pillow mercantile 'rasterio==1.0b1' 'rio-tiler==1.0a7'
'''

import os

import argparse

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#!/bin/bash
#
# ogrcat
# produces line-delimited geojson features
# Like `fio cat` but uses ogr2ogr under the hood


ECHO_FEATURES=""

ogr2ogr -f GeoJSON /vsistdout/ "$@" | while read line

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#! /bin/bash -ex

# Convert Landsat 8 GeoTIFF images into RGB pan-sharpened JPEGs.
#
# Requirements:
#              * gdal http://www.mapbox.com/tilemill/docs/guides/gdal/
#              * Dan Stahlke's https://github.com/gina-alaska/dans-gdal-scripts
#              * convert (image-magick)
#
# Reference info:

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NYC had an import of over 1 million building footprints and 900,000 addresses in 2014 from the New York City Department of Information Technology and Telecommunications (DoITT). The DoITT GIS releases an updated shapefile of the footprints every quarter, and the latest version can be accessed here: Building footprints | Address points

Open datasets like these are a great opportunity to explore how OSM can be used as a bridge between authoritative information and that crowdsourced by citizens. Two years after the import, it is interesting to see how the OSM data compares with the latest official footprints. The interesting questions to ask is:

• What has improved in the DoITT footprints that can be updated in OSM?
• What has

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Mabuhay!

Welcome to the Open Source for Geography developers training.

This week we will learn about the basic building blocks for web based gis systems and desktop analysis tools. We will cover topics such as Git/Github, Postgis, GeoServer, Tilemill, GeoNode, QGIS and Inasafe. During the training, there will be tutorials on each of the tools and will work together on a prototype for a web based flood impact analysis tool.

This gist will be both our agenda and minutes document. It contains links to the training materials as well as the description of each activity.

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#!/usr/bin/perl

# Create index.html with a list of all files.
# Written by Ilya Zverev, licensed WTFPL.

use strict;
use POSIX qw(strftime);
use HTML::Template;
use File::Basename;
use Getopt::Long;

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# Example of downloading all data from a GeoServer WFS server
# and loading it into a PostGIS database. Use with caution
# as you could put a lot of load on someone's server if they
# host a lot of data which might make them sad.
# In response to: http://underdark.wordpress.com/2012/09/26/wfs-to-postgis-in-3-steps/

BASEURL="http://data.wien.gv.at/daten/geoserver/ows?service=WFS&version=1.1.0"

for LAYERNAME in `wget -qO- $BASEURL"&request=GetCapabilities" | xpath -q -e "//FeatureType/Name/text()"` ; do 
    PARTS=(${LAYERNAME//:/ })

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import sqlite3, os

conn = sqlite3.connect('Mills1860.mbtiles')

results=conn.execute('select * from tiles').fetchall()

for result in results:
    zoom, column, row, png= result
    try:
        os.makedirs('%s/%s/' % (zoom, row))