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     {\href{mailto:\citeemail}{Pete~\citename}}, %Change only 1st name of 1st author
		{\href{mailto:kmerry@warnell.uga.edu} {Krista Merry}}
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\small\it{\href{http://www.uga.edu/}{University of Georgia, Georgia, USA}} \\
%$^2$\small\it{{ETH-Zürich, Brüggliäcker 37, 8050 Zürich, Switzerland.}}
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 {{
A Brief Overview of the 9${}^{th}$ Southern Forestry and Natural Resources GIS Conference
}} %need double {{for \\ e.g.: {{Title \\ Subtitle}}
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Symposium Proceedings, SOFOR GIS, Geographic Information Systems, Spatial Information Technologies
}
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{
This short summary represents the introduction and overview of a special
section of two papers that arose from the 2013 (9${}^{th}$) Southern Forestry and
Natural Resources GIS Conference (SOFOR GIS). The conference held its ninth meeting
in Athens, Georgia (USA) on December 9-10, 2013.
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\section{Introduction}

For the last 20 years, the\textit{ Southern Forestry and Natural Resources
GIS Conference} (SOFOR GIS) has been offered by the University of Georgia as a venue
for practitioners, researchers, and others to learn about new developments and applications
of GIS technology. The conference is now held biannually. It began in 1996 as the \textit{Southern
Forestry GIS Conference}, but was re-branded in 2004 to reflect the broader range
of participants and audience for which it serves (Bettinger and Hubbard 2010). The
conference proceedings have historically been peer-edited, yet in 2010 a small set
of selected papers were also peer-reviewed and simultaneously published in \textit{Mathematical
and Computational Forestry and Natural-Resource Sciences}.



 The 9${}^{th}$ SOFOR GIS Conference, as with prior conferences in this
series, contained a diverse program of presentations that spanned a number of natural
resource management fields. Dr. Songlin Fei organized a set of presentations on spatial
analysis of invasive species issues of the southern United States, in conjunction
with a National Science Foundation program. In combination with this, Sandy Liebhold
of the U.S. Forest Service provided the introductory keynote address of the conference,
in which he discussed patterns of insect and disease infestation across the country.
Concurrent sessions during the first morning of the conference included eight other
presentations on the subject of invasive species, along with presentations that addressed
forest inventory and mapping developments and other new technologies. These latter
groups included presentations on unmanned aircraft, transportation analytics, and
the use of Pictometry, among others. The afternoon sessions of the first day of the
conference centered on ecological applications of GIS, image classification, biomass
estimation, and again, unmanned aircrafts. Twelve presentations comprised the ecological
applications sessions. These ranged from the development of spatial prediction models
for fuel accumulation and breeding bird richness to estimation of the vulnerability
of land to sea level rise. Image classification presentations centered on the use
of new methods for allocating land areas to land classes based on spectral reflectance
values, to the detection of specific landscape features through high-resolution imagery.
Bioenergy and unmanned aircrafts are emerging areas of interest that are relevant
in the GIS discipline; and therefore several presentations provided overviews of
new developments in these areas.



 The second day of the conference consisted of concurrent sessions on GPS
and LiDAR technologies, and forest health issues. The GPS and LiDAR session included
presentations on recent results of GPS accuracy studies, and advances in the use
of LiDAR for extracting forest information of value to land managers. The forest
health session included, among other topics, southern pine beetle (\textit{Dendroctonus
frontalis}) spread and hardwood mortality trends.



 The closing session included presentations on new developments from ESRI,
a leading developer of GIS technology, forest change detection, visualization technology,
and database development. Dr. Marguerite Madden presented the concluding keynote
presentation, which consisted of an overview of remote sensing technology and its
value to natural resource management.



 The planning committee for the 2013 (9${}^{th}$) Southern Forestry and
Natural Resources GIS Conference consisted of the following people:

\begin{itemize}

\item Pete Bettinger, Conference Chair (University of Georgia)

\item Krista Merry, Proceedings Chair (University of Georgia)

\item Tyler Brown (National Wild Turkey Federation)

\item Chris Cieszewski (University of Georgia)

\item Joseph Fan (Mississippi State University)

\item Songlin Fei (Purdue University)

\item Bill Hubbard (South.~Regional Extension Forestry)

\item I-Kuai Hung (Stephen F. Austin State University)

\item Tommy Jordan (University of Georgia)

\item Tripp Lowe (University of Georgia)

\item Qingmin Meng (Mississippi State University)

\item Jacek Siry (University of Georgia)

\end{itemize}

 The SOFOR GIS conferences have served several purposes over the years,
from providing a venue where GIS users, developers, researchers, and practitioners
can intermingle and share ideas to providing a source of new information for foresters,
loggers, and other professionals seeking continuing education experiences. The proceedings
(Merry et al. 2014) are peer-edited, and can be found at the Internet site http://soforgis.net.
These materials have served to inform the public of advances in GIS technology, research
and application, and have incrementally advanced the sciences associated with GIS.

\vspace{.1in}
\section{Contents of the Special Section}

 This special section of \textit{Mathematical and Computational Forestry
\& Natural-Resource Sciences} (MCFNS) contains two papers that were presented at
the 9${}^{th}$ SOFOR GIS conference. In one of the papers, Roger Lowe and Chris Cieszewski
delve into the issue of determining the appropriate nearest-neighbor value for \textit{kNN} approaches
to broad-scale landscape inventory development. \textit{kNN} approaches are essentially
image classification processes that are applied to remotely sensed imagery. The goal
with these approaches is to not only classify an image, but to also assign a tree
list to the individual units (grid cells, pixels) within the image. This then facilitates
estimates of volume, basal area, and other forest characteristics of interest to
managers and policy makers. Lowe and Cieszewski (2014) describe the issues one may
encounter when a process optimizes the number of nearest neighbors (\textit{k}) by
minimizing a fitness statistic, and the possible effects on the range of forest characteristic
estimates and the ability to emulate other broad-scale inventory estimates developed
from continuous forest inventories.

 The other paper included in this special section describes the processes
that were employed by Williams et al. (2014) to create the spatial information that
described the behavior of a large and devastating 1894 wildfire situated in Wisconsin.
Historical maps and first-hand accounts from witnesses were used to create the information
necessary to calibrate and run FARSITE (Finney 2004). Wind speed and direction, and
fuel model spread rates were adjusted in a way that the outcomes of the spatial analysis
(flame front location and time of impact) matched eyewitness statements during the
period of most intense fire activity. Increasing the rate of spread within the FARSITE
model allowed it to account for spot fires, atmospheric interaction, and merging
fires that were thought to play role in the development of this natural disaster.

\vspace{.1in}
\section*{Acknowledgements}
The University of Georgia Center for Continuing Education once again hosted the conference.
Sponsors included ESRI, F4 Tech, American Forest Management, Drahola Technologies,
Inc., the James W. Sewall Company, and the E2 (Land Use Planning, Organization, and
Management) working group of the Society of American Foresters. In addition, people
from these organizations helped develop and organize the conference: Southern Regional
Extension Forester's Office, Mississippi State University, Stephen F. Austin State
University, Purdue University, and the National Wild Turkey Federation.

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\vspace{.1in}
\begin{thebibliography}{9}

\bibitem[a(2012)]{a}
Bettinger, P., and W.G. Hubbard. 2010. The 2009 Southern Forestry and Natural
Resources GIS Conference. Mathematical and Computational Forestry and Natural-Resources
Sciences. 1: 135--137.

\bibitem[a(2012)]{a}
 Finney, M.A. 2004. FARSITE: fire area simulator - model development and
evaluation. U.S. Department of Agriculture, Forest Service, Rocky Mountain Research
Station, Ogden UT. Research Paper RMRS-RP-4 Revised. 47 p.

\bibitem[a(2012)]{a}
 Lowe, R.C., and C.J. Cieszewski. 2014. Multi-source K-nearest neighbor,
mean balanced forest inventory of Georgia.  Mathematical and Computational Forestry
\& Natural-Resource Sciences (MCFNS). 6(2)10--24.  Available online
at: \href{http://mcfns.com/index.php/Journal/article/view/MCFNS_184/MCFNS-184} {http://mcfns.com/.../MCFNS\_184/MCFNS-184}

\bibitem[a(2012)]{a}
 Merry, K., P. Bettinger, T. Brown, C.J. Cieszewski, I-K. Hung, and Q. Meng.
2014. Proceedings of the 9${}^{th}$ Southern Forestry and Natural Resources GIS Conference.
Warnell School of Forestry and Natural Resources, University of Georgia, Athens,
GA. 165 p.

\vspace{5pt}
\bibitem[a(2012)]{a}
 Williams, T.M.,  B.J. Williams, and B. Song. 2014.  Creation of GIS data
requirements for FARSITE modeling of an historic wildfire.  Mathematical and Computational
Forestry \& Natural-Resource Sciences (MCFNS). 6(2)25--33.  Available
online at: \href{http://mcfns.com/index.php/Journal/article/view/MCFNS_183/MCFNS-183} {http://mcfns.com/.../MCFNS\_183/MCFNS-183}

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\end{thebibliography}

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