[ES_JOBS_NET] remote sensing postdoc position ORISE

[Mona Papes]

  Postdoctoral position available through Oak Ridge Institute for 
Science and Education. Full position description:

*Utilizing Sentinel 3 Satellites to Detect and Monitor Vegetation 
Disturbances in Post-MODIS /ForWarn/,**and Developing A Network 
Representativeness Plan to Statistically Direct Growth of the 
Experimental Forest Network*

This is a combined position, comprising effort toward two different 
research programs outlined below.The position is aimed at the 
postdoctoral level, but existing prior experience and ability with 
linux, shell script programming, and GIS is more important than the 
terminal degree that is held.The participant’s effort will be split two 
thirds on */ForWarn/* Sentinel 3 and one third on EFRN.This opportunity 
is within the Eastern Forest Environmental Threat Assessment Center 
(EFETAC), a dynamic research unit of the USFS Southern Research 
Station.EFETAC scientists engage in diverse ecological research over 
large regional areas, including: evaluating the effects and consequences 
of multiple interacting stresses (e.g., climate change, invasive 
species, wildland fire) on forest conditions; increasing knowledge of 
the risks, uncertainties, and/or benefits of multiple stresses on 
ecological conditions and socioeconomic values; and providing 
science-based decision support tools for policy formulation and land 
management.

The initial appointment is for 1.5 years, contingent on the availability 
of funds.The annual stipend will be $7,075/month, and a travel allowance 
and medical, prescription, dental and vision coverage are also provided.

To apply: https://www.zintellect.com/Opportunity/Details/USDA-USFS-2022-0128

Please use the link above for additional fellowship details and to 
apply. This position is an Oak Ridge Institute for Science and Education 
(ORISE) fellowship, administered by ORAU through an interagency 
agreement with USDA Forest Service.For project-specific inquiries 
contact William Hargrove, Research Ecologist, USDA Forest Service: 
william.w.hargrove at usda.gov.

Deadline: April 1, 2022.Applications will be reviewed on a rolling basis 
as received. Start date May 2022, or as soon as a suitable candidate is 
found.

Location: Asheville, North Carolina; teleworking may be possible

*Research description*

*/ForWarn/**II *(*https://forwarn.forestthreats.org* 
<https://forwarn.forestthreats.org>)**has produced over a dozen map 
products showing forest disturbances across North America every 8 days 
for the last 10 years <https://forwarn.forestthreats.org/fcav2>, but the 
two MODIS satellites on which it depends will be moved to lower orbits 
in 2022, and destroyed one year later.Two newer Sentinel 3 satellites 
now provide an alternative data stream to continue */ForWarn/*. 
Sentinel-3’s S3A and S3B satellites have a revisit time of less than 2 
days, with a resolution of around 300m.

*/ForWarn/*produces “departure” maps that show deviations, both negative 
and positive, from “normal” forest conditions.*/ForWarn /*produces a 
suite of disturbance map products every 8 days which differ primarily in 
the historical depth that is used for this departure comparison.Forest 
managers gain important disturbance insights by looking across 
*/ForWarn/* products using this changing historical perspective.

Interpretation of forest disturbances and their impact requires 
comparison with a lengthy historical archive going back 10 years or 
more, but Sentinel 3 satellites were only launched about three years 
ago.This need for historical perspective to detect and interpret 
disturbances also necessitated developing a backwards-compatibility with 
our existing library of stored MODIS NDVI maps that will allow their 
continued use as “normal” baselines to produce a full multi-year 
historical suite of new */ForWarn/* departure products into the future.

The participant will help to develop and evaluate new Sentinel 3-based 
*/ForWarn/* disturbance maps, in comparison to their MODIS-based 
counterparts, as well as developing and testing entirely new */ForWarn/* 
products.The participant will interact in a team environment with 
research collaborators and with forest management professionals to 
design, construct, execute and communicate complex programming tools and 
applications that are likely to include quantitative analysis (e.g., 
satellite data and/or maps of environmental characteristics) and to 
produce landscape maps of ecological results.Research may include 
downloading and integrating spatial datasets, such as remotely sensed 
data and environmental data, as well as integrating data-driven and 
expert-driven information.

The performance of any network of experimental sites depends on how well 
the experimental conditions at those sites reflect or represent the 
conditions occurring throughout the greater area that the network is 
supposed to represent.Many experimental networks, including the 
Experimental Forest and Rangeland Network (EFRN), have added sites in an 
undirected, /ad hoc/ way, through a process of simple organic growth.But 
a new, quantitative ability to statistically analyze and map network 
representativeness and constituency shows locations whose conditions are 
well-represented by existing EFs, as well as poorly represented 
locations where additional, new EFs need to be added into the EFRN.

Such quantitative network analysis provides the ability of network 
analysis to actively guide the addition of new EFs into the network, in 
order to achieve the greatest increases in EFR network 
representativeness.Existing State and National Forests are the most 
likely candidates for additions to the EFRN.Statistical network analysis 
can direct the recruiting and addition of only the best new Forests: the 
ones which will provide the greatest new increment of added network 
representativeness to the EFRN.Instead of blind growth, an ordered list 
of the most-preferred Forests to be added will result in planned growth 
of the EFRN, and the maximized network representativeness that results 
will provide the greatest advantage per Forest that is added to the network.

The participant will help to provide an optimized design guide for the 
EFR network, at two scales: SRS southeastern subset, and national.This 
guide will be a sorted list, in preference order, of all existing state 
and national forest candidate sites that might represent the most likely 
candidates for adding to the existing EFRN.Calculated quantitatively 
against the existing, current constellation of EFRN sites, the list will 
allow guided rather than blind growth, and will maximize the 
representativeness and experimental utility of the EFRN as it grows in 
the future.

Please distribute this announcement widely to any interested potential 
applicants.

-- 
Monica Papes, PhD
Associate Professor
University of Tennessee
Department of Ecology and Evolutionary Biology
mail: 569 Dabney
office: 443 Hesler
Knoxville, TN 37996
tel: 865-974-2821
http://monapapes.wix.com/biodivmatters
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