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README.md

empirical-paper

A project to process, analyze, and interpret data on the changes in the spatial distribution of deforestation in Borneo as a result of the 2011 moratorium on new deforestation concessions in Indonesia.

Latest write-up

The primary purpose of this project is to analyze and interpret the spatial distribution of deforestation, and how it changed with the enactment of Indonesia's 2011 moratorium on new deforestation concessions. The latest version of the paper (errors and all) can be found here.

Computing outline

The data processing is, unfortunately, split into three broad parts due to the relative strengths of Clojure, R, and Stata.

  1. The raw time series data is screened and processed on a Hadoop cluster using the process-borneo function in the empirics.core namespace. The details for processing can be found in the following Notes section within the readme. The output is stored on S3 as a tab-delimited text file, where each entry is a separate deforestation alert with the appropriate metadata.

  2. The hits are then clustered using the hierarchical clustering algorithm in Stata. This is an incredibly inefficient way to find the clusters; but the Stata implementation is stable and can be run on a remote server. It takes many days to run the clustering algorithm for Borneo for all periods. The output is saved as a series of separate files, one for each interval.

  3. The graphs and and analysis are done in R, making use of its graphing libraries and LaTeX export options. These graphs are imported into the org-mode write-up, which can be compiled to TeX or HTML, and then into a PDF.

Notes

This project makes use of the lein-emr project. To start the cluster for this project, you'll first need to install Leinigen and then type the following at the command line:

lein emr -n "emp" -t "large" -s 10 -b 0.2 -m 4 -r 2 -bs bsaconfig.xml 

where bsaconfig.xml is a configuration script, as described in the lein-emr readme. Once the cluster is properly bootstrapped and running, you will need to run the following commands in sequence:

curl https://raw.github.com/technomancy/leiningen/preview/bin/lein > ~/bin/lein
chmod 755 ~/bin/lein

git clone git@github.com:reddmetrics/forma-clj.git
cd forma-clj
lein do compile :all, install

cd
git clone git@github.com:danhammer/empirical-paper.git
cd empirical-paper/

lein do compile :all, uberjar

repl

Or this:

git clone git://github.com/reddmetrics/forma-clj.git;
cd forma-clj;
git checkout feature/rollback-gadm;
cd ../bin;
wget https://raw.github.com/technomancy/leiningen/preview/bin/lein;
chmod u+x lein;
./lein;
cd ..;
git clone git://github.com/nathanmarz/cascalog.git;
cd cascalog;
lein sub install;
cd ..;
cd forma-clj;
uj;
lein install;
cd ..;
git clone git://github.com/danhammer/empirical-paper.git;
cd empirical-paper;
uj;

At this point, you will be in a REPL, and can launch a command from within any available namespace. Specifically, if you want to restrict the data set to pixels within Borneo, you can run the screen-borneo function from within the empirics.core namespace.

(use 'empirics.core)
(in-ns 'empirics.core)

(process-borneo)

Alternatively, you can run the processing directly from the instance command line on the master node:

hadoop jar /home/hadoop/empirical-paper/target/empirics-0.1.0-SNAPSHOT.jar empirics.core.process-borneo

This code will screen out all pixels that are not in Borneo, and save it do a sequence file on S3. The custom repl command will put you into a separate screen, which you can detach from once the Hadoop job has started using the key command C-a d. You can reattach with screen -rr.

Once the job is running, you can check on it in the browser by entering the DNS followed by :9100. For example:

ec2-54-242-148-62.compute-1.amazonaws.com:9100

License

Copyright © 2012

Distributed under the Eclipse Public License, the same as Clojure.