Koen Hufkens khufkens

## reference_blue_marble.sh
gdal_translate -a_ullr -180 90 180 -90 -a_srs EPSG:4326 world.topo.bathy.200408.3x5400x2700.jpg tmp.tif

## opt_span_example.R
# Interpolation using a loess smoother
# and optimal span determination

library(MODISTools)
library(phenocamr)
library(tidyverse)

VI <- mt_subset(
  product = "MOD13Q1",
  lon = -72.1755,

## download_plumber2.R
library(rvest)

# base html url
url <- "http://dapds00.nci.org.au/thredds/fileServer/ks32/CLEX_Data/PLUMBER2/v1-0/Flux/"

# catalogue
html_page = read_html("https://dap.nci.org.au/thredds/remoteCatalogService?catalog=http://dapds00.nci.org.au/thredds/catalog/ks32/CLEX_Data/PLUMBER2/v1-0/Flux/catalog.xml")

# grab files from the catalogue
files = html_page %>%

## animation.sh
# convert pngs to mp4
ffmpeg -r 2 -i tmp/%03d.png -y  out.mp4

# convert mp4 to twitter compatible format
ffmpeg -i out.mp4  -vf scale=1280:720 -b:v 5000K -minrate 5000K -maxrate 5000K -b:a 128K -r 30 -f mp4 -vcodec libx264 -profile:v high -pix_fmt yuv420p -strict -2  -ac 2 -acodec aac twitter.mp4

## waffle_plot.R
# data wrangling
library(tidyverse)

# waffle plot
library(waffle)

# combining graphs
library(patchwork)

# text magic

## downsample_extract_hwsd.R
# Downsample HWSD data to the scale of 0.5 degree
# WFDEI / CRU data

library(raster)
library(hwsdr)
library(tidyverse)

# get mu_global at 0.5 degrees from the
# ORNL DAAC (which is easier than reading in
# that monstrous BIL file)

## equi2polar.sh
#!/bin/bash
# convert equirectangular 2 fisheye

files=`ls *.jpg`

for i in $files;
do
noext=`echo $i | cut -d'.' -f1`

echo $noext

## format_phenor_data.R
# required libraries
library(phenor)

# where to store the data
out_dir <- "data-raw/"

# sites to process, stored in a csv file
# with columns site, veg_type, roi (check for extra spaces
# which can mess with name formatting)
sites <- read.table("data/sites.csv", sep = ",", header = TRUE)

## crop_and_animate.sh
#!/bin/bash

# crop section of images
mogrify -crop 2770x2304+3560+296 *.jpg

# compile into animated gif
convert -delay 100 -loop 0 -depth 8 -resize '640x' -quality 75% *.jpg anim.gif

## MODIS_arctic_sites_download.R
# download NDVI time series
library(MODISTools)

df <- data.frame(
  site_name =
    c("US-Bes",
      "US-Atq",
      "US-Ivo",
      "US-ICt",
      "DK-ZaH",
	# Interpolation using a loess smoother
	# and optimal span determination

	library(MODISTools)
	library(phenocamr)
	library(tidyverse)

	VI <- mt_subset(
	product = "MOD13Q1",
	lon = -72.1755,
	library(rvest)

	# base html url
	url <- "http://dapds00.nci.org.au/thredds/fileServer/ks32/CLEX_Data/PLUMBER2/v1-0/Flux/"

	# catalogue
	html_page = read_html("https://dap.nci.org.au/thredds/remoteCatalogService?catalog=http://dapds00.nci.org.au/thredds/catalog/ks32/CLEX_Data/PLUMBER2/v1-0/Flux/catalog.xml")

	# grab files from the catalogue
	files = html_page %>%
	# convert pngs to mp4
	ffmpeg -r 2 -i tmp/%03d.png -y out.mp4

	# convert mp4 to twitter compatible format
	ffmpeg -i out.mp4 -vf scale=1280:720 -b:v 5000K -minrate 5000K -maxrate 5000K -b:a 128K -r 30 -f mp4 -vcodec libx264 -profile:v high -pix_fmt yuv420p -strict -2 -ac 2 -acodec aac twitter.mp4
	# data wrangling
	library(tidyverse)

	# waffle plot
	library(waffle)

	# combining graphs
	library(patchwork)

	# text magic
	# Downsample HWSD data to the scale of 0.5 degree
	# WFDEI / CRU data

	library(raster)
	library(hwsdr)
	library(tidyverse)

	# get mu_global at 0.5 degrees from the
	# ORNL DAAC (which is easier than reading in
	# that monstrous BIL file)
	#!/bin/bash
	# convert equirectangular 2 fisheye

	files=`ls *.jpg`

	for i in $files;
	do
	noext=`echo $i \| cut -d'.' -f1`

	echo $noext
	# required libraries
	library(phenor)

	# where to store the data
	out_dir <- "data-raw/"

	# sites to process, stored in a csv file
	# with columns site, veg_type, roi (check for extra spaces
	# which can mess with name formatting)
	sites <- read.table("data/sites.csv", sep = ",", header = TRUE)
	#!/bin/bash

	# crop section of images
	mogrify -crop 2770x2304+3560+296 *.jpg

	# compile into animated gif
	convert -delay 100 -loop 0 -depth 8 -resize '640x' -quality 75% *.jpg anim.gif
	# download NDVI time series
	library(MODISTools)

	df <- data.frame(
	site_name =
	c("US-Bes",
	"US-Atq",
	"US-Ivo",
	"US-ICt",
	"DK-ZaH",