To observe, characterise, identify, understand, predict... This is the approach that researchers follow every day. This sequence is tirelessly repeated as the biological model, the targeted ecosystem and/or the experimental, environmental or modelling conditions change. This way of proceeding is essential in a world of rapid change in response to the frenetic pace of intensifying pressures and forcings that impact ecosystems. To better understand our Earth and the dynamics of its components, to map ecosystems and diversity patterns, and to identify changes, humanity had to demonstrate inventiveness and defy gravity.
Gustave Hermite and Georges Besançon were the first to launch aloft balloons equipped with radio transmitters, making possible the transmission of meteorological data to observers in real time . The development of aviation in the middle of the 20th century constituted a real leap forward for the frequent acquisition of aerial observations, leading to a significant improvement in weather forecasting models. The need for systematic collection of data as holistic as possible – an essential component for the observation of complex biological systems - has resulted in pushing the limits of technological prowess.
The conquest of space and the concurrent development of satellite observations has largely contributed to the collection of a considerable mass of data, placing our Earth under the "macroscope" - a concept introduced to ecology in the early 1970s by Howard T. Odum (see ), and therefore allowing researchers to move towards a better understanding of ecological systems, deterministic and stochastic patterns … with the ultimate goal of improving management actions [2,3]. Satellite observations have been carried out for nearly five decades now  and have greatly contributed to a better qualitative and quantitative understanding of the functioning of our planet, its diversity, its climate... and to a better anticipation of possible future changes (e.g., [4-7]).
This access to rich and complex sources of information, for which both spatial and temporal resolutions are increasingly fine, results in the implementation of increasingly complex computation-based analyses, in order to meet the need for a better understanding of ecological mechanisms and processes, and their possible changes. Steven Levitt stated that "Data is one of the most powerful mechanisms for telling stories". This is so true … Data should not be used as a guide to thinking and a critical judgment at each stage of the data exploitation process should not be neglected.
This is what Mahood et al.  rightly remind us in their article "Ten simple rules for working with high-resolution remote sensing data" in which they provide the fundamentals to consider when working with data of this nature, a still underutilized resource in several topics, such as conservation biology . In this unconventional article, presented in a pedagogical way, the authors remind different generations of readers how satellite data should be handled and processed. The authors aim to make the readers aware of the most frequent pitfalls encouraging them to use data adapted to their original question, the most suitable tools/methods/procedures, to avoid methodological overkill, and to ensure both ethical use of data and transparency in the research process. While access to high-resolution data is increasingly easy thanks to the implementation of dedicated platforms , and because of the development of easy-to-use processing software and pipelines, it is important to take the time to recall some of the essential rules and guidelines for managing them, from new users with little or no experience who will find in this article the recommendations, resources and advice necessary to start exploiting remote sensing data, to more experienced researchers.
 Jeannet P, Philipona R, and Richner H (2016). 8 Swiss upper-air balloon soundings since 1902. In: Willemse S, Furger M (2016) From weather observations to atmospheric and climate sciences in Switzerland: Celebrating 100 years of the Swiss Society for Meteorology. vdf Hochschulverlag AG.
 Odum HT (2007) Environment, Power, and Society for the Twenty-First Century: The Hierarchy of Energy. Columbia University Press.
 Boyle SA, Kennedy CM, Torres J, Colman K, Pérez-Estigarribia PE, Sancha NU de la (2014) High-Resolution Satellite Imagery Is an Important yet Underutilized Resource in Conservation Biology. PLOS ONE, 9, e86908. https://doi.org/10.1371/journal.pone.0086908
 Le Traon P-Y, Antoine D, Bentamy A, Bonekamp H, Breivik LA, Chapron B, Corlett G, Dibarboure G, DiGiacomo P, Donlon C, Faugère Y, Font J, Girard-Ardhuin F, Gohin F, Johannessen JA, Kamachi M, Lagerloef G, Lambin J, Larnicol G, Le Borgne P, Leuliette E, Lindstrom E, Martin MJ, Maturi E, Miller L, Mingsen L, Morrow R, Reul N, Rio MH, Roquet H, Santoleri R, Wilkin J (2015) Use of satellite observations for operational oceanography: recent achievements and future prospects. Journal of Operational Oceanography, 8, s12–s27. https://doi.org/10.1080/1755876X.2015.1022050
 Turner W, Rondinini C, Pettorelli N, Mora B, Leidner AK, Szantoi Z, Buchanan G, Dech S, Dwyer J, Herold M, Koh LP, Leimgruber P, Taubenboeck H, Wegmann M, Wikelski M, Woodcock C (2015) Free and open-access satellite data are key to biodiversity conservation. Biological Conservation, 182, 173–176. https://doi.org/10.1016/j.biocon.2014.11.048
 Melet A, Teatini P, Le Cozannet G, Jamet C, Conversi A, Benveniste J, Almar R (2020) Earth Observations for Monitoring Marine Coastal Hazards and Their Drivers. Surveys in Geophysics, 41, 1489–1534. https://doi.org/10.1007/s10712-020-09594-5
 Zhao Q, Yu L, Du Z, Peng D, Hao P, Zhang Y, Gong P (2022) An Overview of the Applications of Earth Observation Satellite Data: Impacts and Future Trends. Remote Sensing, 14, 1863. https://doi.org/10.3390/rs14081863
 Mahood AL, Joseph MB, Spiers A, Koontz MJ, Ilangakoon N, Solvik K, Quarderer N, McGlinchy J, Scholl V, Denis LS, Nagy C, Braswell A, Rossi MW, Herwehe L, Wasser L, Cattau ME, Iglesias V, Yao F, Leyk S, Balch J (2021) Ten simple rules for working with high resolution remote sensing data. OSFpreprints, ver. 6 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.31219/osf.io/kehqz
DOI or URL of the preprint: https://doi.org/10.31219/osf.io/kehqz
Version of the preprint: 3
Dear Dr. Mahood
The revised version of your manuscript entitled ‘Ten simple rules for working with high resolution remote sensing data’ has now been reviewed.
I would like to thank you both reviewers for their hard work and insights, and the authors for the careful consideration of the previous suggestions. As you will see from the comments, the revised version of your manuscript was positively perceived by both referees, one of whom was fully satisfied with the changes made. The second referee is also convinced by your modifications, and only a few new suggestions have been made.
The format of the paper and its suitability for PCI is discussed, however. After a careful reading of the new version, I confirm that –and although the format is not classical when compared to other articles published by PCI– it has a very good chance of finding its audience and that it may serve as a basis for thoughts on how using remote sensing data. This article could thus be mentioned as a prerequisite to be read by students, but not only; researchers who has to handle this type of data would also be interested. Please find below other comments to consider, in addition to the suggestions made by referee 2.
From my reading, I recommend that the authors pay attention to the few typos still present in the paper, as well as to the punctuation.
1) The authors mention several data sources. As the paper is oriented towards a pedagogical approach, a summary table of some of the datasets or data sources, with the access links, could be helpful.
2) The use of bulleted lists could help to better identify author’s guidance, for example at the end of the paragraph "Know the question".
3) I would suggest to be more specific in several parts of the manuscript. For example, on the concept of fitness (see “Understand the data”): some sentences are too vague: how to ensure data quality? how to evaluate the adequacy between data and the question? While the advice is important, it may also be necessary to provide ways to meet this expectation if tools exist.
4) I do not know if the authors can do such an exercise, but I would suggest to add a table –or, even better, a figure to highlight the link between spatial resolutions and phenomena depending on the spatial scale to consider in a given context, while displaying possible overlaps (such as proposed in Schlünzen et al; doi: 10.1016/j.jweia.2011.01.009).
5) In the same idea, i.e., to guide the readers in the best possible way, I would suggest to make a list of software for people who would like to start processing and/or visualizing remote sensing data; or to provide books, references, tutorials to readers to help them get started, e.g., resources identify by the authors of which they appreciate the quality, for both the construction of the analyses and/or the clarity of the approaches. The remark also applies for the section "Show your work".
6) Section 9 “Do no harm” is sometimes unclear, especially the part dedicated to ethics. Broadly speaking, I would suggest to clarify some of the sections of the manuscript. For some sections, the first sentences are describing some concepts, gaps, limitations, issues… and examples are shown after, often in a second paragraph. To clarify the key messages, and especially because of the targeted audience of the paper, I would suggest to integrate the examples directly when the issues are raised.
7) Section 9 “Do no harm”. If applicable, I would suggest to add directly in the paper the corresponding url to redirect the readers toward the guidelines (Section 9). This will allow the readers to better find the information for adopting good practices
Please revise the paper according to these two reports and upload a point-by-point response, including a description of any additional materials, and a detailed rebuttal of requested revisions that you disagreed with.
DOI or URL of the preprint: https://doi.org/10.31219/osf.io/kehqz
Version of the preprint: 2
Dear Dr. Joseph
Your manuscript entitled ‘Ten simple rules for working with high resolution remote sensing data’ has now been reviewed.
After approaching more than 20 reviewers to review your article (hence the time delay), two have now returned reviews. Thus, I am happy to thank you for your patience, but also draw your attention to the comments made by the reviewers that invite resubmission of the manuscript after consideration of their suggestions. More specifically, it is strongly recommended to refactor the paper to make it more suitable for a peer reviewed journal, including a more extensive literature review. At that point, I will re-engage with the reviewers to ensure that they are happy with the revisions and make a decision regarding the manuscript's future journey with PCI.
Thank you to both reviewers for their hard work and insights.