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https://github.com/jrawbits/AccessR

NMTK Accessibility Tool
https://github.com/jrawbits/AccessR

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NMTK Accessibility Tool

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README 

        
# AccessR



The AccessR tool set provides a simple set of NMTK tools for preparing an

accessibility map and conducting simple isochrone accessibility analyses

from a set of points.



This tool can be installed under the name "AccessR" in the NMTK's

NMTK_apps subfolder, with a corresponding entry in local_settings.py to

enable the application.  There are system prerequisites detailed below

in in the Installation section.



The tool works in three steps.



The first step takes an input polygon geographic file and rasterizes

it to establish a study area with a base level of accessibility (the

units are arbitrary).  The tool can use either feature values or a

constant value to provide the base level of impedance in each cell.

Any value used for the baseline should be greater than zero; a zero

value is treated as inaccessible.  This step generates a basic raster

file called an "accessibility map".



The second step accepts a spatial layer (areas, lines or points)

and overlays those features onto an existing accessibility map. The

accessibility map can come from the first step, or from a previous

iteration of this second step, which can be conducted as many times

as necessary to include different types of facilities or barriers.

The accessibility value of each feature (or a constant value applied to

all features) is used to update the provided accessibility map, and new

accessibility map is generated; that number should be positive, non-zero

value.  Three "styles" of update are provided: "Barriers" are areas that

will be considered completely untraversable or off-limits.  Areas occupied

by barriers will be considered outside the analysis area.  "Obstacles"

simply reduce the base accessibility by the accessibility value but

still allow passage.  "Facilities" increase the base accessibility.



The third step accepts an accessibility map from one of the previous

steps, plus a file of points for which isochrones are computed using

the accessibility map.



*Installation*



The AccessR accessibility analysis functions are designed as a tool for the

Nonmotorized Toolkit (https://github.com/chander/nmtk).  To use this code,

you'll need a working installation of the Nonmotorized Toolkit first.



To add these tools to the Nonmotorized Toolkit, the entire set of repository

code should be placed in a subfolder of the NMTK_apps folder of the NMTK

called "AccessR", and the "AccessR" tool should be added to the list of

available tools in local_settings.py (see the NMTK documentation for details).

The tool will be enabled when the deploy.sh script is run (see below).



As the name suggests, the tool uses the R Statistical Environment to

perform its computations.  So you'll need to install a recent version

of R from one of the CRAN mirrors (see http://cran.r-project.org).

For Ubuntu, you can look here: https://cran.r-project.org/bin/linux/ubuntu/



On Ubuntu 14.04 ("trusty") you can do the following to connect a

R repository (replacing "<my.favorite.cran.mirror>" with one of the

mirrors you can find at https://cran.r-project.org/mirrors.html:



    sudo echo "deb https:///bin/linux/ubuntu trusty/" > /etc/apt/sources.list.d/cran.list

    

The repository is secured by a specific signature key.  You need to

install the key by doing this:



    sudo apt-key adv --keyserver keyserver.ubuntu.com --recv-keys E084DAB9



Then you can run these commands to install R itself, plus the development

environment for compiliing packages from source:



    sudo apt-get update # to read the repository

    sudo apt-get install r-base r-base-dev



You will need several R packages (specifically: sp, raster, rgdal,

gdistance).  You will also need Rserve to allow the NMTK environment

to run R commands.  Installation of Rserve is easy, see the Rserve

documentation: https://www.rforge.net/Rserve/doc.html



It is most convenient to install these packages from within R

using the  function 'install.packages':



    sudo R  # run R as an administrator

    install.packages(c("sp","raster","rgdal","gdistance","Rserve","RSclient"))

    quit()



For accessing Rserve from the Python environment, the pyRserve package

is used.  Activate the NMTK python environment from the NMTK root folder,

then install pyRserve using 'pip install -r requirements.txt' Note that

pyRserve requires numpy, which the base NMTK installs.  The complete

sequence for installing pyRserve:



    source ../../venv/bin/activate

    pip install -r requirements.txt



The Rserve configuration file (/etc/Rserv.conf) needs to be adjusted with

consistent permissions for the web server and to set up "out-of-band" (oob)

messages to pass status updates from within R itself.  The Rserv.conf file

should contain these instructions:



    # Configuration for RServe

    control enable



    # Change uid/gid to www-data

    su server

    gid 33

    uid 33



    # Enable Out-of-Band Messages

    oob enable

    eval require(Rserve)



There are two shell script files available to start and stop Rserve, and

there will also soon be an init.d script that is automatically installed to

stop and restart Rserve on system startup and shutdown.



    bash startRserve.sh

    bash stopRserve.sh



Finally, the included "deploy.sh" script will set everything going once

you have all the pieces installed and have added` "AccessR" to the NMTK's

list of tools in local_settings.py.  It calls the root NMTK deployment script

to reload the NMTK environment and it also starts Rserve.  Like the root NMTK

deployment script, it supports an option "-c" which will clear log files.



    sudo bash deploy.sh  # -c optional to clear log files