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Full-Text Articles in Physical Sciences and Mathematics
Spatiotemporal Analysis Of Lake Water Quality Indicators On Small Lakes, Lake Bloomington And Evergreen Lake In Central Illinois, Using Satellite Remote Sensing, Gare Ambrose-Igho
Spatiotemporal Analysis Of Lake Water Quality Indicators On Small Lakes, Lake Bloomington And Evergreen Lake In Central Illinois, Using Satellite Remote Sensing, Gare Ambrose-Igho
Theses and Dissertations
This research explores the use of Sentinel-2 satellite to determine the spatiotemporal patterns of lake water quality indicators (e.g. chlorophyll a) in Lake Bloomington and Evergreen Lake. Lake water quality issues related to algal blooms is a serious problem in basins with abundant agricultural lands causing harmful effects to freshwater ecosystems such as pollution of beaches, taste and odor problems in drinking water, depletion of oxygen levels causing fish kills and the issue of water exceeding safe drinking water standards. Developing monitoring techniques using various water quality indicators of algal blooms is crucial. In this project, remote sensing and field …
Mountain Livelihoods In A Time Of Change: A Case Study Of Upper Mustang In Nepal, Sandesh Shrestha
Mountain Livelihoods In A Time Of Change: A Case Study Of Upper Mustang In Nepal, Sandesh Shrestha
Electronic Theses and Dissertations
A case study was conducted in a remote Himalayan village—Yara—in the Upper Mustang region of Nepal. The goal of this study was to understand and assess the livelihood strategies of local people in the village. The study focused on understanding the socio-economic and environmental driving factors of livelihood vulnerability, prevalent livelihood activities, emergent livelihood strategies, and resulting livelihood outcomes in the village. We used multiple data generation methods, which included both qualitative social science and quantitative biophysical components. For the qualitative component, we utilized multiple data generation methods including key informant interviews, semi-structured household interviews, group discussions, and field observations. …
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, …
Object-Based Supervised Machine Learning Regional-Scale Land-Cover Classification Using High Resolution Remotely Sensed Data, Christopher A. Ramezan
Object-Based Supervised Machine Learning Regional-Scale Land-Cover Classification Using High Resolution Remotely Sensed Data, Christopher A. Ramezan
Graduate Theses, Dissertations, and Problem Reports
High spatial resolution (HR) (1m – 5m) remotely sensed data in conjunction with supervised machine learning classification are commonly used to construct land-cover classifications. Despite the increasing availability of HR data, most studies investigating HR remotely sensed data and associated classification methods employ relatively small study areas. This work therefore drew on a 2,609 km2, regional-scale study in northeastern West Virginia, USA, to investigates a number of core aspects of HR land-cover supervised classification using machine learning. Issues explored include training sample selection, cross-validation parameter tuning, the choice of machine learning algorithm, training sample set size, and feature selection. A …
Remote Sensing Of Planetary Boundary Layer Height And Particulate Matter 2.5 In New York State Mesonet Network, Bhupal Shrestha
Remote Sensing Of Planetary Boundary Layer Height And Particulate Matter 2.5 In New York State Mesonet Network, Bhupal Shrestha
Legacy Theses & Dissertations (2009 - 2024)
Abstract: