Accurate and comprehensive measurements of a range of sustainable development outcomes are fundamental inputs into both research and policy. We synthesize the growing literature that uses satellite imagery to understand these outcomes, with a focus on approaches that combine imagery with machine learning. We quantify the paucity of ground data on key human-related outcomes and the growing abundance and improving resolution (spatial, temporal, and spectral) of satellite imagery. We then review recent machine learning approaches to model-building in the context of scarce and noisy training data, highlighting how this noise often leads to incorrect assessment of model performance. We quantify recent model performance across multiple sustainable development domains, discuss research and policy applications, explore constraints to future progress, and highlight research directions for the field.
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Loss and damage from climate change and implicit assumptions of sustainable development
Abstract Loss and damage from climate change, recognized as a unique research and policy domain through the Warsaw International Mechanism (WIM) in 2013, has drawn increasing attention among climate scientists and policy makers. Labelled by some as the “third pillar” of the international climate regime—along with mitigation and adaptation—it has been suggested that loss and damage has the potential to catalyze important synergies with other international agendas, particularly sustainable development. However, the specific approaches to sustainable development that inform loss and damage research and how these approaches influence research outcomes and policy recommendations remain largely unexplored. We offer a systematic analysis of the assumptions of sustainable development that underpins loss and damage scholarship through a comprehensive review of peer-reviewed research on loss and damage. We demonstrate that the use of specific metrics, decision criteria, and policy prescriptions by loss and damage researchers and practitioners implies an unwitting adherence to different underlying theories of sustainable development, which in turn impact how loss and damage is conceptualized and applied. In addition to research and policy implications, our review suggests that assumptions about the aims of sustainable development determine how loss and damage is conceptualized, measured, and governed, and the human development approach currently represents the most advanced perspective on sustainable development and thus loss and damage. This review supports sustainable development as a coherent, comprehensive, and integrative framework for guiding further conceptual and empirical development of loss and damage scholarship.
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- Award ID(s):
- 1633831
- PAR ID:
- 10278894
- Date Published:
- Journal Name:
- Climatic Change
- Volume:
- 164
- Issue:
- 1-2
- ISSN:
- 0165-0009
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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