khufkens

#!/bin/bash

# Insert PDF meta-data into exif header
# for pdf files with format author - year - title.pdf.
# This allows e-readers to query meta-data for proper
# display and sorting of authors and titles
# (note: relies on exiftool)

for filename in *.pdf; do  
  noext=`echo "${filename%.*}"`

khufkens

# map El Nino drought in the Amazon and Africa
library(raster)
library(tidyverse)
library(maps)
library(RColorBrewer)

# set colour theme
colours = brewer.pal(11,"RdBu")

# download CHIRP data

khufkens

# load required libraries
if(!require(devtools)){install.package("devtools")}
if(!require(daymetr)){devtools::install_github("khufkens/daymetr")}
library("daymetr")

# no delay calls
no_delay = unlist(lapply(1:100, function(...){
  
  # download data
  error = try(download_daymet(silent = TRUE))

khufkens

// years to process (from start year t0 to end year t1)
var t0 = "2001";
var t1 = "2014";

var LC = ee.ImageCollection('MCD12Q1')
.select('Land_Cover_Type_1')
.filterDate(t0.concat("-01-01"),t1.concat("-12-31"))
.median();

// Create a geometry representing an export region.

khufkens

#' @param species: genus species or genus
#' @param quiet: TRUE / FALSE provides verbose output
#' @keywords Tropicos, species distribution
#' @examples
#'
#' # with defaults, outputting a data frame with species distribution
#' # for Clematis
#' df <- tropicos.species.distribution()
#' # returns NA if no data are present
#' [requires the rvest package for post-processing]

khufkens

library(raster)
library(maps)
library(maptools)
library(sf)
library(scales)

# set coordinate systems
robinson = CRS(" +proj=robin +lon_0=0 +x_0=0 +y_0=0 +ellps=WGS84 +datum=WGS84 +units=m +no_defs")
latlon = CRS("+init=epsg:4326")

khufkens

#-------- arctic map

library(sp)
library(maps)
library(rgeos)
 
# function to slice and dice a map and convert it to an sp() object
maps2sp = function(xlim, ylim, l.out = 100, clip = TRUE) {
  stopifnot(require(maps))
  m = map(xlim = xlim, ylim = ylim, plot = FALSE, fill = TRUE)

khufkens

# calculate adjusted phenology dates
# for greenness onset and maximum

extract_MODIS_phenology_layer <- function(value="increase",tiles_file="mytiles.txt"){
  
  # load required libraries
  require(raster)
  require(MODIS) # to import the SDS layers
  
  # list all hdf files, and extract unique years

khufkens

#!/bin/bash
#
# swath to grid conversion for
# MOD04 reflectance data
#

# get the reprojection information
gdal_translate -of VRT HDF4_EOS:EOS_SWATH:"$1":mod04:Mean_Reflectance_Land land.vrt
gdal_translate -of VRT HDF4_EOS:EOS_SWATH:"$1":mod04:Mean_Reflectance_Ocean ocean.vrt

khufkens

#!/bin/bash

# Bash script to download all NCDC weather records for
# a list of stations (Station number (AWS/WMO/DATSAV3 number))
# (it's easy to adjust the script to take any selection
# of years, just replace the ncftpls query for the years
# with a years file of your own liking or a range in the
# for loop e.g. years 2001 - 2010 = {2001..2010..1} )
#
# raw data is downloaded, extracted from gz files