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Satellite imagery has been used to provide global and regional estimates of forest cover. Despite increased availability and accessibility of satellite data, approaches for detecting forest degradation have been limited. We produce a very-high resolution 3-meter (m) land cover dataset and develop a normalized index, the Bare Ground Index (BGI), to detect and map exposed bare ground within forests at 90 m resolution in central India. Tree cover and bare ground was identified from Planet Labs Very High-Resolution satellite data using a Random Forest classifier, resulting in a thematic land cover map with 83.00% overall accuracy (95% confidence interval: 61.25%-90.29%). The BGI is a ratio of bare ground to tree cover and was derived by aggregating the land cover. Results from field data indicate that the BGI serves as a proxy for intensity of forest use although open areas occur naturally. The BGI is an indicator of forest health and a baseline to monitor future changes to a tropical dry forest landscape at an unprecedented spatial scale., (© 2023. Springer Nature Limited.)

Early retirement of coal-fired power is essential for remaining in line with the 2°C target set in the Paris Agreement. Plant age plays the major role in designing retirement pathways, however, this overlooks the economic and health costs associated with coal-fired power. We introduce multi-dimensional retirement schedules that account for age, operating cost, and air pollution hazards. Results show that regional retirement pathways vary substantially with different weighting schemes. Schedules based on age would retire capacity mostly in the US and EU, whereas those based on cost or air pollution would shift the majority of near-term retirements to China and India, respectively. Our approach emphasizes that a "one-size-fits-all" strategy is ineffective in addressing global phase-out pathways. It provides the opportunity for devising region-specific pathways that are sound to the local context. Our results involve emerging economies and highlight incentives for early retirement that surpass climate change mitigation and address regional priorities., Competing Interests: The authors declare no competing interests., (© 2023 The Author(s).)