jgomezdans

#!/usr/bin/env python
"""
SYNOPSIS

    dn_2_rad.py [-h,--help] [-v,--verbose] [-i,--input] [-o,--output]
    

DESCRIPTION

  This program is used to extract the gain parameters and to convert 

celoyd

#!/usr/bin/env python

# ndvi.py red.tif nir.tif output-ndvi.tif
# Calculate NDVI (see Wikipedia). Assumes atmospheric correction.
# (Although I use it without all the time for quick experiments.)

import numpy as np
from sys import argv
from osgeo import gdal, gdalconst

oeon

##This workflow is only for the pansharpened images

####red-green-blue
gdalbuildvrt -separate -q -srcnodata "0 0 0" -vrtnodata "0 0 0" rgb.vrt LC80430352013339LGN00_B4.tif LC80430352013339LGN00_B3.tif LC80430352013339LGN00_B2.tif

####NIR, SWIR, and visible red
gdalbuildvrt -separate -q -srcnodata "0 0 0" -vrtnodata "0 0 0" false.vrt LC80430352013339LGN00_B5.tif LC80430352013339LGN00_B6.tif LC80430352013339LGN00_B4.tif

####color infrared
gdalbuildvrt -separate -q -srcnodata "0 0 0" -vrtnodata "0 0 0" cir.vrt LC80430352013339LGN00_B5.tif LC80430352013339LGN00_B3.tif LC80430352013339LGN00_B4.tif

dwtkns

# This is a shell function to quickly grab the data for a given Landsat 8 tile ID from Google's servers
# For example:
# l8get LC81690352014169LGN00

# The echo at the end is to remind myself of the syntax for extracting bands 8, 4, 3, and 2. (Pansharp, Red, Green, Blue)

# On OSX this would go into your ~/.bash_profile file.
# Requires gsutil from https://developers.google.com/storage/docs/gsutil_install
# Most useful in conjunction with USGS' Earth Explorer: http://earthexplorer.usgs.gov/

bsweger

Useful Pandas Snippets

A personal diary of DataFrame munging over the years.

Data Types and Conversion

Convert Series datatype to numeric (will error if column has non-numeric values)
(h/t @makmanalp)

dwtkns

# These are shell functions to quickly create pansharpened RGB images ready for color correction 
# from a set of raw Landsat 8 TIF files in a given directory.

# For example:
#  l8_pansharp LC81690352014169LGN00
# Creates:
#  LC81690352014169LGN00_rgb_pansharp.tif

# l8_rush_pansharp downloads a L8 tile from Google Storage (if they have it), extracts the relevant bands, then creates the pansharpened output.

briantjacobs

# This is a shell function to quickly grab the data for a given Landsat 8 tile ID from Google's servers
# For example:
# l8get LC81690352014169LGN00

# The echo at the end is to remind myself of the syntax for extracting bands 8, 4, 3, and 2. (Pansharp, Red, Green, Blue)

# On OSX this would go into your ~/.bash_profile file.
# Requires gsutil from https://developers.google.com/storage/docs/gsutil_install
# Most useful in conjunction with USGS' Earth Explorer: http://earthexplorer.usgs.gov/

celoyd

#!/usr/bin/env python
# Very simple rasterio NDVI (or general normalized difference ratio) demo.
# python ndvi.py $landsat_scene/*B{4,5}.TIF ndvi.tif

import rasterio as rio
from sys import argv
import numpy as np

math_type = np.float32 # type for internal calculations

albert-decatur

#!/bin/bash

# see Development Seed landsat-api scene extent on geojson.io
# example use: $0 LC81660362014196LGN00

scene=$1
# get scene metadata from devseed landsat-api
curl -s "https://api.developmentseed.org/landsat?search=${scene}"  |\
# get corner coords
jq '.results[]|[.lowerLeftCornerLongitude,.lowerLeftCornerLatitude,"",.lowerRightCornerLongitude,.lowerRightCornerLatitude,"",.upperRightCornerLongitude,.upperRightCornerLatitude,"",.upperLeftCornerLongitude,.upperLeftCornerLatitude,"",.lowerLeftCornerLongitude,.lowerLeftCornerLatitude]|@csv' |\

kgjenkins