| Sumario: | Numerous studies have been undertaken to understand shifts in ecological indicators over time, employing various valuation methods and comprehensive ecological health monitoring efforts. This study presents a cost-effective approach to evaluating carbon storage and sequestration in Kenya, utilizing crop type maps derived from remote sensing data and the InVEST (Integrated Valuation of Environmental Services and Tradeoffs) carbon model. By harnessing publicly available satellite data and open-source ecosystem models, our spatially explicit analysis addresses concerns regarding data scarcity, providing essential insights into carbon stock dynamics across diverse land use types. We employ a proximity-based scenario generator to project future scenarios, including the expansion of select crop types, offering valuable tools for assessing land use changes and their impacts on carbon stocks. Spatial-temporal assessments uncover the dynamic nature of carbon stocks in response to land use changes over time.
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