But where are these soil science researchers? R code for producing the HTML and KML directory

Julien Moeys

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• Publié par: Onfue
• Nombre de lectures: 23
• Langue: English

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But where are these soil science researchers?
R code for producing the HTML and KML
directory
Julien Moeys
September 30, 2009
Contents
1 About this document 1
2 Files needed 2
3 Time needed 2
4 Set the directory and load R KML functions 2
5 Import and clean the data 2
6 Write the KML le 3
7 Write the HTML bookmark le 3
8 Compact the KML le into a KMZ le 4
1 About this document
This document has been created by Julien MOEYS. See the my website for
more information and contact details (especially the page But where are these
Soil Science researchers?).
This document and the soil laboratory directory DATA are licensed under a
Creative Commons Attribution-Share Alike 3.0 Unported or higher.
The R code (functions that produce HTML and KML le from the CSV ta-
ble of soil science laboratories) is licensed under a GNU General Public License
version 3 or higher.
Please feel free to contact the author (see website) if you have any question
or suggestion, but remember all this is provided with absolutely no garantee of
any kind.
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2 Files needed
For running this sample code, you need:
The HTML and KML functions code in a le named FUNCTION KML.R;
An export of the soil laboratories directory in the form of a CSV data
frame SOIL LABS.CSV;
Eventually, 7zip program installed on your computer and executable from
the command line (7z.exe)
The code has been tested under Microsoft windows XP.
3 Time needed
On my computer, running the whole script over 303 labs took 10 minutes.
The code is optimised (with "lapply" & co), but some parts may need further
improvements.
4 Set the directory and load R KML functions
# Date of script START:
date()
[1] "Wed Sep 30 14:53:37 2009"
# Set the directory:
setwd("C:/_RTOOLS/SWEAVE_WORK/KML_SOIL_LABS")
# Import the functions:
eval( parse( file = "FUNCTION_KML.R" ) )
5 Import and clean the data
# Import the data
mydata <- read.table(
file = "SOIL_LABS.CSV",
header = TRUE,
sep = ",",
dec = ".",
stringsAsFactors = FALSE,
na.strings = "",
quote = " ,
encoding = "UTF-8"
) #
# Clean the data from eventual "missing data"
dim(mydata)
[1] 315 8
2mydata <- clean.dtf(mydata)
dim(mydata)
[1] 315 8
# Display columns names
colnames(mydata)
[1] "name" "wgs_lat" "wgs_long" "description"
[5] "name_url" "institution" "city" "country"
6 Write the KML le
write.point.kml(
data.s = mydata,
fileName = "SOIL_LABS.kml",
fileDir = getwd(),
lat = "wgs_lat",
long = "wgs_long",
folderCol = "country",
placeMCol = "city",
alt = NULL,
name = "name",
description = "description",
additional = "institution",
descUrl = "name_url",
iconUrl =
"http://maps.google.com/mapfiles/kml/shapes/poi.png",
iconScale = 1.0,
GMUrlZoom = 14,
encoding = "UTF-8"
) #
7 Write the HTML bookmark le
In the text below, change "Firstname FAMILYNAME" by your name if you
create yourself the directory le (and state somewhere that this is a derived
data from me (Julien MOEYS), in case you distribute the result of this script).
write.point.html(
data.s = mydata,
fileName = "SOIL_LABS_BOOKMARKS.HTML",
fileDir = getwd(),
lat = "wgs_lat",
long = "wgs_long",
folderCol = "country",
placeMCol = "city",
alt = NULL,
name = "name",
3description = "description",
additional = "institution",
descUrl = "name_url",
iconUrl = "http://maps.google.com/mapfiles/kml/shapes/poi.png",
iconScale = 1.0,
GMUrlZoom = 14,
encoding = "UTF-8",
doc.title = "World Soil Science Labs",
doc.author = "Firstname FAMILYNAME",
doc.C.own = "Firstname FAMILYNAME",
doc.licence = "Creative Commons Attribution-Share Alike 3.0",
doc.licence.url = "http://creativecommons.org/licenses/by-sa/3.0/",
doc.licence.txt = "Some rights reserved"
) #
8 Compact the KML le into a KMZ le
The sample code below require 7zip to be installed and available from the com-
mand line (7z.exe). It works under MS Windows. It is not necessary to compact
the KML