This tutorial builds upon the on the work done in the context of the ESA Cat-1 project “Production of global MERIS MCI composite images for detection of plankton blooms and other events” submitted by Dr. Jim Gower. More context information is available from the tutorial wiki page.
Hereafter, we will guide you to implement a "MERIS Algal bloom detection using BEAM" application on Terradue's Cloud Platform, a set of Cloud services to develop, test and exploit scalable, distributed earth data processors.
To run this application, you will need a Developer Cloud Sandbox that can be requested from Terradue's Portal, provided user registration approval.
Log on the developer sandbox and run these commands in a shell:
- Install Java 7
sudo yum install -y java-1.7.0-openjdk
- Select Java 7
sudo /usr/sbin/alternatives --config java
This will show on the terminal window:
There are 3 programs which provide 'java'.
Selection Command
-----------------------------------------------
+ 1 /usr/java/jdk1.6.0_35/jre/bin/java
2 /usr/lib/jvm/jre-1.5.0-gcj/bin/java
* 3 /usr/lib/jvm/jre-1.7.0-openjdk.x86_64/bin/java
Enter to keep the current selection[+], or type selection number:
Select java 1.7 out of the menu options by typing the correct number (here it's 3).
- Install R required packages
Run these commands in the Developer Cloud Sandbox shell:
sudo yum install -y miniconda-3.8.3
export PATH=/opt/anaconda/bin/:$PATH
sudo conda install -y -c r r-essentials
sudo conda install -y -c r -c terradue r-rciop
sudo conda install -y -c r -c terradue r-ff
- Install this application
cd
git clone [email protected]:Terradue/dcs-beam-algalbloom.git
cd dcs-beam-algalbloom
mvn install
Run this command in a shell:
ciop-run
Or invoke the Web Processing Service via the Sandbox dashboard providing a start/stop date in the format YYYY/MM/DD (e.g. 2012-04-01 and 2012-04-03).
To learn more and find information go to
- Brito Fabrice
- Mathot Emmannuel
Copyright 2014 Terradue Srl
Licensed under the Apache License, Version 2.0: http://www.apache.org/licenses/LICENSE-2.0