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Home Publications PE&RS Submissions Call for Papers: Understanding Uncertainty in Remotely Sensed Vegetation Data Products

PE&RS Submissions

Call for Papers: Understanding Uncertainty in Remotely Sensed Vegetation Data Products 

Deadline for submission of manuscripts: November 1, 2014
Tentative publication date: September 1, 2015

Guest Editors:
Dr. Leah Wasser, Remote Sensing Ecologist / Senior Science Educator
National Ecological Observatory Network, Boulder, CO
Email: lwasser@neoninc.org Tel.: (720) 746-4917

Dr. Tanya Ramond, Systems Engineer - Airborne Observation Platform
National Ecological Observatory Network, Boulder, CO
Email: tramond@neoninc.org Tel.:(720) 746-4862

Dr. Jan van Aardt, Associate Professor
Rochester Institute of Technology - Chester F. Carlson Center for Imaging Science
Digital Imaging and Remote Sensing Group
Email: vanaardt@cis.rit.edu Tel.: (585) 475-4229

Mr. Jason Stoker, Physical Scientist
USGS Earth Resources Observation and Science (EROS)
Email: Jstoker@usgs.gov, Tel.: (605) 594-2579

Dr. Tom Kampe, Director - Remote Sensing
National Ecological Observatory Network, Boulder, CO 80305, USA 
Email: tkampe@neoninc.org, Tel.: (720) 836.2414

Accurately quantifying spatial patterns of vegetation structure, health, and composition is integral to our understanding of local and global ecological change and to monitoring diverse ecosystems. In this context, remote sensing methods are essential for measuring multiple biophysical properties over broad geographical regions. However, despite the recognized need to use remote sensing methods, they bring with them unique challenges.  These include incorporation of a wide range of both active and passive remote sensor types; non-uniform collection and processing methods; and varying in situ validation methods. If not well-characterized, these factors can reduce the accuracy associated with remote sensing derived estimates of local on-the-ground measurements and processes across larger regions.  Further, they produce variability in data product and analysis outcomes that is not well-understood. Understanding this variability is integral to missions such as ICESAT-II, BIOMASS, Sentinel, HyspIRI, EnMAP, NEON, and Australia‚Äôs TERN and 3DEP, that will be providing widely available remote sensing data products to support scientific study and quantification of vegetation state and dynamics.

This special issue of Photogrammetric Engineering & Remote Sensing focuses on quantifying uncertainty in remotely sensed estimates of vegetation biophysical characteristics. Paper topics could include uncertainty associated with instrument specification / configuration / calibration, data collection, processing and analysis, or identifying best analysis methods which reduce this uncertainty in resulting vegetation data products.

We especially encourage submissions that

  • focus on spectral or structural (active or passive sensor) modalities, but use both in a fusion approach to reduce uncertainty;
  • address the scalability of remote sensing estimates; and
  • are aligned with planned science community biophysical products, such as those found in the large scope ecological observatories.

All submissions will be peer-reviewed in line with PE&RS policy. Because of page limits, not all submissions recommended for acceptance by the review panel may be included in the special issue. Under this circumstance, the guest editors will select the most relevant papers for inclusion in the special issue. Papers that are reviewed favorably, but will not fit within the Special Issue, can be revised and submitted for review as a new paper to the PE&RS Editor-in-Chief for possible publication in a future regular issue of PE&RS.  Authors must prepare manuscripts according to the PE&RS Instructions to Authors, published in each issue of PE&RS and also available on the ASPRS web site at Instructions for Authors.

Important Dates:
Manuscripts Due:             11/01/14
Notification to Authors:    02/01/15
Final Papers Due:             03/01/15
Publication:                       09/01/15

PLEASE SUBMIT YOUR MANUSCRIPT BY EMAIL DIRECTLY TO LEAD GUEST EDITOR:

Dr. Leah Wasser
National Ecological Observatory Network, Boulder, CO
Email: lwasser@neoninc.org
Tel.: (720) 746-4917

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