CEOS Ecosystem Extent Task Team White Paper V1.0. Space-based Earth Observation and Ecosystem Extent: Exploring Opportunities
Notice bibliographique
Résumé
Preface: White Paper Purpose and Context Although CEOS has had a Biodiversity Activity for some time the biodiversity area has not yet been a major CEOS focus. Recently, however, the importance of biodiversity to society and the need for improved monitoring have become much clearer. The 2019 Global Assessment Report on Biodiversity and Ecosystem Services developed by the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES, analogous to the IPCC) provided a daunting assessment on the state of biodiversity and its implications for society. Understanding and appreciation of the interconnections between biodiversity and climate have also advanced, as has the role of nature-based solutions for mitigation and adaptation. A key recent activity has been the update to the UN Convention on Biological Diversity’s (CBD) decadal planning, resulting in the Kunming-Montreal Global Biodiversity Framework (GBF) and its Monitoring Framework. The GBF was developed over several years and agreed to by the CBD’s nearly 200 Parties in December 2022. It laid out four goals for 2050 and 23 Targets for 2030, many of which are of direct or indirect relevance to Earth observation (EO) from space. These recent developments and the visibility they provided set the stage for CEOS to start exploring ways to increase its engagement with biodiversity; this led to a proposal to create the Ecosystem Extent Task Team (EETT), approved at CEOS Plenary in 2022. Also significant is that in 2018 the UN CBD’s Executive Secretary sent a letter to CEOS suggesting the two organizations explore ways to strengthen their collaboration. The CEOS Chair responded in agreement and acknowledged that much work remains for EO’s potential for biodiversity monitoring to be fully realized. Many things have changed since that early exchange and, while in retrospect it may have been ahead of its time, the letter exchange laid important groundwork for future collaboration and the start of this Ecosystem Extent Task Team. This brief history provides the context for this white paper, which is called out in the EETT’s Terms of Reference: Develop a white paper that will provide an integrated international perspective on how space-based Earth observations can be used to support ecosystem mapping and monitoring with a focus on ecosystem extent. Keeping in mind these Terms of Reference, the increasing awareness of the importance of biodiversity, and the potential for enhancing the role that EO can play in ecosystem mapping and monitoring, this white paper focuses on two audiences: CEOS Principals that represent their agency to CEOS, and the biodiversity community with a particular focus on the CBD and their Parties as well as the UN System of Environmental-Economic Accounting (UN SEEA). The Introduction summarizes the broad context within which the work of the EETT sits, explains why ecosystem extent is so important, and discusses the key policy anchors that lay behind it. Section 2 discusses some of the conceptual basis upon which ecosystem extent maps are created. Section 3 then turns to the role of space-based Earth Observation, how it is used, types of sensors, and related information. Recommendations to CEOS on how it might enhance existing ecosystem extent mapping and monitoring activities are then suggested in Section 4. -- Co-leads Gary Geller, Shaun Levick, Sandra Luque, Roger Sayre
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,002 |
| Méta-épidémiologie (sens large) | 0,002 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,004 |
| Science ouverte | 0,004 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,017 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».