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Section: Ecology
Topic: Ecology, Applied biological sciences

Ten simple rules for working with high resolution remote sensing data

Mahood, Adam L.1, 2, 3  ; Joseph, Maxwell B.1 ; Spiers, Anna I.1, 4 ; Koontz, Michael J.1 ; Ilangakoon, Nayani1; Solvik, Kylen K.1, 2; Quarderer, Nathan1; McGlinchy, Joe1, 5; Scholl, Victoria M.1, 2 ; St. Denis, Lise A.1; Nagy, Chelsea1, 6; Braswell, Anna7, 8 ; Rossi, Matthew W.1; Herwehe, Lauren1, 2; Wasser, Leah1, 2 ; Cattau, Megan E.9 ; Iglesias, Virginia1; Yao, Fangfang1; Leyk, Stefan1, 2, 10; Balch, Jennifer K.1, 2, 6
1 Earth Lab, University of Colorado, Boulder - CO, USA
2 Department of Geography, University of Colorado, Boulder - CO, USA
3 Water Resources, USDA-ARS, Fort Collins, CO, USA
4 Department of Ecology and Evolutionary Biology, University of Colorado, Boulder - CO, USA
5 Hydrostat, Inc. - Washington, DC, USA
6 Environmental Data Science Innovation and Inclusion Lab, University of Colorado, Boulder - CO, USA
7 School of Forest, Fisheries, and Geomatic Sciences, Institute of Food and Agricultural Sciences, University of Florida, Gainesville - FL, USA
8 Florida Sea Grant, Institute of Food and Agricultural Sciences, University of Florida, Gainesville - FL, USA
9 Department of Human-Environment Systems, Boise State University, Boise - ID, USA
10 Institute of Behavioral Science, University of Colorado, Boulder - CO, USA

10.24072/pcjournal.223 - Peer Community Journal, Volume 3 (2023), article no. e4.

Get full text PDF Peer reviewed and recommended by PCI

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.

Published online:
DOI: 10.24072/pcjournal.223
Type: Opinion, perspective
Mahood, Adam L. 1, 2, 3; Joseph, Maxwell B. 1; Spiers, Anna I. 1, 4; Koontz, Michael J. 1; Ilangakoon, Nayani 1; Solvik, Kylen K. 1, 2; Quarderer, Nathan 1; McGlinchy, Joe 1, 5; Scholl, Victoria M. 1, 2; St. Denis, Lise A. 1; Nagy, Chelsea 1, 6; Braswell, Anna 7, 8; Rossi, Matthew W. 1; Herwehe, Lauren 1, 2; Wasser, Leah 1, 2; Cattau, Megan E. 9; Iglesias, Virginia 1; Yao, Fangfang 1; Leyk, Stefan 1, 2, 10; Balch, Jennifer K. 1, 2, 6

1 Earth Lab, University of Colorado, Boulder - CO, USA
2 Department of Geography, University of Colorado, Boulder - CO, USA
3 Water Resources, USDA-ARS, Fort Collins, CO, USA
4 Department of Ecology and Evolutionary Biology, University of Colorado, Boulder - CO, USA
5 Hydrostat, Inc. - Washington, DC, USA
6 Environmental Data Science Innovation and Inclusion Lab, University of Colorado, Boulder - CO, USA
7 School of Forest, Fisheries, and Geomatic Sciences, Institute of Food and Agricultural Sciences, University of Florida, Gainesville - FL, USA
8 Florida Sea Grant, Institute of Food and Agricultural Sciences, University of Florida, Gainesville - FL, USA
9 Department of Human-Environment Systems, Boise State University, Boise - ID, USA
10 Institute of Behavioral Science, University of Colorado, Boulder - CO, USA
License: CC-BY 4.0
Copyrights: The authors retain unrestricted copyrights and publishing rights 
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     author = {Mahood, Adam L. and Joseph, Maxwell B. and Spiers, Anna I. and Koontz, Michael J. and Ilangakoon, Nayani and Solvik, Kylen K. and Quarderer, Nathan and McGlinchy, Joe and Scholl, Victoria M. and St. Denis, Lise A. and Nagy, Chelsea and Braswell, Anna and Rossi, Matthew W. and Herwehe, Lauren and Wasser, Leah and Cattau, Megan E. and Iglesias, Virginia and Yao, Fangfang and Leyk, Stefan and Balch, Jennifer K.},
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Mahood, Adam L.; Joseph, Maxwell B.; Spiers, Anna I.; Koontz, Michael J.; Ilangakoon, Nayani; Solvik, Kylen K.; Quarderer, Nathan; McGlinchy, Joe; Scholl, Victoria M.; St. Denis, Lise A.; Nagy, Chelsea; Braswell, Anna; Rossi, Matthew W.; Herwehe, Lauren; Wasser, Leah; Cattau, Megan E.; Iglesias, Virginia; Yao, Fangfang; Leyk, Stefan; Balch, Jennifer K. Ten simple rules for working with high resolution remote sensing data. Peer Community Journal, Volume 3 (2023), article  no. e4. doi : 10.24072/pcjournal.223. https://peercommunityjournal.org/articles/10.24072/pcjournal.223/

Peer reviewed and recommended by PCI : 10.24072/pci.ecology.100102

Conflict of interest of the recommender and peer reviewers:
The recommender in charge of the evaluation of the article and the reviewers declared that they have no conflict of interest (as defined in the code of conduct of PCI) with the authors or with the content of the article.

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