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Full-Text Articles in Physical Sciences and Mathematics

Remote Sensing Of High Latitude Rivers: Approaches, Insights, And Future Ramifications, Merritt E. Harlan Jun 2022

Remote Sensing Of High Latitude Rivers: Approaches, Insights, And Future Ramifications, Merritt E. Harlan

Doctoral Dissertations

High latitude rivers across the pan-Arctic domain are changing due to changes in climate and positive Arctic feedback loops. Understanding and contextualizing these changes is challenging due to a lack of data and methods for estimating and modeling river discharge, and mapping rivers. Remote sensing, and the availability of satellite imagery can provide ways to overcome these challenges. Through combining various forms of fieldwork, modeling, deep learning, and remote sensing, we contribute methodologies and knowledge to three key challenges associated with better understanding high latitude rivers. In the first chapter, we combine field data that can be rapidly deployed with …


Models And Machine Learning Techniques For Improving The Planning And Operation Of Electricity Systems In Developing Regions, Santiago Correa Cardona Jun 2022

Models And Machine Learning Techniques For Improving The Planning And Operation Of Electricity Systems In Developing Regions, Santiago Correa Cardona

Doctoral Dissertations

The enormous innovation in computational intelligence has disrupted the traditional ways we solve the main problems of our society and allowed us to make more data-informed decisions. Energy systems and the ways we deliver electricity are not exceptions to this trend: cheap and pervasive sensing systems and new communication technologies have enabled the collection of large amounts of data that are being used to monitor and predict in real-time the behavior of this infrastructure. Bringing intelligence to the power grid creates many opportunities to integrate new renewable energy sources more efficiently, facilitate grid planning and expansion, improve reliability, optimize electricity …


Magnitude And Rates Of Agriculturally-Induced Soil Erosion In The Midwestern United States, Evan Thaler Oct 2021

Magnitude And Rates Of Agriculturally-Induced Soil Erosion In The Midwestern United States, Evan Thaler

Doctoral Dissertations

Fertile, agricultural productive soils are essential for producing food for a growing global population. Soil erosion diminishes soil quality, threatens food security by decreasing crop productivity, and degrades ecosystem health through increased rates of sedimentation and runoff. Despite decades and thousands of soil erosion studies, robust scalable methods for estimating the magnitude and rates of soil erosion have been elusive. In this dissertation, we develop a remote sensing method for quantifying the areal extent of historical loss in an agricultural landscape and provide a method for estimating the total thickness of soil loss and rates of historical soil loss in …


Estimation Of Cdom In Inland Waters Via Water Bio-Optical Properties Using A Remote Sensing Approach, Jiwei Li Jul 2018

Estimation Of Cdom In Inland Waters Via Water Bio-Optical Properties Using A Remote Sensing Approach, Jiwei Li

Doctoral Dissertations

Monitoring of Colored dissolved organic matter (CDOM) in inland waters provides important information for tracing carbon cycle at the land-water interface and studying aquatic ecosystem. Remote sensing estimation of CDOM in the inland waters offers an alternative approach to field samplings in examining CDOM spatial-temporal dynamics. However, CDOM retrieval is a challenge due to the lack of algorithm for resolving bottom effect in shallow inland waters. Moreover, an effective approach based on multi-spectral, high spatial resolution and global coverage satellite images is in urgent need. To resolve these challenges, shallow water bio-optical properties (SBOP) algorithm was developed to overcome bottom …