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Articles 1 - 5 of 5
Full-Text Articles in Spatial Science
Uncertain Regional Urbanism In Venezuela. Government, Infrastructure And Environment, Fabio Capra-Ribeiro
Uncertain Regional Urbanism In Venezuela. Government, Infrastructure And Environment, Fabio Capra-Ribeiro
Faculty Publications
Uncertain Regional Urbanism in Venezuela explores the changes cities face when they become metropolises, forming expanding regions which create both potential and problems within settlements. To do so, it focuses on three metropolitan areas located in Venezuela’s Center-North region: Caracas, Maracay and Valencia, designated as "Camava."
Considering three core topics, government and territorial administration, infrastructure and environment, as well as looking at the reciprocal impact, this book describes and analyzes the determinant variables that characterize the phenomenon of regional urbanization in this area and in the wider Global South. It includes documentary research, semi-structured interviews and Delphi methodology, involving a …
Using Spatial Analysis And Machine Learning Techniques To Develop A Comprehensive Highway-Rail Grade Crossing Consolidation Model, Samira Soleimani
Using Spatial Analysis And Machine Learning Techniques To Develop A Comprehensive Highway-Rail Grade Crossing Consolidation Model, Samira Soleimani
LSU Doctoral Dissertations
The safety of highway-railroad grade crossings (HRGC) is still an issue in the United States of America (USA). The grade crossing is where a railroad crosses a road at the same level without any over or underpass. To improve the safety of crossings, the crossings’ condition should be explored from several aspects such as engineering design (speed limit, warning signs, etc.), road condition (number of lanes, surface markings, etc.), rail design (the type of track, ballast, etc.), temporal variables (weather, visibility, time of day, lightning, etc.), social variables (population, race, etc.), and last but not least, spatial variables (the type …
Automatic Features Extraction From Time Series Of Passive Microwave Images For Snowmelt Detection Using Deep-Learning – A Bidirectional Long-Short Term Memory Autoencoder (Bi-Lstm-Ae) Approach., Bienvenu Sedin Massamba
Automatic Features Extraction From Time Series Of Passive Microwave Images For Snowmelt Detection Using Deep-Learning – A Bidirectional Long-Short Term Memory Autoencoder (Bi-Lstm-Ae) Approach., Bienvenu Sedin Massamba
LSU Master's Theses
The Antarctic surface snowmelt is prone to the polar climate and is common in its coastal regions. With about 90 percent of the planet's glaciers, if all of the Antarctica glaciers melted, sea levels will rise about 58 meters around the planet. The development of an effective automated ice-sheet snowmelt monitoring system is therefore crucial.
Microwave remote sensing instruments, on the one hand, are very sensitive to snowmelt and can see day and night through clouds, allowing us to distinguish melting from dry snow and to better understand when, where, and for how long melting has taken place. On the …
An Atmospheric And Spatiotemporal Examination Of Lightning-Initiated Terrestrial Gamma-Ray Flashes Detected By The Fermi Satellite And Tetra Ii, Deirdre Colleen Smith
An Atmospheric And Spatiotemporal Examination Of Lightning-Initiated Terrestrial Gamma-Ray Flashes Detected By The Fermi Satellite And Tetra Ii, Deirdre Colleen Smith
LSU Doctoral Dissertations
Terrestrial Gamma-ray Flashes (TGFs) are sub-millisecond bursts of the highest naturally occurring light-energy found within Earth’s atmosphere. TGFs are associated with the electric fields produced in thunderstorms and are geolocated by coincident sferics from lightning strokes. Though billions of lightning strokes occur globally each year, fewer than 1,000 TGFs are detected via satellite and ground-based sensors and only a small fraction are geolocated via sferics.
To date, few studies have focused on individual thunderstorms and climates that produce TGFs. This dissertation examines TGFs from two differing data samples: 1) NASA's Fermi Gamma-Ray Burst Monitor (2013-2018) and 2) The TGF and …
Spatial And Topological Analysis Of Urban Land Cover Structure In New Orleans Using Multispectral Aerial Image And Lidar Data, Shuxian Liu
LSU Master's Theses
Urban land use and land cover (LULC) mapping has been one of the major applications in remote sensing of the urban environment. Land cover refers to the biophysical materials at the surface of the earth (i.e. grass, trees, soils, concrete, water), while land use indicates the socio-economic function of the land (i.e., residential, industrial, commercial land uses). This study addresses the technical issue of how to computationally infer urban land use types based on the urban land cover structures from remote sensing data. In this research, a multispectral aerial image and high-resolution LiDAR topographic data have been integrated to investigate …