Repository: incubator-sdap-website Updated Branches: refs/heads/asf-site 2420d9eab -> 6e0454e86
http://git-wip-us.apache.org/repos/asf/incubator-sdap-website/blob/6e0454e8/source/_site/blog.html ---------------------------------------------------------------------- diff --git a/source/_site/blog.html b/source/_site/blog.html index 527f482..cbcd432 100644 --- a/source/_site/blog.html +++ b/source/_site/blog.html @@ -20,7 +20,9 @@ <div class="container"> <div class="logos"> - <!--img src="/images/logo-nasa-jpl-caltech.png" class="pull-left" /--> + <a href="https://incubator.apache.org";> + <img src="/images/egg-logo.png" class="pull-left" /> + </a> </div> <!-- navigation bar --> @@ -46,199 +48,6 @@ -<a href="/2017/10/21/hyspiri.html"><h2>COAL featured at 2017 HyspIRI Science and Applications Workshop</h2></a> -<p>Posted <b>2017-10-21</b> by <b>Lewis John McGibbney</b></p> -<div class="clearfix"> - - <figure class="figure" style="float:right;margin:0 0 1em 1em;width:50%;"> - <img src="/images/IMG_3851.JPG" class="figure-img img-responsive" alt="" \> - <figcaption class="figure-caption"><b>Figure 1:</b> COAL Poster</figcaption> - </figure> - - <p>COAL was presented to attendees of the <a href="https://hyspiri.jpl.nasa.gov/events/2017-hyspiri-science-team-meeting";>2017 HyspIRI Science and Applications Workshop</a> which took place at the California Institute of Technology, Beckman Institute Auditorium, 1200 E California Blvd Pasadena, CA 91125 from Oct 17th - 19th. COAL was presented alongside a huge variety of outstanding work in the area of Global Earth Imaging Spectroscopy and Thermal Infrared Measurements.</p> - - <p>The workshop was focused on everything related to the NASA Decadal Survey Mission Concept named <a href="https://hyspiri.jpl.nasa.gov";>HyspIRI</a>; Hyperspectral Infrared Imager. HyspIRI will study the worldâs ecosystems and provide critical information on natural disasters such as volcanoes, wildfires and drought. HyspIRI will be able to identify the type of vegetation that is present and whether the vegetation is healthy. The mission will provide a benchmark on the state of the worlds ecosystems against which future changes can be assessed. The mission will also assess the pre-eruptive behavior of volcanoes and the likelihood of future eruptions as well as the carbon and other gases released from wildfires.</p> - - <figure class="figure" style="float:right;margin:0 0 1em 1em;width:50%;"> - <img src="/images/hyspiri-in-space.jpg" class="figure-img img-responsive" alt="" \> - <figcaption class="figure-caption"><b>Figure 2:</b> HyspIRI in Space</figcaption> - </figure> - - <p>The HyspIRI mission includes two instruments mounted on a satellite in Low Earth Orbit. There is an imaging spectrometer measuring from the visible to short wave infrared (VSWIR: 380 nm - 2500 nm) in 10 nm contiguous bands and a multispectral imager measuring from 3 to 12 um in the mid and thermal infrared (TIR). The VSWIR and TIR instruments both have a spatial resolution of 60 m at nadir. The VSWIR will have a revisit of of 19 days and the TIR will have a revisit of 5 days. HyspIRI also includes an Intelligent Payload Module (IPM) which will enable direct broadcast of a subset of the data.</p> - - <p>The data from HyspIRI will be used for a wide variety of studies primarily in the Carbon Cycle and Ecosystem and Earth Surface and Interior focus areas. The mission was recommended in the 2007 National Research Council Decadal Survey requested by NASA, NOAA, and USGS.The mission is currently at the study stage and this website is being provided as a focal point for information on the mission and to keep the community informed on the mission activities.</p> - - <p>We intend to extend COAL to accomodate data from HyspIRI once it is available. In the meantime we look forward to continued work and collaborations with members of the Global Earth Imaging Spectroscopy and Thermal Infrared Measurements community. The COAL poster presented at the HyspIRI Workshop can be downloaded from our <a href="./publications.html">publications page</a>.</p> - -</div> - - - - -<a href="/2017/10/16/coal-fo.html"><h2>COAL Follow-On (COAL-FO) Project Accepted</h2></a> -<p>Posted <b>2017-10-16</b> by <b>Lewis John McGibbney</b></p> -<div class="clearfix"> - - <p>We we absolutely stoked to receive excellent news that the <a href="http://eecs.oregonstate.edu/capstone/submission/?page=preview&pid=320";>COAL Follow-On (COAL-FO) project proposal</a> was accepted by Oregon State Universities Senior Capstone program. This will enable us to continue critical work into COAL software development, research and utilization of the XSEDE Startup resources we have available.</p> - - <p>We are very happy to welcome Kenneth Bertino Thompson and Bryce Egley, our new Senior Computer Scientists from OSU's College for Electrical Engineering and Computer Science to the COAL team. The 2017-2018 project is the successor project to the 2016-2017 COAL project. COAL initially aimed to deliver a suite of algorithms to identify, classify, characterize, and quantify (by reporting a number of key metrics) the direct and indirect impacts of mining operations and related destructive surface mining activities across the continental U.S (and further afield). COAL successfully delivered a Python library for processing hyperspectral imagery from remote sensing devices such as the Airborne Visible/InfraRed Imaging Spectrometer (AVIRIS) and a Science Data System for running COAL pipelines. COAL-FO will utilize recent funding obtained from a recently awarded NSF-funded XSEDE high performance computing (HPC) grant to further improve, validate and document COAL algorithms, execution ru ntime performance and geospatial output results.</p> - -</div> - - - - -<a href="/2017/08/25/final-report-gis-bundle.html"><h2>Final Report and GIS Bundle</h2></a> -<p>Posted <b>2017-08-25</b> by <b>Taylor Alexander Brown</b></p> -<div class="clearfix"> - - <figure class="figure" style="float:right;margin:0 0 1em 1em;width:25%;"> - <img src="/images/final-report.png" class="figure-img img-responsive" alt="The COAL final report cover page" \> - <figcaption class="figure-caption"><b>Figure 1:</b> The COAL final report cover page.</figcaption> - </figure> - - <p>The COAL final report with code and digital artifacts was submitted at the end of the term, completing the 2016 – 2017 senior capstone project. The hard copy of the printed report is on file with the OSU School of Electrical Engineering and Computer Science where it may be shared with students and industry sponsors. This blog post describes how to obtain digital copies of the report and associated files.</p> - - <p>The entire COAL final report submission including all documents, code, and digital artifacts is hosted on Box for Oregon State University. The <a href="https://oregonstate.box.com/s/caaavrxblinttcyoj7qpjyjb7jyztbtv";>archive</a> is in <code>tar.bz2</code> format and is 8.8GB in size. Enclosed within the archive is a <code>README</code> which summarizes the locations of important resources such as documents, presentations, and requisite files.</p> - - <p>The San Juan Mine case study QGIS project and files can be downloaded separately from Google Drive. The <a href="https://drive.google.com/open?id=0BxysdOuBmaIGX0JucjlUZ0d4cGc";>archive</a> is in <code>tar.gz</code> format and is 2GB in size (7GB uncompressed). It contains visible-light, mining classified, and environmental correlation imagery as well as mine permit, hydrography, elevation, and transportation data. Extract the archive and open the project file <code>san‑juan‑mine.qgs</code> with a <a href="/docs#qgis">build of QGIS</a> linked against GDAL 2.2.0+.</p> - - <p>Contact the COAL <a href="/team">team</a> with any questions about accessing the data.</p> - -</div> - - - - -<a href="/2017/06/12/xsede.html"><h2>COAL awarded XSEDE Startup Request</h2></a> -<p>Posted <b>2017-06-12</b> by <b>Lewis John McGibbney</b></p> -<div class="clearfix"> - - <figure class="figure" style="float:right;margin:0 0 1em 1em;width:50%;"> - <img src="/images/image001.png" class="figure-img img-responsive" alt="" \> - <figcaption class="figure-caption"><b>Figure 1:</b> XSEDE Logo</figcaption> - </figure> - - <p>COAL was recently awarded an <a href="https://portal.xsede.org/allocations/startup";>XSEDE Startup Allocation</a> which will be used to continue application development by the team. In addition, we will be looking to undertake benchmarking, evaluation and experimentation on the various XSEDE resources. The availability and opportunity to use computational infrastructure of this calibre will further enable the development of a science gateway to continue foundational COAL research.</p> - - <p>Specifically the allocation details are as follows</p> - <ul> - <li>PI: Lewis McGibbney, NASA JPL</li> - <li>Co-I's: Taylor Alexander Brown, Heidi Ann Clayton and Xiaomei Wang of OSU</li> - <li>Request: Coal and Open-pit surface mining impacts on American Lands (COAL)</li> - <li>Request Number: EAR170010 (New)</li> - <li>Start Date: N/A</li> - <li>End Date: 2018-05-21</li> - <li>Awarded Resources: PSC Large Memory (Bridges Large): 1,000.0 SUs PSC Storage (Bridges Pylon): 2,000.0 GB</li> - </ul> - <p>The estimated value of these awarded resources is $732.00. The allocation of these resources represents a considerable investment by the NSF in advanced computing infrastructure for U.S. The dollar value of the COAL allocation is estimated from the NSF awards supporting the allocated resources.</p> - - <p>Generally speaking we are extermely happy to be in receipt of such an award. It is our aim and intention to publish the progress we make in a series of conference, workshop and journal activities... so watch this space!</p> - -</div> - - - - -<a href="/2017/06/08/release.html"><h2>COAL 0.5.2 released</h2></a> -<p>Posted <b>2017-06-08</b> by <b>Lewis John McGibbney</b></p> -<div class="clearfix"> - - <figure class="figure" style="float:right;margin:0 0 1em 1em;"> - <img src="/images/pypi.jpg" alt="" \> - <figcaption class="figure-caption"><b>Figure 1:</b> Batman dishes out a Python pounding!</figcaption> - </figure> - - <p>We are proud to announce the immediate release and availability of <b>COAL 0.5.2</b>. We urge all users of the <b>pycoal</b> Python package to upgrade to this release immediately.</p> - - <h3>What is COAL?</h3> - <p>COAL is a Python library for processing hyperspectral imagery from remote sensing devices such as the Airborne Visible/InfraRed Imaging Spectrometer (AVIRIS). COAL was originally developed as a 2016âââ2017 senior capstone collaboration between scientists at the Jet Propulsion Laboratory (JPL) and computer science students at Oregon State University (OSU). COAL aims to provide a suite of algorithms for classifying land cover, identifying mines and other geographic features, and correlating them with environmental data sets. COAL is Free and Open Source Software with the pycoal toolkit licensed under the terms of the <a class="external" href="https://www.gnu.org/licenses/gpl-2.0.html";>GPL v2.0</a>.</p> - - <h3>How do I install it?</h3> - <p>The Python COAL package pycoal can be installed from the cheeseshop</p> - <pre>$ pip install pycoal</pre> - <p>or from conda</p> - <pre>$ conda install -c conda-forge pycoal</pre> - - <h3>How do I get started?</h3> - <p>See our <a href="https://capstone-coal.github.io/docs#usage";>Quickstart Documentation</a>.</p> - - <h3>Community and Development</h3> - <p>To become involved or if you require help using the project request to join our <a href="https://groups.google.com/forum/#!forum/coal-capstone";>mailing list</a>. If you have issue using COAL, please log a ticket in our <a href="https://github.com/capstone-coal/pycoal/issues";>Github issue tracker</a>.</p> -</div> - - - - -<a href="/2017/05/25/expo.html"><h2>Undergraduate Engineering Expo 2017</h2></a> -<p>Posted <b>2017-05-25</b> by <b>Taylor Alexander Brown</b></p> -<div class="clearfix"> - - <figure class="figure" style="float:right;margin:0 0 1em 1em;width:50%;"> - <img src="/images/IMG_0896_800.JPG" class="figure-img img-responsive" alt="" \> - <figcaption class="figure-caption"><b>Figure 1:</b> The COAL poster presentation at Expo.</figcaption> - </figure> - - <p>Taylor, Heidi, and Xiaomei from <a href="/team">the COAL team</a> presented the poster and demo at the Undergraduate Engineering Expo 2017 on Friday, May 19<sup>th</sup> 2017. Expo featured more than 200 projects by more than 600 undergraduate students from the College of Engineering at Oregon State University. COAL was promoted by Expo media as an example of computer science excellence. The COAL team shared its methodology and findings with members of the academic community, representatives from industry, and the general public and enjoyed in-depth conversations about remote sensing, environmental science, and software development.</p> - - <p>COAL was selected for one of four industry <a href="http://expo.engr.oregonstate.edu/awards"; class="external">awards</a> presented during Expo, the CH2M Multidisciplinary Collaboration Award. The COAL team spoke with CH2M representatives who were interested in its work with the scientific and Free Software communities and the possible applications of its remote sensing techniques to environmental remediation efforts. After several rounds of interviews with the judges, COAL was chosen based on the following criteria: -</p> - - <blockquote>Complex projects rarely exist within a single technical field. Collaboration between technical specialists is necessary to meet client needs and design criteria. Quality begins with a defined design development process. CH2M will award the Multidisciplinary Collaboration Award to a project team that clearly demonstrates proactive planning and collaboration with others at key points throughout project execution. The impact of the collaboration should be to produce an innovative final product which returns high value to the project sponsor/client or to overcome unique technical challenges. The selected team shall be prepared to describe the design process leading up to the final product, and the lessons learned along the way.</blockquote> - - <p>The award was presented during the ceremony at the end of Expo. The COAL team was honored to be recognized by OSU and CH2M.</p> - - <p>The presentation at Expo provided opportunities to promote the COAL project and communicate its methodology and findings to the public. The interest from members of the community demonstrated that remote sensing is an increasingly important technique for environmental science. The COAL team is pleased with a successful conclusion to its senior capstone collaboration between OSU and JPL.</p> - -</div> - - - - -<a href="/2017/04/30/expo-poster.html"><h2>Expo Poster</h2></a> -<p>Posted <b>2017-04-30</b> by <b>Taylor Alexander Brown</b></p> -<p>In preparation for the <a href="http://engineering.oregonstate.edu/expo2017"; class="external">Undergraduate Engineering Expo 2017</a>, the COAL team has submitted the final draft of its presentation poster for printing. In addition to interactive demonstrations and in-person conversations, the poster will help illustrate the COAL project and the data products produced during its development. A preview of the poster is displayed below and the full version can be downloaded in <a href="/images/expo-poster.pdf">PDF</a> format.</p> - -<figure class="figure"> - <img src="/images/expo-poster.png" class="figure-img img-responsive" alt="COAL poster for Undergraduate Engineering Expo 2017" /> - <figcaption class="figure-caption"><b>Figure 1:</b> COAL poster for Undergraduate Engineering Expo 2017.</figcaption> -</figure> - - - - -<a href="/2017/04/30/gdal-envi-rotation-bug-fix.html"><h2>GDAL ENVI Rotation Bug Fix</h2></a> -<p>Posted <b>2017-04-30</b> by <b>Taylor Alexander Brown</b></p> -<p>COAL is a library for processing imaging spectrometer data from <a href="https://aviris.jpl.nasa.gov/"; class="external">AVIRIS</a> and <a href="https://avirisng.jpl.nasa.gov/"; class="external">AVIRIS-NG</a>. The multiband raster imagery is provided in <a href="http://www.harrisgeospatial.com/docs/enviheaderfiles.html"; class="external">ENVI</a> format. COAL uses the <a href="http://gdal.org/"; class="external">Geospatial Data Abstraction Library (GDAL)</a> and the Free and Open Source geographic information system <a href="http://qgis.org/en/site/"; class="external">QGIS</a> to process imagery and combine it with geographic data for analysis. Due to a bug in GDAL, rotation information in ENVI files was not handled and the images were not imported correctly. This post describes a bug fix which was developed for COAL and contributed back to GDAL.</p> - -<div class="row"> - <div class="col-md-6"> - <figure class="figure"> - <img src="/images/gdal-rotation-bug.png" class="figure-img img-responsive" alt="Incorrectly rotated flightline" /> - <figcaption class="figure-caption"><b>Figure 1:</b> Incorrectly rotated flightline.</figcaption> - </figure> - </div> - <div class="col-md-6"> - <figure class="figure"> - <img src="/images/gdal-rotation-fix.png" class="figure-img img-responsive" alt="Correctly rotated flightline" /> - <figcaption class="figure-caption"><b>Figure 2:</b> Correctly rotated flightline.</figcaption> - </figure> - </div> -</div> - -<!--more--> - -<p>The rotation issue was first discussed <a href="https://groups.google.com/d/msg/coal-capstone/nXhRb1fA7lg/aW8efhNUAgAJ"; class="external">on our mailing list</a> after loading the imagery into GIS applications. The same behavior was observed in QGIS, GRASS, and ArcMap, all of which use the underlying GDAL library. To help solve the problem, a <a href="https://gis.stackexchange.com/questions/229952/rotate-envi-hyperspectral-imagery-with-gdal"; class="external">question</a> was posted to the GIS StackExchange describing the issue and requesting assistance. The proposed answer did not work, suggesting it was due to a <a href="https://trac.osgeo.org/gdal/ticket/1778"; class="external">bug</a> in the ENVI driver of the GDAL library itself.</p> - -<p>It was found that the ENVI rotation parameter, which is not documented in the header file format, was ignored by GDAL when reading the geographic transformation information. As a result, images were imported incorrectly by all software using GDAL, including the Python interface, command-line utilities, and GIS applications. The problem affected the GDAL source file <code>gdal/frmts/raw/envidataset.cpp</code>. Editing this file with the values suggested by the StackExchange answer solved the issue, allowing images to be rotated correctly.</p> - -<p>The solution was shared <a href="https://lists.osgeo.org/pipermail/gdal-dev/2017-February/046127.html"; class="external">on the GDAL mailing list</a> where it received feedback from the GDAL developers. After addressing the changes requested by the maintainers, a <a href="https://github.com/OSGeo/gdal/pull/197"; class="external">pull request</a> was submitted. The maintainer added write support to <a href="https://trac.osgeo.org/gdal/changeset/37506"; class="external">the patch</a> and merged it into the latest version of the library scheduled for release on 2017-05-01 as part of GDAL <a href="https://trac.osgeo.org/gdal/milestone/2.2.0"; class="external">2.2.0</a>. - -<p>The resolution of this bug facilitated continued progress in COAL for processing and visualizing georeferenced raster imagery. It also provided experience contributing to another Free and Open Source Software library. Once the latest version of GDAL is released, QGIS and other applications will have enhanced capabilities for reading and writing ENVI files from AVIRIS, AVIRIS-NG, and other remote-sensing devices.</p> - - - - <!-- footer --> <nav class="navbar navbar-default"> <div class="navbar-header"> @@ -246,6 +55,7 @@ </div> <div class="navbar-text pull-right">© 2017 The Apache Software Foundation. Licensed under <a href="http://www.apache.org/licenses/LICENSE-2.0";>Apache License 2.0</a>.<br/> Apache SDAP, SDAP, Apache, the Apache feather logo, and the Apache SDAP project logo are trademarks of The Apache Software Foundation.</div> + <div class="navbar-text pull-right">Apache SDAP is an effort undergoing <a href="https://incubator.apache.org/";>Incubation</a> at The Apache Software Foundation (ASF), sponsored by the Incubator. Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.</div> </nav> <script src="js/jquery.min.js"></script> http://git-wip-us.apache.org/repos/asf/incubator-sdap-website/blob/6e0454e8/source/_site/docs.html ---------------------------------------------------------------------- diff --git a/source/_site/docs.html b/source/_site/docs.html index 6ef3fe3..f9495ea 100644 --- a/source/_site/docs.html +++ b/source/_site/docs.html @@ -20,7 +20,9 @@ <div class="container"> <div class="logos"> - <!--img src="/images/logo-nasa-jpl-caltech.png" class="pull-left" /--> + <a href="https://incubator.apache.org";> + <img src="/images/egg-logo.png" class="pull-left" /> + </a> </div> <!-- navigation bar --> @@ -44,228 +46,11 @@ <h1>Documentation</h1> -<p>This page describes how to install, use, and contribute to COAL.</p> - -<h2>Contents</h2> - -<ul> - <li><a href="#dependencies">Dependencies</a></li> - <ul> - <li><a href="#numpy-spectral">Numpy and Spectral Python</a></li> - <li><a href="#gdal">GDAL</a></li> - <li><a href="#qgis">QGIS</a></li> - </ul> - <li><a href="#installation">Installation</a></li> - <li><a href="#downloading">Downloading Data</a></li> - <ul> - <li><a href="#udsl06">USGS Digital Spectral Library 06</a></li> - <li><a href="#aviris">AVIRIS</a></li> - <li><a href="#national-map">The National Map</a></li> - </ul> - <li><a href="#usage">Usage</a></li> - <ul> - <li><a href="#mineral">Mineral Classification</a></li> - <li><a href="#mining">Mining Identification</a></li> - <li><a href="#environment">Environmental Correlation</a></li> - </ul> - <li><a href="#development">Development</a></li> -</ul> - -<h2 id="dependencies">Dependencies</h2> - -<p>COAL has been tested on x86_64 GNU/Linux and is expected to work without modification on any Unix-like system. COAL supports <a href="https://www.python.org/"; class="external">Python</a> versions 2.6+ and 3.3+ Required dependencies include <a href="http://www.numpy.org/"; class="external">NumPy</a>, <a href="http://www.spectralpython.net/"; class="external">Spectral Python</a>, and <a href="http://gdal.org/"; class="external">GDAL</a> version 2.2.0+. The recommended geographic information system is <a href="http://qgis.org/en/site/"; class="external">QGIS</a>. - -<h3 id="numpy-spectral">Numpy and Spectral Python</h3> - -<p>The easiest way to install both Numpy and Spectral Python is from the <a href="https://pypi.python.org/pypi"; class="external">Python Package Index (PyPI)</a> with <code>pip</code>:</p> - -<pre>$ sudo pip install spectral</pre> - -<h3 id="gdal">GDAL</h3> - -<p>The command-line utilities from GDAL 2.2.0+ are required for correct processing of <a href="/2017/04/30/gdal-envi-rotation-bug-fix.html">rotated ENVI files</a> in the environmental correlation module. If necessary, GDAL can be installed from source following the instructions for <a href="https://trac.osgeo.org/gdal/wiki/BuildingOnUnix"; class="external">Building on Unix</a>.</p> - -<h4>Install from Source</h4> - -<p>Check out the source code:</p> - -<pre>$ git clone https://github.com/OSGeo/gdal.git -$ cd gdal/gdal -$ git checkout --track origin/2.2</pre> - -<p>Configure GDAL with the Python bindings. The default installation directory is <code>/usr/local</code>. Compile with <code>make</code> and install as root with either <code>make install</code> or <a href="https://wiki.debian.org/CheckInstall"; class="external"><code>checkinstall</code></a> to create a package that can be easily installed and uninstalled. GDAL does not include a <code>make uninstall</code> target.</p> - -<pre>$ ./configure --with-python -$ make -$ sudo checkinstall</pre> - -<p>After installation, the correct version can be verified by calling the command-line interface or Python API.</p> - -<pre>$ gdalwarp --version -GDAL 2.2.0beta2, released 2017/04/23</pre> - -<pre>>>> import osgeo.gdal ->>> print osgeo.gdal.__version__ -2.2.0beta2 ->>> print osgeo.gdal.VersionInfo() -2020000 -</pre> - -<h3 id="qgis">QGIS</h3> - -<p>QGIS is the recommended geographic information system for viewing COAL data products. QGIS must be linked against GDAL 2.2.0+ to import rotated ENVI files correctly. If necessary, install QGIS from source to link to the correct version of GDAL.</p> - -<h4>Install from source</h4> - -<p>See the <code>INSTALL</code> file in the root of the QGIS source tree for more details. The following steps can be used to install QGIS from a Debian source package. We can verify that Debian 8 was used to build QGIS however we encourage feedback and use of newer Debian versions.</p> - -<p>Install the dependencies and download the Debian source package with <code>apt-get</code> or <code>aptitude</code>.</p> - -<pre>$ sudo apt-get update -$ sudo apt-get upgrade -$ sudo apt-get build-dep qgis -$ sudo apt-get install bison cmake doxygen flex git graphviz grass-dev libexpat1-dev libfcgi-dev libgdal-dev libgeos-dev libgsl0-dev libopenscenegraph-dev libosgearth-dev libpq-dev libproj-dev libqt4-dev libqt4-opengl-dev libqtwebkit-dev libqwt-dev libspatialindex-dev libspatialite-dev libsqlite3-dev pkg-config pyqt4-dev-tools python-all python-all-dev python-qt4 python-qt4-dev python-sip python-sip-dev txt2tags xauth xfonts-100dpi xfonts-75dpi xfonts-base xfonts-scalable xvfb devscripts pkg-kde-tools checkinstall -$ apt-get source qgis -$ cd qgis-2.4.0</pre></code> - -<p>Create a build directory and configure QGIS with <code>cmake</code>.</p> - -<pre>$ mkdir build-master -$ cd build-master -$ cmake -Wno-dev -DCMAKE_INSTALL_PREFIX=/usr/local ..</pre> - -<p>Verify that the line <code>-- Found GDAL: /usr/local/lib/libgdal.so (2.2.0beta2)</code> appears in the output. Then compile and install as root.</p> - -<pre>$ make -$ sudo make install</pre> - -<h2 id="installation">Installation</h2> - -<p>The COAL Python package <code>pycoal</code> can be installed from PyPI with <code>pip</code>.</p> - -<pre>$ sudo pip install pycoal</pre> - -<p>The latest development source may be obtained from <a href="https://github.com/capstone-coal/pycoal"; class="external">GitHub</a>.</p> - -<h2 id="downloading">Downloading Data</h2> - -<h3 id="udsl06">USGS Digital Spectral Library 06</h3> - -<p>COAL was developed using classifications from the <a href="https://speclab.cr.usgs.gov/spectral.lib06/"; class="external">USGS Digital Spectral Library 06</a>. The ENVI spectral library files <a href="ftp://ftpext.cr.usgs.gov/pub/cr/co/denver/speclab/pub/spectral.library/splib06.library/Convolved.libraries/s06av95a_envi.hdr"; class="external"><code>s06av95a_envi.hdr</code></a> and <a href="ftp://ftpext.cr.usgs.gov/pub/cr/co/denver/speclab/pub/spectral.library/splib06.library/Convolved.libraries/s06av95a_envi.sli"; class="external"><code>s06av95a_envi.sli</code></a> can be accessed via FTP.</p> - -<h3 id="aviris">AVIRIS</h3> - -<p>Imaging spectrometer data from the Jet Propulsion Laboratory can be downloaded or requested via the <a href="https://aviris.jpl.nasa.gov/"; class="external">AVIRIS</a> and <a href="https://avirisng.jpl.nasa.gov/"; class="external">AVIRIS-NG</a> websites.</p> - -<h3 id="national-map">The National Map</h3> - -<p><a href="https://nationalmap.gov/"; class="external">The National Map</a> from the United States Geological Survey (USGS) provides detailed hydrography, transportation, and elevation datasets.</p> - -<h2 id="usage">Usage</h2> - -<p>This section demonstrates basic usage of COAL. Refer to the <a class="external" href="https://pycoal.readthedocs.io/en/latest/";>API reference</a> for detailed documentation. The following images display several COAL data products.</p> - -<div class="row"> - <div class="col-sm-6"> - <figure class="figure"> - <img src="/images/visible-light.png" class="figure-img img-responsive" alt="Visible-light image" /> - <figcaption class="figure-caption"><b>Figure 1:</b> Visible-light image.</figcaption> - </figure> - </div> - <div class="col-sm-6"> - <figure class="figure"> - <img src="/images/mineral-classified.png" class="figure-img img-responsive" alt="Mineral classified image" /> - <figcaption class="figure-caption"><b>Figure 2:</b> Mineral classified image.</figcaption> - </figure> - </div> -</div> -<div class="row"> - <div class="col-sm-6"> - <figure class="figure"> - <img src="/images/mining-classified.png" class="figure-img img-responsive" alt="Mining classified image" /> - <figcaption class="figure-caption"><b>Figure 3:</b> Mining classified image.</figcaption> - </figure> - </div> - <div class="col-sm-6"> - <figure class="figure"> - <img src="/images/environmental-correlation.png" class="figure-img img-responsive" alt="Environmental correlation image" /> - <figcaption class="figure-caption"><b>Figure 4:</b> Environmental correlation image.</figcaption> - </figure> - </div> -</div> - -<h3 id="mineral">Mineral Classification</h3> - -<p>The <a href="https://pycoal.readthedocs.io/en/latest/mineral.html"; class="external">Mineral Classification API</a> provides methods for generating visible-light (Figure 1) and mineral classified (Figure 2) images. Mineral classification can take hours to days depending on the size of the spectral library and the available computing resources, so running a script in the background is recommended.</p> - -<pre>#!/usr/bin/env python -import pycoal - -# path to spectral library -library_filename = "s06av95a_envi.hdr" - -# path to orthocorrected, scaled-reflectance image -input_filename = "ang20150420t182050_corr_v1e_img.hdr" - -# path to save RGB image -rgb_filename = "ang20150420t182050_corr_v1e_img_rgb.hdr" - -# path to save mineral classified image -classified_filename = "ang20150420t182050_corr_v1e_img_class.hdr" - -# create a new mineral classification instance -mineral_classification = pycoal.mineral.MineralClassification(input_filename) - -# generate a georeferenced visible-light image -mineral_classification.to_rgb(input_filename, rgb_filename) - -# generate a mineral classified image -mineral_classification.classify_image(input_filename, classified_filename)</pre> - -<h3 id="mining">Mining Identification</h3> - -<p>The <a href="https://pycoal.readthedocs.io/en/latest/mining.html"; class="external">Mining Identification API</a> filters mineral classified images to identify specific classes of interest (Figure 3), by default proxies for coal mining in the USGS Digital Spectral Library 06.</p> - -<pre>#!/usr/bin/env python -import pycoal - -# path to mineral classified image -mineral_filename = "ang20150420t182050_corr_v1e_img_class.hdr" - -# path to save mining classified image -mining_filename = "ang20150420t182050_corr_v1e_img_class_mining.hdr" - -# create a new mining classification instance -mining_classification = pycoal.mining.MiningClassification() - -# generate a mining classified image -mining_classification.classify_image(mineral_filename, mining_filename)</pre> - -<h3 id="environment">Environmental Correlation</h3> - -<p>The <a href="https://pycoal.readthedocs.io/en/latest/environment.html"; class="external">Environmental Correlation API</a> finds pixels in a mining classified image that are within a certain number of meters from features in a vector layer (Figure 4) such as flow lines in the National Hydrography Dataset (NHD).</p> - -<pre>#!/usr/bin/env python -import pycoal - -# path to mining classified image -mining_filename = "ang20150420t182050_corr_v1e_img_class_mining.hdr" - -# path to hydrography data -vector_filename = "NHDNM/Shape/NHDFlowline.shp" - -# path to save environmental correlation image -correlation_filename = "ang20150420t182050_corr_v1e_img_class_mining_NHDFlowline_correlation.hdr" - -# create a new environmental correlation instance -environmental_correlation = pycoal.environment.EnvironmentalCorrelation() - -# generate an environmental correlation image of mining pixels within 10 meters of a stream -environmental_correlation.intersect_proximity(mining_filename, vector_filename, 10.0, correlation_filename)</pre> +<p>This page describes how to install, use, and contribute to SDAP.</p> <h2 id="development">Development</h2> -<p>Contribute to the project through our <a class="external" href="https://github.com/capstone-coal";>GitHub Organization</a>, refer to the COAL <a class="external" href="https://github.com/capstone-coal/pycoal/wiki";>wiki</a> for development documentation, and contact the <a href="/team.html">team</a> to get involved.</p> +<p>Get involved and contribute to SDAP through our <a href="http://sdap.apache.org/team";>Community Hubs</a>. <!-- footer --> <nav class="navbar navbar-default"> @@ -274,6 +59,7 @@ environmental_correlation.intersect_proximity(mining_filename, vector_filename, </div> <div class="navbar-text pull-right">© 2017 The Apache Software Foundation. Licensed under <a href="http://www.apache.org/licenses/LICENSE-2.0";>Apache License 2.0</a>.<br/> Apache SDAP, SDAP, Apache, the Apache feather logo, and the Apache SDAP project logo are trademarks of The Apache Software Foundation.</div> + <div class="navbar-text pull-right">Apache SDAP is an effort undergoing <a href="https://incubator.apache.org/";>Incubation</a> at The Apache Software Foundation (ASF), sponsored by the Incubator. Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.</div> </nav> <script src="js/jquery.min.js"></script> http://git-wip-us.apache.org/repos/asf/incubator-sdap-website/blob/6e0454e8/source/_site/images/egg-logo.png ---------------------------------------------------------------------- diff --git a/source/_site/images/egg-logo.png b/source/_site/images/egg-logo.png new file mode 100644 index 0000000..759252f Binary files /dev/null and b/source/_site/images/egg-logo.png differ http://git-wip-us.apache.org/repos/asf/incubator-sdap-website/blob/6e0454e8/source/_site/index.html ---------------------------------------------------------------------- diff --git a/source/_site/index.html b/source/_site/index.html index 525a010..383b269 100644 --- a/source/_site/index.html +++ b/source/_site/index.html @@ -20,7 +20,9 @@ <div class="container"> <div class="logos"> - <!--img src="/images/logo-nasa-jpl-caltech.png" class="pull-left" /--> + <a href="https://incubator.apache.org";> + <img src="/images/egg-logo.png" class="pull-left" /> + </a> </div> <!-- navigation bar --> @@ -135,6 +137,7 @@ Courtesy NASA/JPL-Caltech." /> </div> <div class="navbar-text pull-right">© 2017 The Apache Software Foundation. Licensed under <a href="http://www.apache.org/licenses/LICENSE-2.0";>Apache License 2.0</a>.<br/> Apache SDAP, SDAP, Apache, the Apache feather logo, and the Apache SDAP project logo are trademarks of The Apache Software Foundation.</div> + <div class="navbar-text pull-right">Apache SDAP is an effort undergoing <a href="https://incubator.apache.org/";>Incubation</a> at The Apache Software Foundation (ASF), sponsored by the Incubator. Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.</div> </nav> <script src="js/jquery.min.js"></script> http://git-wip-us.apache.org/repos/asf/incubator-sdap-website/blob/6e0454e8/source/_site/publications.html ---------------------------------------------------------------------- diff --git a/source/_site/publications.html b/source/_site/publications.html index 82695ac..a1a4f85 100644 --- a/source/_site/publications.html +++ b/source/_site/publications.html @@ -20,7 +20,9 @@ <div class="container"> <div class="logos"> - <!--img src="/images/logo-nasa-jpl-caltech.png" class="pull-left" /--> + <a href="https://incubator.apache.org";> + <img src="/images/egg-logo.png" class="pull-left" /> + </a> </div> <!-- navigation bar --> @@ -44,16 +46,13 @@ <h1>Publications</h1> -<p>Here you can find all COAL publications, they are ordered in reverse chronological order.</p> +<p>Here you can find all SDAP publications, they are ordered in reverse chronological order.</p> <ul> - <li><a href="/publications/bids2017_coal.pdf">McGibbney, L. J., Brown, T. A., Clayton, H. A., Wang, X. (2017) "COAL AND OPEN-PIT MINING IMPACTS ON AMERICAN LANDS (COAL): A PYTHON LIBRARY FOR PROCESSING HYPERSPECTRAL IMAGERY", <i>2017 Conference on Big Data from Space (BiDS'17) Research, Technology and Innovation</i>, 28-30 November 2017 Centre de Congrès Pierre Baudis, Toulouse, France</a></li> - <li><a href="/publications/hyspiri_workshop_poster.pdf">McGibbney, L. J., Brown, T. A., Clayton, H. A., Wang, X. (2017) "COAL AND OPEN-PIT SURFACE MINING IMPACTS ON AMERICAN LANDS (COAL)", <i>2017 Conference on Big Data from Space (BiDS'17) Research, Technology and Innovation</i>, 28-30 November 2017 Centre de Congrès Pierre Baudis, Toulouse, France</a></li> - <li><a href="/publications/hyspiri_workshop_poster.pdf">McGibbney, L. J., Brown, T. A., Clayton, H. A., Wang, X. (2017) "COAL AND OPEN-PIT SURFACE MINING IMPACTS ON AMERICAN LANDS (COAL)", <i>2017 HyspIRI Science and Applications Workshop</i>, 17-19 October 2017 California Institute of Technology Beckman Institute Auditorium 1200 E California Blvd Pasadena, CA</a></li> - <li><a href="/images/expo-poster.pdf">McGibbney, L. J., Brown, T. A., Clayton, H. A., Wang, X. (2017) "COAL AND OPEN-PIT MINING IMPACTS ON AMERICAN LANDS (COAL): A PYTHON LIBRARY FOR PROCESSING HYPERSPECTRAL IMAGERY", <i>Oregon State University Undergraduate Engineering Expo 2017</i>, 19 May 2017 Kelley Engineering Center, Johnson Hall, Oregon State University</a></li> + <li>todo</li> </ul> -<p>Contribute to the project through our <a class="external" href="https://github.com/capstone-coal";>GitHub Organization</a>, refer to the COAL <a class="external" href="https://github.com/capstone-coal/pycoal/wiki";>wiki</a> for development documentation, and contact the <a href="/team.html">team</a> to get involved.</p> +<p>Get involved and contribute to SDAP through our <a href="http://sdap.apache.org/team";>Community Hubs</a>. <!-- footer --> <nav class="navbar navbar-default"> @@ -62,6 +61,7 @@ </div> <div class="navbar-text pull-right">© 2017 The Apache Software Foundation. Licensed under <a href="http://www.apache.org/licenses/LICENSE-2.0";>Apache License 2.0</a>.<br/> Apache SDAP, SDAP, Apache, the Apache feather logo, and the Apache SDAP project logo are trademarks of The Apache Software Foundation.</div> + <div class="navbar-text pull-right">Apache SDAP is an effort undergoing <a href="https://incubator.apache.org/";>Incubation</a> at The Apache Software Foundation (ASF), sponsored by the Incubator. Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.</div> </nav> <script src="js/jquery.min.js"></script> http://git-wip-us.apache.org/repos/asf/incubator-sdap-website/blob/6e0454e8/source/_site/resources.html ---------------------------------------------------------------------- diff --git a/source/_site/resources.html b/source/_site/resources.html index 7b25b23..cfb8efa 100644 --- a/source/_site/resources.html +++ b/source/_site/resources.html @@ -20,7 +20,9 @@ <div class="container"> <div class="logos"> - <!--img src="/images/logo-nasa-jpl-caltech.png" class="pull-left" /--> + <a href="https://incubator.apache.org";> + <img src="/images/egg-logo.png" class="pull-left" /> + </a> </div> <!-- navigation bar --> @@ -44,41 +46,11 @@ <h1>Resources</h1> -<p>A collection of useful resources generated by or related to COAL</p> +<p>A collection of useful resources generated by or related to SDAP</p> <h2>Videos</h2> -<h3>NASA Studies Volcanos and Coral Reefs from 65,000 feet (HyspIRI Hawaii, Part 1)</h3> -<iframe width="560" height="315" src="https://www.youtube.com/embed/iKGeufqQqyc"; frameborder="0" allowfullscreen></iframe> -<p>This 6-minute, 8-second video shows how a NASA-led science team spent six weeks in January and February studying Hawaii's volcanoes and coral reefs using the Agency's ER-2 aircraft. The mission, called Hyperspectral InfraRed Imager (HyspIRI), focused on observing coral reef health and volcano emissions and eruptions. Flying at 65,000 feet (19,800 meters), above 95 percent of Earthâs atmosphere, the ER-2 can closely replicate the data a future satellite could collect. Data from this mission will help in developing a NASA satellite to study natural hazards and ecosystems. NASA's ER-2 aircraft are operated by NASA's Armstrong Flight Research Center and based at Hangar 703 in Palmdale, CA.</p> - -<h3>From the Ground Up: Building an Earth Science Satellite (HyspIRI Hawaii, Part 2)</h3> -<iframe width="560" height="315" src="https://www.youtube.com/embed/eAxZuFk7kPQ"; frameborder="0" allowfullscreen></iframe> -<p>In this 2-minute, 37-second video, the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) flies high aboard NASAâs ER-2, using over 224 sensors to identify, measure, and monitor natural features of the Earth's surface and atmosphere based on reflective light from the sun. The instrument was recently used for the Hyperspectral InfraRed Imager (HyspIRI) airborne preparatory mission, which focused on observing coral reef health and volcano emissions and eruptions around the Hawaiian Islands. Data from this mission will help develop a NASA satellite to study natural hazards and ecosystems. The Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) instrument is developed and managed by NASA's Jet Propulsion Laboratory, Pasadena, CA. NASAâs ER-2 aircraft is managed and based at NASAâs Armstrong Flight Research Center, Hangar 703 in Palmdale, CA.</p> - -<h3>From the Ground Up: Building an Earth Science Satellite (HyspIRI Hawaii, Part 3)</h3> -<iframe width="560" height="315" src="https://www.youtube.com/embed/Ts71279n8FE"; frameborder="0" allowfullscreen></iframe> -<p>Before a satellite is launched into orbit, scientists use instruments on NASA aircraft to calibrate, validate, and refine sensors that are part of current and future satellite payloads. In this 3-minute, 44-second video, data systems analyst Eric Fraim explains how an instrument called MASTER (MODIS Airborne ASTER Simulator) is being used to further develop Earth observing satellites. Flying on board NASAâs high-altitude ER-2, MASTER can detect thermal and visible spectral data as it scans air columns between the ground and the aircraft. The instrument was recently used for the Hyperspectral InfraRed Imager (HyspIRI) airborne preparatory mission, which focused on observing coral reef health and volcano emissions and eruptions around the Hawaiian Islands. HyspIRI is a proposed NASA satellite concept that will study natural hazards and ecosystems. The MODIS/ASTER (MASTER) airborne simulator is a joint development involving the Airborne Sensor Facility at the Ames Research Center, the Jet Propulsion Laboratory and the EROS Data Center. NASAâs ER-2 aircraft is managed and based at NASAâs Armstrong Flight Research Center, Hangar 703 in Palmdale, CA.</p> - -<h3>From the Ground Up: Building an Earth Science Satellite (HyspIRI Hawaii, Part 4)</h3> -<iframe width="560" height="315" src="https://www.youtube.com/embed/kljFd9Aai7c"; frameborder="0" allowfullscreen></iframe> -<p>In this 5-minute, 5-second video, noxious sulfur dioxide gas and other pollutants emitted from Kilauea Volcano on the Island of Hawai`i react with oxygen and atmospheric moisture to produce volcanic smog (vog) and acid rain. These forms of pollution are recurrent health issues for the citizens of Hawaii. Vog can aggravate preexisting respiratory ailments and create conditions for acid rain, which damages crops and can leach lead into household water supplies. Scientists from the U.S. Geological Survey's (USGS) Hawaiian Volcano Observatory (HVO) at the summit of Kilauea closely monitor the amount and composition of gas emissions from the volcano's ongoing eruption. In February 2017, NASA scientists joined efforts with USGS, collecting data on the ground and from NASAâs high-altitude ER-2 aircraft as part of the Hyperspectral InfraRed Imager (HyspIRI) airborne preparatory mission. Data from this mission will potentially help develop a NASA satellite to study natural hazards and e cosystems, including those affected by volcanic activity. The ER-2 aircraft is operated by NASA's Armstrong Flight Research Center and based at Hangar 703 in Palmdale, CA.</p> - -<h3>From the Ground Up: Building an Earth Science Satellite (HyspIRI Hawaii, Part 5)</h3> -<iframe width="560" height="315" src="https://www.youtube.com/embed/qdjsfKky4Dw"; frameborder="0" allowfullscreen></iframe> -<p>In this 5-minute, 52-second video, scientists from NASA and University of Hawaii, in partnership the U.S. Naval Research Laboratory, teamed up in February 2017 to study the health of coral reefs located around the Hawaiian Islands for the Hyperspectral InfraRed Imager (HyspIRI) airborne preparatory mission. Research divers and an autonomous kayak monitored coral color signatures from the ocean floor and surface, while NASAâs high-altitude ER-2 collected images of the same areas from a height of 70,000 ft. The data from these sources are being combined to better understand how coral reef ecosystems are responding to stressful conditions like warming ocean temperatures and water acidification. Data from this mission will potentially help develop a NASA satellite to study natural hazards and ecosystems all over the world. The ER-2 aircraft is operated by NASA's Armstrong Flight Research Center and based at Hangar 703 in Palmdale, CA.</p> - -<h3>Blowing Up Mountains: Destroying the Environment for Coal</h3> -<iframe width="560" height="315" src="https://www.youtube.com/embed/UvKe2LYy5pk"; frameborder="0" allowfullscreen></iframe> -<p>Massive corporations are blowing up mountains and creating environmental ruins in West Virginia. All this devastation, just to extract some coal. VICE News went to West Virginia to investigate mountain-top removal -- which a way of extracting coal from deposits under mountains. Instead of drilling into the mountain and sending men underground to take out the coal in the traditional way, they just take the whole top of a mountain off.</p> - -<h3>AVIRIS-Faces of Earth</h3> -<iframe width="560" height="315" src="https://www.youtube.com/embed/cg2B05ZCw18"; frameborder="0" allowfullscreen></iframe> -<p>Faces of Earth is a 4-hour high-definition television series about the ever-changing planet we live on. The only thing constant on Earth is change and Faces of Earth examines this phenomenon through the eyes of those that know it best - geoscientists. Explosive volcanic eruptions, earthquakes, floods and even human beings contribute to the constant changes on the Earth's surface. -Explore how through time the forces of nature have continuously remade Earth - giving it many distinct faces through history, and many new ones into the future. Faces of Earth is shot in stunning high-definition with extensive aerials, cutting edge animations, and engaging interviews. Discover the compelling story of how the world's titanic forces play a key role in just about every aspect of life. Geoscientists note that by understanding Earth's constantly shifting surface, we can prepare for changes such as volcanic eruptions, earthquakes and floods to perhaps make adjustments for what lies ahead. Watch as Faces of Earth peels back the layers of Earth's geologic system to uncover a world of mystery. -Uncover the deep mysteries of our planet with top geologists in Faces Of Earth. Using state-of-the-art computer animation and stunning photography, these four in-depth, compelling programs explore how these forces shape the Earth and how, in turn, the Earth has shaped human evolution.</p> - -<p>Contribute to the project through our <a class="external" href="https://github.com/capstone-coal";>GitHub Organization</a>, refer to the COAL <a class="external" href="https://github.com/capstone-coal/pycoal/wiki";>wiki</a> for development documentation, and contact the <a href="/team.html">team</a> to get involved.</p> +<p>Get involved and contribute to SDAP through our <a href="http://sdap.apache.org/team";>Community Hubs</a>. <!-- footer --> <nav class="navbar navbar-default"> @@ -87,6 +59,7 @@ Uncover the deep mysteries of our planet with top geologists in Faces Of Earth. </div> <div class="navbar-text pull-right">© 2017 The Apache Software Foundation. Licensed under <a href="http://www.apache.org/licenses/LICENSE-2.0";>Apache License 2.0</a>.<br/> Apache SDAP, SDAP, Apache, the Apache feather logo, and the Apache SDAP project logo are trademarks of The Apache Software Foundation.</div> + <div class="navbar-text pull-right">Apache SDAP is an effort undergoing <a href="https://incubator.apache.org/";>Incubation</a> at The Apache Software Foundation (ASF), sponsored by the Incubator. Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.</div> </nav> <script src="js/jquery.min.js"></script> http://git-wip-us.apache.org/repos/asf/incubator-sdap-website/blob/6e0454e8/source/_site/team.html ---------------------------------------------------------------------- diff --git a/source/_site/team.html b/source/_site/team.html index e34c4e7..002e6ff 100644 --- a/source/_site/team.html +++ b/source/_site/team.html @@ -20,7 +20,9 @@ <div class="container"> <div class="logos"> - <!--img src="/images/logo-nasa-jpl-caltech.png" class="pull-left" /--> + <a href="https://incubator.apache.org";> + <img src="/images/egg-logo.png" class="pull-left" /> + </a> </div> <!-- navigation bar --> @@ -215,6 +217,7 @@ </div> <div class="navbar-text pull-right">© 2017 The Apache Software Foundation. Licensed under <a href="http://www.apache.org/licenses/LICENSE-2.0";>Apache License 2.0</a>.<br/> Apache SDAP, SDAP, Apache, the Apache feather logo, and the Apache SDAP project logo are trademarks of The Apache Software Foundation.</div> + <div class="navbar-text pull-right">Apache SDAP is an effort undergoing <a href="https://incubator.apache.org/";>Incubation</a> at The Apache Software Foundation (ASF), sponsored by the Incubator. Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.</div> </nav> <script src="js/jquery.min.js"></script> http://git-wip-us.apache.org/repos/asf/incubator-sdap-website/blob/6e0454e8/source/docs.html ---------------------------------------------------------------------- diff --git a/source/docs.html b/source/docs.html index f730969..1eafe40 100644 --- a/source/docs.html +++ b/source/docs.html @@ -5,227 +5,10 @@ <h1>Documentation</h1> -<p>This page describes how to install, use, and contribute to COAL.</p> - -<h2>Contents</h2> - -<ul> - <li><a href="#dependencies">Dependencies</a></li> - <ul> - <li><a href="#numpy-spectral">Numpy and Spectral Python</a></li> - <li><a href="#gdal">GDAL</a></li> - <li><a href="#qgis">QGIS</a></li> - </ul> - <li><a href="#installation">Installation</a></li> - <li><a href="#downloading">Downloading Data</a></li> - <ul> - <li><a href="#udsl06">USGS Digital Spectral Library 06</a></li> - <li><a href="#aviris">AVIRIS</a></li> - <li><a href="#national-map">The National Map</a></li> - </ul> - <li><a href="#usage">Usage</a></li> - <ul> - <li><a href="#mineral">Mineral Classification</a></li> - <li><a href="#mining">Mining Identification</a></li> - <li><a href="#environment">Environmental Correlation</a></li> - </ul> - <li><a href="#development">Development</a></li> -</ul> - -<h2 id="dependencies">Dependencies</h2> - -<p>COAL has been tested on x86_64 GNU/Linux and is expected to work without modification on any Unix-like system. COAL supports <a href="https://www.python.org/"; class="external">Python</a> versions 2.6+ and 3.3+ Required dependencies include <a href="http://www.numpy.org/"; class="external">NumPy</a>, <a href="http://www.spectralpython.net/"; class="external">Spectral Python</a>, and <a href="http://gdal.org/"; class="external">GDAL</a> version 2.2.0+. The recommended geographic information system is <a href="http://qgis.org/en/site/"; class="external">QGIS</a>. - -<h3 id="numpy-spectral">Numpy and Spectral Python</h3> - -<p>The easiest way to install both Numpy and Spectral Python is from the <a href="https://pypi.python.org/pypi"; class="external">Python Package Index (PyPI)</a> with <code>pip</code>:</p> - -<pre>$ sudo pip install spectral</pre> - -<h3 id="gdal">GDAL</h3> - -<p>The command-line utilities from GDAL 2.2.0+ are required for correct processing of <a href="/2017/04/30/gdal-envi-rotation-bug-fix.html">rotated ENVI files</a> in the environmental correlation module. If necessary, GDAL can be installed from source following the instructions for <a href="https://trac.osgeo.org/gdal/wiki/BuildingOnUnix"; class="external">Building on Unix</a>.</p> - -<h4>Install from Source</h4> - -<p>Check out the source code:</p> - -<pre>$ git clone https://github.com/OSGeo/gdal.git -$ cd gdal/gdal -$ git checkout --track origin/2.2</pre> - -<p>Configure GDAL with the Python bindings. The default installation directory is <code>/usr/local</code>. Compile with <code>make</code> and install as root with either <code>make install</code> or <a href="https://wiki.debian.org/CheckInstall"; class="external"><code>checkinstall</code></a> to create a package that can be easily installed and uninstalled. GDAL does not include a <code>make uninstall</code> target.</p> - -<pre>$ ./configure --with-python -$ make -$ sudo checkinstall</pre> - -<p>After installation, the correct version can be verified by calling the command-line interface or Python API.</p> - -<pre>$ gdalwarp --version -GDAL 2.2.0beta2, released 2017/04/23</pre> - -<pre>>>> import osgeo.gdal ->>> print osgeo.gdal.__version__ -2.2.0beta2 ->>> print osgeo.gdal.VersionInfo() -2020000 -</pre> - -<h3 id="qgis">QGIS</h3> - -<p>QGIS is the recommended geographic information system for viewing COAL data products. QGIS must be linked against GDAL 2.2.0+ to import rotated ENVI files correctly. If necessary, install QGIS from source to link to the correct version of GDAL.</p> - -<h4>Install from source</h4> - -<p>See the <code>INSTALL</code> file in the root of the QGIS source tree for more details. The following steps can be used to install QGIS from a Debian source package. We can verify that Debian 8 was used to build QGIS however we encourage feedback and use of newer Debian versions.</p> - -<p>Install the dependencies and download the Debian source package with <code>apt-get</code> or <code>aptitude</code>.</p> - -<pre>$ sudo apt-get update -$ sudo apt-get upgrade -$ sudo apt-get build-dep qgis -$ sudo apt-get install bison cmake doxygen flex git graphviz grass-dev libexpat1-dev libfcgi-dev libgdal-dev libgeos-dev libgsl0-dev libopenscenegraph-dev libosgearth-dev libpq-dev libproj-dev libqt4-dev libqt4-opengl-dev libqtwebkit-dev libqwt-dev libspatialindex-dev libspatialite-dev libsqlite3-dev pkg-config pyqt4-dev-tools python-all python-all-dev python-qt4 python-qt4-dev python-sip python-sip-dev txt2tags xauth xfonts-100dpi xfonts-75dpi xfonts-base xfonts-scalable xvfb devscripts pkg-kde-tools checkinstall -$ apt-get source qgis -$ cd qgis-2.4.0</pre></code> - -<p>Create a build directory and configure QGIS with <code>cmake</code>.</p> - -<pre>$ mkdir build-master -$ cd build-master -$ cmake -Wno-dev -DCMAKE_INSTALL_PREFIX=/usr/local ..</pre> - -<p>Verify that the line <code>-- Found GDAL: /usr/local/lib/libgdal.so (2.2.0beta2)</code> appears in the output. Then compile and install as root.</p> - -<pre>$ make -$ sudo make install</pre> - -<h2 id="installation">Installation</h2> - -<p>The COAL Python package <code>pycoal</code> can be installed from PyPI with <code>pip</code>.</p> - -<pre>$ sudo pip install pycoal</pre> - -<p>The latest development source may be obtained from <a href="https://github.com/capstone-coal/pycoal"; class="external">GitHub</a>.</p> - -<h2 id="downloading">Downloading Data</h2> - -<h3 id="udsl06">USGS Digital Spectral Library 06</h3> - -<p>COAL was developed using classifications from the <a href="https://speclab.cr.usgs.gov/spectral.lib06/"; class="external">USGS Digital Spectral Library 06</a>. The ENVI spectral library files <a href="ftp://ftpext.cr.usgs.gov/pub/cr/co/denver/speclab/pub/spectral.library/splib06.library/Convolved.libraries/s06av95a_envi.hdr"; class="external"><code>s06av95a_envi.hdr</code></a> and <a href="ftp://ftpext.cr.usgs.gov/pub/cr/co/denver/speclab/pub/spectral.library/splib06.library/Convolved.libraries/s06av95a_envi.sli"; class="external"><code>s06av95a_envi.sli</code></a> can be accessed via FTP.</p> - -<h3 id="aviris">AVIRIS</h3> - -<p>Imaging spectrometer data from the Jet Propulsion Laboratory can be downloaded or requested via the <a href="https://aviris.jpl.nasa.gov/"; class="external">AVIRIS</a> and <a href="https://avirisng.jpl.nasa.gov/"; class="external">AVIRIS-NG</a> websites.</p> - -<h3 id="national-map">The National Map</h3> - -<p><a href="https://nationalmap.gov/"; class="external">The National Map</a> from the United States Geological Survey (USGS) provides detailed hydrography, transportation, and elevation datasets.</p> - -<h2 id="usage">Usage</h2> - -<p>This section demonstrates basic usage of COAL. Refer to the <a class="external" href="https://pycoal.readthedocs.io/en/latest/";>API reference</a> for detailed documentation. The following images display several COAL data products.</p> - -<div class="row"> - <div class="col-sm-6"> - <figure class="figure"> - <img src="/images/visible-light.png" class="figure-img img-responsive" alt="Visible-light image" /> - <figcaption class="figure-caption"><b>Figure 1:</b> Visible-light image.</figcaption> - </figure> - </div> - <div class="col-sm-6"> - <figure class="figure"> - <img src="/images/mineral-classified.png" class="figure-img img-responsive" alt="Mineral classified image" /> - <figcaption class="figure-caption"><b>Figure 2:</b> Mineral classified image.</figcaption> - </figure> - </div> -</div> -<div class="row"> - <div class="col-sm-6"> - <figure class="figure"> - <img src="/images/mining-classified.png" class="figure-img img-responsive" alt="Mining classified image" /> - <figcaption class="figure-caption"><b>Figure 3:</b> Mining classified image.</figcaption> - </figure> - </div> - <div class="col-sm-6"> - <figure class="figure"> - <img src="/images/environmental-correlation.png" class="figure-img img-responsive" alt="Environmental correlation image" /> - <figcaption class="figure-caption"><b>Figure 4:</b> Environmental correlation image.</figcaption> - </figure> - </div> -</div> - -<h3 id="mineral">Mineral Classification</h3> - -<p>The <a href="https://pycoal.readthedocs.io/en/latest/mineral.html"; class="external">Mineral Classification API</a> provides methods for generating visible-light (Figure 1) and mineral classified (Figure 2) images. Mineral classification can take hours to days depending on the size of the spectral library and the available computing resources, so running a script in the background is recommended.</p> - -<pre>#!/usr/bin/env python -import pycoal - -# path to spectral library -library_filename = "s06av95a_envi.hdr" - -# path to orthocorrected, scaled-reflectance image -input_filename = "ang20150420t182050_corr_v1e_img.hdr" - -# path to save RGB image -rgb_filename = "ang20150420t182050_corr_v1e_img_rgb.hdr" - -# path to save mineral classified image -classified_filename = "ang20150420t182050_corr_v1e_img_class.hdr" - -# create a new mineral classification instance -mineral_classification = pycoal.mineral.MineralClassification(input_filename) - -# generate a georeferenced visible-light image -mineral_classification.to_rgb(input_filename, rgb_filename) - -# generate a mineral classified image -mineral_classification.classify_image(input_filename, classified_filename)</pre> - -<h3 id="mining">Mining Identification</h3> - -<p>The <a href="https://pycoal.readthedocs.io/en/latest/mining.html"; class="external">Mining Identification API</a> filters mineral classified images to identify specific classes of interest (Figure 3), by default proxies for coal mining in the USGS Digital Spectral Library 06.</p> - -<pre>#!/usr/bin/env python -import pycoal - -# path to mineral classified image -mineral_filename = "ang20150420t182050_corr_v1e_img_class.hdr" - -# path to save mining classified image -mining_filename = "ang20150420t182050_corr_v1e_img_class_mining.hdr" - -# create a new mining classification instance -mining_classification = pycoal.mining.MiningClassification() - -# generate a mining classified image -mining_classification.classify_image(mineral_filename, mining_filename)</pre> - -<h3 id="environment">Environmental Correlation</h3> - -<p>The <a href="https://pycoal.readthedocs.io/en/latest/environment.html"; class="external">Environmental Correlation API</a> finds pixels in a mining classified image that are within a certain number of meters from features in a vector layer (Figure 4) such as flow lines in the National Hydrography Dataset (NHD).</p> - -<pre>#!/usr/bin/env python -import pycoal - -# path to mining classified image -mining_filename = "ang20150420t182050_corr_v1e_img_class_mining.hdr" - -# path to hydrography data -vector_filename = "NHDNM/Shape/NHDFlowline.shp" - -# path to save environmental correlation image -correlation_filename = "ang20150420t182050_corr_v1e_img_class_mining_NHDFlowline_correlation.hdr" - -# create a new environmental correlation instance -environmental_correlation = pycoal.environment.EnvironmentalCorrelation() - -# generate an environmental correlation image of mining pixels within 10 meters of a stream -environmental_correlation.intersect_proximity(mining_filename, vector_filename, 10.0, correlation_filename)</pre> +<p>This page describes how to install, use, and contribute to SDAP.</p> <h2 id="development">Development</h2> -<p>Contribute to the project through our <a class="external" href="https://github.com/capstone-coal";>GitHub Organization</a>, refer to the COAL <a class="external" href="https://github.com/capstone-coal/pycoal/wiki";>wiki</a> for development documentation, and contact the <a href="/team.html">team</a> to get involved.</p> +<p>Get involved and contribute to SDAP through our <a href="http://sdap.apache.org/team";>Community Hubs</a>. {% include footer.html %} http://git-wip-us.apache.org/repos/asf/incubator-sdap-website/blob/6e0454e8/source/images/egg-logo.png ---------------------------------------------------------------------- diff --git a/source/images/egg-logo.png b/source/images/egg-logo.png new file mode 100644 index 0000000..759252f Binary files /dev/null and b/source/images/egg-logo.png differ http://git-wip-us.apache.org/repos/asf/incubator-sdap-website/blob/6e0454e8/source/publications.html ---------------------------------------------------------------------- diff --git a/source/publications.html b/source/publications.html index e3aaf07..8545cef 100644 --- a/source/publications.html +++ b/source/publications.html @@ -5,15 +5,12 @@ <h1>Publications</h1> -<p>Here you can find all COAL publications, they are ordered in reverse chronological order.</p> +<p>Here you can find all SDAP publications, they are ordered in reverse chronological order.</p> <ul> - <li><a href="/publications/bids2017_coal.pdf">McGibbney, L. J., Brown, T. A., Clayton, H. A., Wang, X. (2017) "COAL AND OPEN-PIT MINING IMPACTS ON AMERICAN LANDS (COAL): A PYTHON LIBRARY FOR PROCESSING HYPERSPECTRAL IMAGERY", <i>2017 Conference on Big Data from Space (BiDS'17) Research, Technology and Innovation</i>, 28-30 November 2017 Centre de Congrès Pierre Baudis, Toulouse, France</a></li> - <li><a href="/publications/hyspiri_workshop_poster.pdf">McGibbney, L. J., Brown, T. A., Clayton, H. A., Wang, X. (2017) "COAL AND OPEN-PIT SURFACE MINING IMPACTS ON AMERICAN LANDS (COAL)", <i>2017 Conference on Big Data from Space (BiDS'17) Research, Technology and Innovation</i>, 28-30 November 2017 Centre de Congrès Pierre Baudis, Toulouse, France</a></li> - <li><a href="/publications/hyspiri_workshop_poster.pdf">McGibbney, L. J., Brown, T. A., Clayton, H. A., Wang, X. (2017) "COAL AND OPEN-PIT SURFACE MINING IMPACTS ON AMERICAN LANDS (COAL)", <i>2017 HyspIRI Science and Applications Workshop</i>, 17-19 October 2017 California Institute of Technology Beckman Institute Auditorium 1200 E California Blvd Pasadena, CA</a></li> - <li><a href="/images/expo-poster.pdf">McGibbney, L. J., Brown, T. A., Clayton, H. A., Wang, X. (2017) "COAL AND OPEN-PIT MINING IMPACTS ON AMERICAN LANDS (COAL): A PYTHON LIBRARY FOR PROCESSING HYPERSPECTRAL IMAGERY", <i>Oregon State University Undergraduate Engineering Expo 2017</i>, 19 May 2017 Kelley Engineering Center, Johnson Hall, Oregon State University</a></li> + <li>todo</li> </ul> -<p>Contribute to the project through our <a class="external" href="https://github.com/capstone-coal";>GitHub Organization</a>, refer to the COAL <a class="external" href="https://github.com/capstone-coal/pycoal/wiki";>wiki</a> for development documentation, and contact the <a href="/team.html">team</a> to get involved.</p> +<p>Get involved and contribute to SDAP through our <a href="http://sdap.apache.org/team";>Community Hubs</a>. {% include footer.html %} http://git-wip-us.apache.org/repos/asf/incubator-sdap-website/blob/6e0454e8/source/resources.html ---------------------------------------------------------------------- diff --git a/source/resources.html b/source/resources.html index 982e00b..601ff41 100644 --- a/source/resources.html +++ b/source/resources.html @@ -5,40 +5,10 @@ <h1>Resources</h1> -<p>A collection of useful resources generated by or related to COAL</p> +<p>A collection of useful resources generated by or related to SDAP</p> <h2>Videos</h2> -<h3>NASA Studies Volcanos and Coral Reefs from 65,000 feet (HyspIRI Hawaii, Part 1)</h3> -<iframe width="560" height="315" src="https://www.youtube.com/embed/iKGeufqQqyc"; frameborder="0" allowfullscreen></iframe> -<p>This 6-minute, 8-second video shows how a NASA-led science team spent six weeks in January and February studying Hawaii's volcanoes and coral reefs using the Agency's ER-2 aircraft. The mission, called Hyperspectral InfraRed Imager (HyspIRI), focused on observing coral reef health and volcano emissions and eruptions. Flying at 65,000 feet (19,800 meters), above 95 percent of Earthâs atmosphere, the ER-2 can closely replicate the data a future satellite could collect. Data from this mission will help in developing a NASA satellite to study natural hazards and ecosystems. NASA's ER-2 aircraft are operated by NASA's Armstrong Flight Research Center and based at Hangar 703 in Palmdale, CA.</p> - -<h3>From the Ground Up: Building an Earth Science Satellite (HyspIRI Hawaii, Part 2)</h3> -<iframe width="560" height="315" src="https://www.youtube.com/embed/eAxZuFk7kPQ"; frameborder="0" allowfullscreen></iframe> -<p>In this 2-minute, 37-second video, the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) flies high aboard NASAâs ER-2, using over 224 sensors to identify, measure, and monitor natural features of the Earth's surface and atmosphere based on reflective light from the sun. The instrument was recently used for the Hyperspectral InfraRed Imager (HyspIRI) airborne preparatory mission, which focused on observing coral reef health and volcano emissions and eruptions around the Hawaiian Islands. Data from this mission will help develop a NASA satellite to study natural hazards and ecosystems. The Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) instrument is developed and managed by NASA's Jet Propulsion Laboratory, Pasadena, CA. NASAâs ER-2 aircraft is managed and based at NASAâs Armstrong Flight Research Center, Hangar 703 in Palmdale, CA.</p> - -<h3>From the Ground Up: Building an Earth Science Satellite (HyspIRI Hawaii, Part 3)</h3> -<iframe width="560" height="315" src="https://www.youtube.com/embed/Ts71279n8FE"; frameborder="0" allowfullscreen></iframe> -<p>Before a satellite is launched into orbit, scientists use instruments on NASA aircraft to calibrate, validate, and refine sensors that are part of current and future satellite payloads. In this 3-minute, 44-second video, data systems analyst Eric Fraim explains how an instrument called MASTER (MODIS Airborne ASTER Simulator) is being used to further develop Earth observing satellites. Flying on board NASAâs high-altitude ER-2, MASTER can detect thermal and visible spectral data as it scans air columns between the ground and the aircraft. The instrument was recently used for the Hyperspectral InfraRed Imager (HyspIRI) airborne preparatory mission, which focused on observing coral reef health and volcano emissions and eruptions around the Hawaiian Islands. HyspIRI is a proposed NASA satellite concept that will study natural hazards and ecosystems. The MODIS/ASTER (MASTER) airborne simulator is a joint development involving the Airborne Sensor Facility at the Ames Research Center, the Jet Propulsion Laboratory and the EROS Data Center. NASAâs ER-2 aircraft is managed and based at NASAâs Armstrong Flight Research Center, Hangar 703 in Palmdale, CA.</p> - -<h3>From the Ground Up: Building an Earth Science Satellite (HyspIRI Hawaii, Part 4)</h3> -<iframe width="560" height="315" src="https://www.youtube.com/embed/kljFd9Aai7c"; frameborder="0" allowfullscreen></iframe> -<p>In this 5-minute, 5-second video, noxious sulfur dioxide gas and other pollutants emitted from Kilauea Volcano on the Island of Hawai`i react with oxygen and atmospheric moisture to produce volcanic smog (vog) and acid rain. These forms of pollution are recurrent health issues for the citizens of Hawaii. Vog can aggravate preexisting respiratory ailments and create conditions for acid rain, which damages crops and can leach lead into household water supplies. Scientists from the U.S. Geological Survey's (USGS) Hawaiian Volcano Observatory (HVO) at the summit of Kilauea closely monitor the amount and composition of gas emissions from the volcano's ongoing eruption. In February 2017, NASA scientists joined efforts with USGS, collecting data on the ground and from NASAâs high-altitude ER-2 aircraft as part of the Hyperspectral InfraRed Imager (HyspIRI) airborne preparatory mission. Data from this mission will potentially help develop a NASA satellite to study natural hazards and e cosystems, including those affected by volcanic activity. The ER-2 aircraft is operated by NASA's Armstrong Flight Research Center and based at Hangar 703 in Palmdale, CA.</p> - -<h3>From the Ground Up: Building an Earth Science Satellite (HyspIRI Hawaii, Part 5)</h3> -<iframe width="560" height="315" src="https://www.youtube.com/embed/qdjsfKky4Dw"; frameborder="0" allowfullscreen></iframe> -<p>In this 5-minute, 52-second video, scientists from NASA and University of Hawaii, in partnership the U.S. Naval Research Laboratory, teamed up in February 2017 to study the health of coral reefs located around the Hawaiian Islands for the Hyperspectral InfraRed Imager (HyspIRI) airborne preparatory mission. Research divers and an autonomous kayak monitored coral color signatures from the ocean floor and surface, while NASAâs high-altitude ER-2 collected images of the same areas from a height of 70,000 ft. The data from these sources are being combined to better understand how coral reef ecosystems are responding to stressful conditions like warming ocean temperatures and water acidification. Data from this mission will potentially help develop a NASA satellite to study natural hazards and ecosystems all over the world. The ER-2 aircraft is operated by NASA's Armstrong Flight Research Center and based at Hangar 703 in Palmdale, CA.</p> - -<h3>Blowing Up Mountains: Destroying the Environment for Coal</h3> -<iframe width="560" height="315" src="https://www.youtube.com/embed/UvKe2LYy5pk"; frameborder="0" allowfullscreen></iframe> -<p>Massive corporations are blowing up mountains and creating environmental ruins in West Virginia. All this devastation, just to extract some coal. VICE News went to West Virginia to investigate mountain-top removal -- which a way of extracting coal from deposits under mountains. Instead of drilling into the mountain and sending men underground to take out the coal in the traditional way, they just take the whole top of a mountain off.</p> - -<h3>AVIRIS-Faces of Earth</h3> -<iframe width="560" height="315" src="https://www.youtube.com/embed/cg2B05ZCw18"; frameborder="0" allowfullscreen></iframe> -<p>Faces of Earth is a 4-hour high-definition television series about the ever-changing planet we live on. The only thing constant on Earth is change and Faces of Earth examines this phenomenon through the eyes of those that know it best - geoscientists. Explosive volcanic eruptions, earthquakes, floods and even human beings contribute to the constant changes on the Earth's surface. -Explore how through time the forces of nature have continuously remade Earth - giving it many distinct faces through history, and many new ones into the future. Faces of Earth is shot in stunning high-definition with extensive aerials, cutting edge animations, and engaging interviews. Discover the compelling story of how the world's titanic forces play a key role in just about every aspect of life. Geoscientists note that by understanding Earth's constantly shifting surface, we can prepare for changes such as volcanic eruptions, earthquakes and floods to perhaps make adjustments for what lies ahead. Watch as Faces of Earth peels back the layers of Earth's geologic system to uncover a world of mystery. -Uncover the deep mysteries of our planet with top geologists in Faces Of Earth. Using state-of-the-art computer animation and stunning photography, these four in-depth, compelling programs explore how these forces shape the Earth and how, in turn, the Earth has shaped human evolution.</p> - -<p>Contribute to the project through our <a class="external" href="https://github.com/capstone-coal";>GitHub Organization</a>, refer to the COAL <a class="external" href="https://github.com/capstone-coal/pycoal/wiki";>wiki</a> for development documentation, and contact the <a href="/team.html">team</a> to get involved.</p> +<p>Get involved and contribute to SDAP through our <a href="http://sdap.apache.org/team";>Community Hubs</a>. {% include footer.html %}
