Author: Sean Gillies Version: 1.0
This document describes a GeoJSON-like protocol for geo-spatial (GIS) vector data.
#!/usr/bin/env python | |
""" | |
A script to grab timeseries from MODIS data using GDAL and python | |
Author: J Gomez-Dans/NCEO & UCL | |
""" | |
__author__: J Gómez-Dans | |
import numpy as np | |
import matplotlib.pyplot as plt | |
from osgeo import gdal |
#!/bin/bash | |
# This command works on my laptop, maybe it's a bug? | |
# USAGE: ./grab_modis.sh productname tile year | |
# Where productname is the complete product name (including collection) | |
# ie MOD17A2.005, or MCD45A1.005 | |
# gist in https://gist.github.com/3145223 | |
usage(){ | |
echo "MODIS data grabber" | |
echo "By J Gómez-Dans, National Centre for Earth Observation & UCL" | |
echo "Usage: $0 <product_name> <tile> <year>" |
L.TileLayer.TileJSON = L.TileLayer.Canvas.extend({ | |
options: { | |
debug: false | |
}, | |
tileSize: 256, | |
initialize: function (options) { | |
L.Util.setOptions(this, options); |
""" | |
Likely not useful to anyone else, but just putting it out there. | |
This script will take a directory of GeoTIFFs and merge them together without issues. | |
This script simply decompresses the files, runs nearblack to remove pseudo-black borders caused by compression, and then uses gdalwarp to stitch the files together. | |
The script is designed to use the minimal amount of disk space possible -- it cleans up each file after decompression and continually merges with a master image. | |
""" | |
import os |