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Full-Text Articles in Physical Sciences and Mathematics
Employing Earth Observations And Artificial Intelligence To Address Key Global Environmental Challenges In Service Of The Sdgs, Wenzhao Li
Computational and Data Sciences (PhD) Dissertations
Earth Observation (EO) data provides the capability to integrate data from multiple sources and helps to produce more relevant, frequent, and accurate information about complex processes. EO, empowered by methodologies from Artificial Intelligence (AI), supports various aspects of the UN’s Sustainable Development Goals (SDGs). This dissertation presents author’s major studies using EO to fill in knowledge gaps and develop methodologies and cloud-based applications in selected SDGs, including SDG 6 (Clean Water and Sanitation), SDG 11 (Sustainable Cities and Communities), SDG 14 (Life below Water) and SDG 15 (Life on Land). For SDG 6, the study focuses on spatiotemporal water recharge …
Utilization Of Various Methods And A Landsat Ndvi/Google Earth Engine Product For Classifying Irrigated Land Cover, Andrew Nemecek
Utilization Of Various Methods And A Landsat Ndvi/Google Earth Engine Product For Classifying Irrigated Land Cover, Andrew Nemecek
Graduate Student Theses, Dissertations, & Professional Papers
Methods for classifying irrigated land cover are often complex and not quickly reproducible. Further, moderate resolution time-series datasets have been consistently utilized to produce irrigated land cover products over the past decade, and the body of irrigation classification literature contains no examples of subclassification of irrigated land cover by irrigation method. Creation of geospatial irrigated land cover products with higher resolution datasets could improve reliability, and subclassification of irrigation by method could provide better information for hydrologists and climatologists attempting to model the role of irrigation in the surface-ground water cycle and the water-energy balance. This study summarizes a simple, …