PCI Ecology

403

Title

Ten simple rules for working with high resolution remote sensing datause asterix (*) to get italics

Authors

Adam L. Mahood, Maxwell Benjamin Joseph, Anna Spiers, Michael J. Koontz, Nayani Ilangakoon, Kylen Solvik, Nathan Quarderer, Joe McGlinchy, Victoria Scholl, Lise St. Denis, Chelsea Nagy, Anna Braswell, Matthew W. Rossi, Lauren Herwehe, Leah wasser, Megan Elizabeth Cattau, Virginia Iglesias, Fangfang Yao, Stefan Leyk, Jennifer Balch Please use the format "First name initials family name" as in "Marie S. Curie, Niels H. D. Bohr, Albert Einstein, John R. R. Tolkien, Donna T. Strickland"

Year

2022

Picture

Abstract

<p>Researchers in Earth and environmental science can extract incredible value from high-resolution (sub-meter, sub-hourly or hyper-spectral) remote sensing data, but these data can be difficult to use. Correct, appropriate and competent use of such data requires skills from remote sensing and the data sciences that are rarely taught together. In practice, many researchers teach themselves how to use high-resolution remote sensing data with ad hoc trial and error processes, often resulting in wasted effort and resources. In order to implement a consistent strategy, we outline ten rules with examples from Earth and environmental science to help academic researchers and professionals in industry work more effectively and competently with high-resolution data.</p>

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Keywords

Remote sensing

Methods that require specific expertise (optional)

NonePlease indicate the methods that may require specialised expertise during the peer review process (use a comma to separate various required expertises).

Thematic fields

Biogeography, Landscape ecology, Macroecology, Spatial ecology, Metacommunities & Metapopulations, Terrestrial ecology

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Submission date

2021-10-19 21:41:22

Recommender

Eric Goberville

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