IEEE Geoscience and Remote Sensing Magazine - December 2015 - 20

supported the USGS developing software
for Earth science application of remote
sensing data. He is currently a principal
software engineer for SGT, Inc. His work
focuses on research in computer science,
supercomputing, and Earth science data
visualization technologies.
Jason Werpy obtained B.S. degrees in

Computer Science and Electrical Engineering from South Dakota State University
(SDSU), Brookings, SD, in 1993, and also
there in 2013 a MS in Engineering with
emphasis in Computer Science. He has
over 20 years of experience in directing
software development. He is employed by SGT, Inc., and his current focus is developing environments for Earth data scientists to
select, organize, and analyze Earth science data.
Aaron Friesz has a 2008 B.S. in Biology
and 2012 M.S. in Geography from SDSU
in Brookings, SD. He is a Data Scientist
for the LP DAAC in Sioux Falls, SD, and
is employed by Innovate!, supporting the
USGS EROS Center. His current focus is
on researching novel uses and methods for
LP DACC remote sensing data.
Kevin Impecoven obtained a B.S. in
Computer Science from SDSU in Brookings, SD, in 1994. He has over 20 years of
experience as a software professional building and scaling highly-available distributed
web systems. He is employed by SGT, Inc.,
and his current focus is development of
middleware services to enable interactive web access to remote
sensing data archives.
Robert J. Quenzer obtained a B.S. in

Computer Science from SDSU in Brookings, SD, in 1995. He works for SGT, Inc.,
as a software developer supporting the
USGS EROS Center, and has 20 years of
experience in web application development
and project management. His current focus
is web client application interaction with middleware services to
extract information from remote sensing data archives.
Thomas Maiersperger received B.S. and
M.S. degrees in Geography from Oregon
State University in 1992 and 1997, respectively. He has conducted terrestrial remote
sensing research and applications development at the U.S. Forest Service (USFS)
Pacific Northwest Research Station (Cor-

vallis, OR), the USFS Remote Sensing Applications Center (Salt
Lake City, UT), and the USGS EROS Center, Sioux Falls, SD.
Over the last decade, he has worked as a member of the Landsat Data Continuity Mission (LDCM) and the LP DAAC. His
LDCM work focused on developing processing capabilities and assessment methods for higher-level Landsat products (e.g., surface
reflectance). His is employed by SGT, Inc., and his current LP
DAAC work is focused on developing new capabilities to foster
the understanding, access, and use of remote sensing data across
a large and varied user community.
David J. Meyer received B.A. and M.S.
degrees in Physics from Indiana State University in 1979 and 1984, respectively. He
obtained a Ph.D in Atmospheric and Space
Science from the University of Michigan in
1994. He has over 30 years of experience
with Earth observation, image processing
and instrument design (multispectral, thermal, spectroscopic, and
synthetic aperture radar imaging. He is employed by the USGS as
the EOS Project Scientist for the LP DAAC, and his current focus
is geo-informatics and collaborative science frameworks.

RefeRences
[1] (2014). Celery: Distributed task queue. Celery. [Online]. Available: http://www.celeryproject.org/
[2] B. Davis and B. Maddox, "Real time visualization teachniques,"
in Manual of Geographic Information Systems, M. Madden,
Bethesda, MD: American Association of Photogrammetry and
Remote Sensing, ch. 44, pp. 871-883
[3] (2013, Oct.). The JSON data interchange format. ecma. Standard EDCM-404. [Online]. Available: http://www.ecma-international.org/publications/files/ECMA-ST/ECMA-404.pdf
[4] J. Gallagher, N. Potter, T. Sgouros, S. Hankin, and G. Flierl.
(2007, Oct.). The data access prototcol-DAP 2.0. Retrieved
from ESE-RFC-004.1.1: [Online]. Available: https://earthdata.nasa.gov/sites/default/files/field/document/ESE-RFC004v1.1.pdf
[5] (2014). mongoDB. mongDB. [Online]. Available: http://www.
mongodb.org/
[6] (2014). OPeNDAP. OPeNDAP. Retrieved from Open-source
Project for a Network Data Access Protocol. [Online]. Available: http://opendap.org
[7] (2014). IO tools (Text, CSV, HDF5, ...). Pandas. Retrieved from
pandas 0.15.2 documentation. [Online]. Available: http://
pandas.pydata.org/pandas-docs/stable/io.html
[8] (2014). Python data analysis library. Pandas, Retrieved from
pandas: [Online]. Available: http://pandas.pydata.org/
[9] D. R. Steinwand, and B. N. Davis, Meta Data Mining in Earth
Remote Sensing Data Archives, Abstract IN21B-3706. San Francisco, CA: American Geophysical Union, Dec. 2014
[10] (2013). The NetCDF markup language (NcML). UCAR, [Online]. Available: http://www.unidata.ucar.edu/software/thredds/current/netcdf-java/ncml/
[11] J. Werpy and C. Torbert, "Augmenting Basic Web Data Services
with Middleware Services to Facilitate Usability and Interoperability, Abstract number IN43D-3721, San Francisco, CA, American Geophysical Union, Dec. 2014

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ieee Geoscience and remote sensing magazine

december 2015

http://www.celeryproject.org/ http://www.ecma-inter http://www.national.org/publications/files/ECMA-ST/ECMA-404.pdf https://earth http://data.nasa.gov/sites/default/files/field/document/ESE-RFC http://www http://www.mongodb.org/ http://www.opendap.org http://http:// http://pandas.pydata.org/pandas-docs/stable/io.html http://pandas.pydata.org/ http://www.unidata.ucar.edu/software/th

Table of Contents for the Digital Edition of IEEE Geoscience and Remote Sensing Magazine - December 2015