Announcement: https://tinyurl.com/y9cathdd
PDF: https://tinyurl.com/yadkwhgr

Graduate Research Assistantship (PhD) Opportunity at Northern Arizona 
University in Flagstaff, AZ

Data Fusion for Forest Planning and Implementation: Ecological Restoration, 
Remote Sensing, and Data Analytics

Are you interested in a PhD program that will provide you an opportunity to 
work in the frequent fire forests of the American Southwest and influence 
ecological restoration practices? These forests are in dire need of 
restoration, mainly due to a century of fire exclusion and subsequent, 
undesirable changes in forest structure and function. For example, the 
largest collaborative forest restoration project in the US, the Four Forest 
Restoration Initiative (4FRI), has a goal of implementing restoration 
treatments on approximately 1M ha of U.S. Forest Service lands in northern 
Arizona. Fundamental to these efforts are precise data on the amount and 
distribution of available resources, knowledge of how resources may change 
over time, and hazard assessments (e.g., wildfire potential); all of which 
require costly and resource intensive, spatially explicit data. As a result, 
managers are using more remote sensing data products (e.g., LiDAR), coupled 
with advanced forest inventory and data analysis techniques, to quantify 
existing conditions and support broad-scale analysis of forest ecosystems.

A PhD graduate research assistantship is available in the School of Forestry 
at Northern Arizona University, Flagstaff, AZ, focused on the development 
and assessment of data fusion techniques that will allow managers to better 
capitalize on major advancements in remote sensing to utilize more accurate 
data and enhance precision of landscape-scale analysis (e.g., >100,000 
acres) project areas. Working alongside the Ecological Restoration 
Institute, the USDA Forest Service, USDI Fish and Wildlife Service, The 
Nature Conservancy, and Campbell Global; the successful applicant will focus 
on developing and statistically validating an open source big data, remote 
sensing, and inventory data fusion platform. This platform will provide 
enhanced forest structural and compositional information in support of 
forest resource decision-making.

The selected student will:

Assess and statistically validate algorithms for identifying individual 
trees and species from remote sensing data of Southwestern forests using new 
and/or existing stemmapped, area and tree based sample data.
Using these algorithms and data, design and implement a platform that 
integrates multiple data sources (data fusion) that are typically too large 
to analyze using traditional methods (big data) to provide detailed forest 
resource information at the tree-,stand-, and landscape levels.
Assess the accuracy, precision, and statistical properties of forest 
resource estimates such as bias, consistency, error, spatial uncertainty, 
and use these to provide improved information for land management decision 
making.
Apply the platform to Southwestern landscape-scale case studies to; quantify 
existing conditions, assess low-value biomass product availability, 
facilitate watershed treatment implementation, and monitor forest 
restoration treatments.
The position includes a full stipend, tuition waiver, health benefits and 
field support for 4 years.

Applications from quantitatively minded individuals with a practical 
approach to solving complex problems are welcome. Experience processing 
large remote sensing and inventory datasets using C++, R, and/or Python is 
preferred.

Qualifications:

MasterÂ’s degree in forestry, geography, ecology, computer science, or 
related fields.
Demonstrable research experience, collaboration abilities, and English 
(written and oral) communication skills.
Competitive GRE scores (top 40th percentile).
 Information about NAU’s graduate program, including eligibility 
requirements, is available at http://nau.edu/CEFNS/Forestry/Degrees/.

NAU's formal application deadline is for Fall 2018 is Feb 15 2018 and 
preferred start date is Summer 2018. However, interested candidates are 
encouraged to contact with Dr. Sanchez Meador as soon as possible using the 
information provided below or submit your CV, written statement of interest, 
and copies of unofficial degree transcripts to initiate a dialog via e-
mail.  andrew.sanchezmea...@nau.edu.

Contact Information:

Dr. Andrew Sánchez Meador 
School of Forestry 
Northern Arizona University
Flagstaff, AZ 86011-5018, USA 
andrew.sanchezmea...@nau.edu 
928-523-3448

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