Framing the concept of satellite remote sensing essential biodiversity variables: challenges and future directions
By Nathalie Pettorelli, Martin Wegmann, Andrew K. Skidmore, S. Mücher, Terence P. Dawson, Miguel Fernández, R. Lucas, Michael E. Schaepman, Tiejun Wang, Brian O'Connor and 33 more. 2016
308 citations recorded by the source corpus.
Although satellite‐based variables have for long been expected to be key components to a unified and global biodiversity monitoring strategy, a definitive and agreed list of these variables still remains elusive. The growth of interest in biodiversity variables observable from space has been partly underpinned by the development of the essential biodiversity variable (EBV) framework by the Group on Earth Observations – Biodiversity Observation Network, which itself was guided by the process of identifying essential climate variables. This contribution aims to advance the development of a global biodiversity monitoring strategy by updating the previously published definition of EBV, providing a definition of satellite remote sensing (SRS) EBVs and introducing a set of principles that are believed to be necessary if ecologists and space agencies are to agree on a list of EBVs that can be routinely monitored from space. Progress toward the identification of SRS‐EBVs will require a clear understanding of what makes a biodiversity variable essential, as well as agreement on who the users of the SRS‐EBVs are. Technological and algorithmic developments are rapidly expanding the set of opportunities for SRS in monitoring biodiversity, and so the list of SRS‐EBVs is likely to evolve over time. This means that a clear and common platform for data providers, ecologists, environmental managers, policy makers and remote sensing experts to interact and share ideas needs to be identified to support long‐term coordinated actions.
Subfields: Ecological Modeling, Ecology, Global and Planetary Change
View Paper: https://www.semanticscholar.org/paper/a841ac4cf57b3baf0058f84711f14a5ef44deeab
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In Ecological Modeling
- Zhe Zhu
- Jonathan M. Jeschke
- Thomas R. Loveland
- Curtis E. Woodcock
- S. Kumschick
- S. Bacher
- T. Blackburn
- M. Wulder
In Ecology
- Zhe Zhu
- Curtis E. Woodcock
- Petr Pyšek
- David P. Roy
- M. Wulder
- Joanne C. White
- Thomas R. Loveland
- Jonathan M. Jeschke
In Global and Planetary Change
- Zhe Zhu
- Curtis E. Woodcock
- David P. Roy
- Thomas R. Loveland
- M. Wulder
- Joanne C. White
- Warren B. Cohen
- Robert E. Kennedy
Citations in the corpus
- A vision for global monitoring of biological invasions (2017, background): “Countries may capitalize on citizen science (Crall et al., 2010), as well as emerging online and remote technologies in data capture (O'Connor et al., 2015; Pettorelli et al., 2016; Skidmore et al., 2015) to improve records of invasions (Table 2).”
- Biodiversity redistribution under climate change: Impacts on ecosystems and human well-being (2017, unknown): “A global, robust biodiversity monitoring system that successfully integrates field and remote-sensing data could substantially improve our ability to manage the changes to come while potentially driving faster mitigation measures (100).”
- Current status of Landsat program, science, and applications (2019, background): “Biodiversity Variables for CBD (Pereira et al., 2013; Pettorelli et al., 2016) and Progress Indicators for the UNCCD (Sommer et al.”
- Land cover 2.0 (2018, background): “At the same time, there is increasing inclusion of these data (and derived products), especially Landsat, in national and international activities and programs (e.g., GCOS 2016; Gong et al. 2013; Hansen et al. 2013; White et al. 2014; Pettorelli et al. 2016).”