Description
Concerns, such as global warming, greenhouse gas emissions, and changes in hydrological regimes, have been raised in response to the global ecosystem changes caused by humans. Understanding the ecosystem functions is crucial for assisting stakeholders in formulating viable plans to address the issues for a healthier planet. However, a systematic evaluation of recent environmental changes and current ecosystem status, focusing on terrestrial ecosystem carbon-water trade-off, in the Lower Mekong Basin (LMB) is lacking. This dissertation involves: (1) examining the long-term spatiotemporal patterns of ecosystem conditions in response to gains and losses of the forest; (2) evaluating the current consumptive water use variation across all biome and land use types with remotely sensed evapotranspiration (ET) products; (3) analyzing the trade-off between terrestrial carbon and water stress condition during the photosynthesis process in response to different climatic/ecosystem conditions, and (4) developing a spatial optimization model to effectively determine possible reforestation/afforestation options considering the balance between water conservation and carbon fluxes. These studies were conducted with many recently developed algorithms and satellite imagery. This dissertation makes significant contributions and expands the knowledge of the variation in water consumption and carbon assimilation within the ecosystem when different conditions are present. In addition, the spatial optimization model was applied to the entire region to formulate possible reforestation plans under different water-carbon tradeoff scenarios for the first time. The findings and results of this research can be used to provide constructive suggestions to policymakers, managers, planners, government officials, and any other stakeholders in LMB to formulate policies and guidelines for the environmentally responsible and sustainable development of LMB.
Details
Title
- Evaluating the Ecosystem of the Lower Mekong Basin: Multi-scale Multi-sensor Geospatial Analytics
Contributors
- Li, Yubin (Author)
- Myint, Soe (Thesis advisor)
- Tong, Daoqin (Thesis advisor)
- Muenich, Rebecca (Committee member)
- Schaffer-Smith, Danica (Committee member)
- Arizona State University (Publisher)
Date Created
The date the item was original created (prior to any relationship with the ASU Digital Repositories.)
2023
Subjects
Resource Type
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Note
- Partial requirement for: Ph.D., Arizona State University, 2023
- Field of study: Geography