Physical Sciences and Mathematics Commons^™

Development Of An Operational Satellite-Based Flood Monitoring Model For Tanzania, Andrew Kimati

Tanzania Journal of Engineering and Technology (TJET)

Timely information during water related disasters is of utmost importance for flood preparedness and risk reduction. However, the conventional ground-based photographic monitoring of flooded areas is an expensive and time-consuming exercise. Satellite remote sensing is a quick and affordable approach that can be used for concurrent floods detection at different scales. This is important as it facilitates timely information for emergency response to disaster management departments, even in scarcely instrumented catchments. This study presents a novel approach for flood tracking using satellite image remote sensing science to map flood affected areas immediately after occurrence of rainfall events. An open-source water …

Utilizing Remote Sensing Technology To Relocate Lubra Village And Visualize Flood Damages, Ronan Wallace

Mathematics, Statistics, and Computer Science Honors Projects

As weather patterns change worldwide, isolated communities impacted by climate change go unnoticed and we need community and habitat-conscious solutions. In Himalayan Mustang, Nepal, indigenous Lubra village faces threats of increasing flash flooding. After every flood, residual concrete-like sediment hardens across the riverbed, causing the riverbed elevation to rise. As elevation increases, sediment encroaches on Lubra’s agricultural fields and homes, magnifying flood vulnerability. In the last monsoon season alone, the village witnessed floods swallowing several fields and damaging two homes. One solution considers relocating the village to a new location entirely. However, relocation poses a challenging task, as eight centuries …

Wildfire Modeling With Data Assimilation, Andrew Johnston

Theses and Dissertations

Wildfire modeling is a complex, computationally costly endeavor, but with droughts worsening and fires burning across the western United States, obtaining accurate wildfire predictions is more important than ever. In this paper, we present a novel approach to wildfire modeling using data assimiliation. We model wildfire spread with a modification of the partial differential equation model described by Mandel et al. in their 2008 paper. Specifically, we replace some constant parameter values with geospatial functions of fuel type. We combine deep learning and remote sensing to obtain real-time data for the model and employ the Nelder-Mead method to recover optimal …

Geologic Mapping Of The Sparta 7.5-Minute Quadrangle In Northern Mississippi Via Remote Sensing, Traditional Geologic Survey, And Applied Geospatial Information Systems Methods, Rayford Dean Parnell

Theses and Dissertations

Traditional geologic mapping involves substantial time and labor in the field as geologic contacts are manually examined and interpreted. The processes of mapping geologic contacts can be condensed into a quicker and less laborious process using advances in remote sensing and GIS (geospatial information systems), including increased resolution and computerized data management and interpretation. Application of these advances reduces the costs and time of geologic mapping. The Sparta 7.5-minute quadrangle provides a mostly unaltered view of regional Paleocene and Upper Cretaceous geology due to its rural locale, lack of development, and stream topography. Recently LiDAR (Light Detection And Ranging) survey …

Oam-Based Wavelets In A High Speed Optical Probing System For Measuring The Angular Decomposition Of The Environment, Justin Free

All Theses

This thesis presents the theoretical development of orbital angular momentum (OAM) based wavelets for the analysis of localized OAM information in space. An optical probing system for generating and detecting these wavelets is demonstrated; individual wavelets can scan the environment in 10µs or less. The probing system was applied to a three-dimensional atmospheric turbulence distribution to obtain a continuous wavelet transform of the angular information of the turbulent propagation path about a fixed radius. An entire continuous wavelet transform was measured in 3.8ms; the measurements are much faster than the turbulence and give insight into the short time scale of …

Hydrothermal Alteration Targeting And Geophysical Mineral Exploration Of Eureka And Sylvanite Mining Districts, Southwest New Mexico, Kenneth Singh

Open Access Theses & Dissertations

As part of the southwestern North American porphyry copper province, mining of natural resources in New Mexico has historically played a crucial role in economic development for over 150 years including this project area in the Little Hatchet Mountains. The northern half of the Little Hatchet Mountains lies in Grant County and includes the Eureka Mining District (EMD) whereas the southern half is in Hidalgo County and includes the Sylvanite Mining District (SMD), 38 miles southeast of Lordsburg. The EMD, a copper and silver-lead mining district from 1880-1961, had a total estimated production from the Laramide veins of 2.9 million …

The Possibilities Of Explicit Striga (Striga Asiatica) Risk Monitoring Using Phenometric, Edaphic, And Climatic Variables, Demonstrated For Malawi And Zambia, Emily Kimathi, Bester Tawona Mudereri, Elfatih M. Abdel-Rahman, Saliou Niassy, Henri E.Z. Tonnang, Tobias Landmann

All Peer-Reviewed Publications

Food insecurity continues to affect more than two-thirds of the population in sub‐Saharan Africa (SSA), particularly those depending on rain-fed agriculture. Striga, a parasitic weed, has caused yield losses of cereal crops, immensely affecting smallholder farmers in SSA. Although earlier studies have established that Striga is a constraint to crop production, there is little information on the spatial extent of spread and infestation severity of the weed in some SSA countries like Malawi and Zambia. This study aimed to use remotely sensed vegetation phenological (n = 11), climatic (n = 3), and soil (n = 4) variables to develop a …

Fitting Solar Panel Brdf Parameters To Out-Of-Plane Empirical Data, Michael R. Gross

Theses and Dissertations

The bidirectional reflectance distribution function (BRDF) describes material reflectance by describing how incident irradiance reflects into all possible scatter angles as a function of incident angle. However, a solar panel has unique features that are not featured in any of these previously known models. A previous project at the Air Force Institute of Technology (AFIT) created a novel microfacet-like BRDF to model a solar panel with a prominent diffractive feature present which had not been previously modeled. This BRDF was coded into MATLAB for modeling purposes and C++ to test its speed with a MEX function call. A previous thesis …

Computer-Based Forage Management Tools: Historical, Current, And Future Applications, David B. Hannaway, C. Daly, D. F. Chapman, B. B. Baker, A. S. Cooper

IGC Proceedings (1977-2023)

Forage management has been an important human activity since the beginning of civilization. By comparison, the personal computer has been available only in the immediate past. The software developed to deal with the complexity of climate, soil, plant, animal, and socioeconomic factors has seen huge changes in a few decades. Mainframe computers facilitated numerical calculations for exploring relationships among dozens of variables. Personal computers opened the door for more individual scientist creativity and routine communication. Web-based communication globalised the option for multidisciplinary teams to tackle problems. Forage-related computer applications abound, allowing farmers, ranchers, and others to more effectively manage the …

Assessing Turgor Loss Point In Bottomland Hardwood Trees Using Leaf Spectroscopy, Alexandra M. Eisley

LSU Master's Theses

Climate change is expected to radically alter our planet’s forests, with higher frequencies of drought- and flood-induced mortality events posing a challenge for forest managers and biologists. Research into the factors underlying plant tolerance to environmental stressors is therefore gaining popularity for incorporation into projective and earth system modeling using remote sensing measures. Leaf turgor loss point (TLP) is a key trait associated with drought tolerance among plants and is defined as the water potential at which leaf turgor pressure reaches zero, causing wilting. Here, I investigated patterns of TLP across the landscape and its role as an indicator of …

Transformers In Remote Sensing: A Survey, Abdulaziz Amer Aleissaee, Amandeep Kumar, Rao Anwer, Salman Khan, Hisham Cholakkal, Gui-Song Xia, Fahad Shahbaz Khan

Computer Vision Faculty Publications

Deep learning-based algorithms have seen a massive popularity in different areas of remote sensing image analysis over the past decade. Recently, transformers-based architectures, originally introduced in natural language processing, have pervaded computer vision field where the self-attention mechanism has been utilized as a replacement to the popular convolution operator for capturing long-range dependencies. Inspired by recent advances in computer vision, remote sensing community has also witnessed an increased exploration of vision transformers for a diverse set of tasks. Although a number of surveys have focused on transformers in computer vision in general, to the best of our knowledge we are …

Characterization Of Smoke Particles Toward Improved Remote Sensing Retrievals And Chemical Transport Modeling, Chenchong Zhang

McKelvey School of Engineering Graduate Student Theses & Dissertations

Wildfires increase in extent, intensity, and frequency across the globe over the recent decades. The uncontrolled fires trigger cascading effects on local ecosystems and the fire emissions pose a higher risk to air quality and climate. Wildfire emissions contain a variety of trace gases and particulate matters. The particle-phase emissions, especially those light-absorbing species including black carbon (BC) and brown carbon (BrC), significantly affect the regional and global climate by modulating the radiative transfer phenomena in the atmosphere. A great discrepancy still exists between model- and observation-based estimates of aerosol-radiation interactions (ARI). The discrepancy is partially attributed to the mischaracterizations …

Quantifying Aboveground Biomass In A Tropical Forest Using A Lidar Waveform Weighted Allometric Model, Alejandro Rojas

Theses and Dissertations

Our knowledge of the distribution and amount of terrestrial above ground biomass (AGB) has increased using lidar technology. Recent advancements in satellite lidar has enabled global mapping of forest biomass and structure. However, there are large biases in satellite lidar estimates which impacts our understanding of carbon dynamics, particularly in tropical forests.

Ni-Meister et al. (2022) developed a lidar full waveform weighted height-based allometric model which produced very good results in temperate deciduous/conifer forest in the continental US. The purpose of this study was to evaluate this biomass model in an African tropical forest using the Land Vegetation and Ice …

Classifying The 2022 Status Of Tsuga Canadensis (Eastern Hemlock) Along The Kentucky Portion Of The Pine Mountain Wildlands Corridor., Grace M. Embree

Electronic Theses and Dissertations

The invasion of the Hemlock Woolly Adelgid (HWA) (Adelges tsugae) has posed a continual threat in the United States to the Eastern Hemlock (Tsuga canadensis) trees since the 1950s. HWA feed on eastern hemlock needles, reducing the amount of healthy photosynthesizing vegetative area. The use of satellite imagery has been instrumental in identifying areas of eastern hemlock presence. Satellite platforms like Landsat and AVIRIS are commonly used for identification, classification, and mapping of eastern hemlock. Sentinel-2 imagery was released in 2015 for free access. It has a finer spatial grain of with the majority of the …

Spatiotemporal Data Augmentation Of Modis-Landsat Water Bodies Using Generative Adversarial Networks, Ashit Neema

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

The monitoring of the shape and area of a water body is an essential component for many Earth science and Hydrological applications. For this purpose, these applications require remote sensing data which provides accurate analysis of the water bodies. In this thesis the same is being attempted, first, a model is created that can map the information from one kind of satellite that captures the data from a distance of 500m to another data that is captured by a different satellite at a distance of 30m. To achieve this, we first collected the data from both of the satellites and …

Coupling Dendrochronology And Remote Sensing Techniques To Assess The Biophysical Traits Of Juniperus Virginiana And Pinus Ponderosa Within Grassland Communities In The Semi-Arid Grasslands Of The Nebraska Sandhills, Reece Allen

School of Natural Resources: Dissertations, Theses, and Student Research

Woody species encroachment is occurring within the sandhills region in Nebraska, primarily driven by Juniperus virginiana and Pinus ponderosa, altering ecosystems and the services they provide. Effective, low cost, and cross-scale monitoring of woody species growth and performance is necessary for integrated grassland and forest management in the face of climate variability and change. In this study, we sought to establish a relationship between remote sensing-derived vegetation indices (VIs) and dendrochronological (raw and standardized tree ring width) measurements to assess the performance of encroaching woody J. virginiana and P. ponderosa located within the Nebraska National Forest in the sandhills. …

Titaniferous-Vanadiferous, Magnetite-Ilmenite Mineralization In A Mafic Suite Within The Chhotanagpur Gneissic Complex, Bihar, India, Ashmeer Mohammad, Anup K. Prasad, Kehe-U Wetsah, Mohammad Azad, Vivek Aryan, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Titanium or vanadium metals or their alloys are important industrial metals/alloys. Because these resources are in short supply, the investigation of potential titaniferous-vanadiferous deposits needs special attention to bridge the supply-demand gap. The study integrates geological, geochemical, remote sensing, and geophysical data for assessing the potentiality of titaniferous-vanadiferous, magnetite-ilmenite mineralization in and around the Sudamakund and Paharpur areas, Gaya and Jehanabad districts, Bihar, India, and delineation of specific targets for detailed exploration. Field visits for large scale mapping on (1:12,500 scale) were used to conduct a reconnaissance survey for magnetite-ilmenite mineralization in parts of toposheet number 72G/04 in the Gaya …

Response Of Surface And Atmospheric Parameters Associated With The Iran M 7.3 Earthquake, Feng Jing, Ramesh P. Singh

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Multiparameter observed from satellite, including microwave brightness temperature, skin temperature, air temperature, and carbon monoxide, have been analyzed to identify the anomalous signals associated with the M 7.3 Iran earthquake of November 12, 2017. Besides removing the multiyear variability of parameters as background, the effect of surface and atmosphere of a dust storm event in Middle East region during October 29–November 1 is considered to distinguish the possible anomalies associated with the earthquake. The characteristic behaviors of surface and atmospheric parameters clearly show the signals associated with the M 7.3 earthquake and the dust storm event. The multiple parameters at …

Ocean Eddies And Frontal Zones In The Gulf Of Mexico And Straits Of Florida, Yingjun Zhang

USF Tampa Graduate Theses and Dissertations

Ocean eddies and fronts in the Gulf of Mexico (GoM) and the Straits of Florida (SoF) play important roles in ocean physics, biology, and ecology. These two ubiquitous physical features have been studied worldwide for decades, yet many questions remain unanswered or poorly studied for the GoM and SoF. This study aims to improve the understanding of ocean eddies and frontal zones in the GoM and SoF using satellite remote sensing, in situ observations and model outputs, as well as state-of-the-art algorithms, with the following objectives: 1) analyze the three-dimensional (3-D) statistical characteristics and thermohaline structure of mesoscale eddies in …

Osm-Gan: Using Generative Adversarial Networks For Detecting Change In High-Resolution Spatial Images, Lasith Niroshan, James Carswell

Articles

Detecting changes to built environment objects such as buildings/roads/etc. in aerial/satellite (spatial) imagery is necessary to keep online maps and various value-added LBS applications up-to-date. However, recognising such changes automatically is not a trivial task, and there are many different approaches to this problem in the literature. This paper proposes an automated end-to-end workflow to address this problem by combining OpenStreetMap (OSM) vectors of building footprints with a machine learning Generative Adversarial Network (GAN) model - where two neural networks compete to become more accurate at predicting changes to building objects in spatial imagery. Notably, our proposed OSM-GAN architecture achieved …

Using Lidar To Estimate Carbon Sequestration Of Evergreen Trees At Eastern Washington University (Ewu) Campus, Cheney, Washington, Kristy A. Snyder

2022 Symposium

EWU contains a variety of deciduous and evergreen trees across its campus, providing several benefits. However, no comprehensive record exists of the total number, location, species, or ages of these trees. This knowledge can inform facilities of proper care for individual trees and can be used to estimate carbon sequestration on campus. Traditional on-the-ground methods for assessing trees require tree cores or clinometers, making trees susceptible to pests or disease and leading to inaccurate results. Remote sensing using lidar data is a noninvasive, more precise method to measure tree height and subsequently assess tree age. This poster explores using point …

Multi-Criteria Evaluation Model For Classifying Marginal Cropland In Nebraska Using Historical Crop Yield And Biophysical Characteristics, Andrew Laws

School of Natural Resources: Dissertations, Theses, and Student Research

Marginal cropland is suboptimal due to historically low and variable productivity and limiting biophysical characteristics. To support future agricultural management and policy decisions in Nebraska, U.S.A, it is important to understand where cropland is marginal for its two most economically important crops: corn (Zea mays) and soybean (Glycine max). As corn and soybean are frequently planted in a crop rotation, it is important to consider if there is a relationship with cropland marginality. Based on the current literature, there exists a need for a flexible yet robust methodology for identifying marginal land at different scales, which …

Studying Suspended Sediment Concentrations In The South Chickamauga Creek Of Chattanooga, Tn Using Satellite Imagery, Digital Image Processing, And Numeric Modeling, Abigail Faxon

Honors Theses

In recent years, Hamilton County, TN has experienced extensive urban growth. According to US Census data, Hamilton County welcomed more than 33,000 new residents in the last decade. There is increased concern about the environmental sustainability of Chattanooga’s urban growth because significant impervious surface development has taken place along the South Chickamauga Creek. This leaves the creek subject to increased urban runoff, which often carries sediments with different municipal pollutants. Thus, monitoring turbidity in the stream water is important to determine the sustainability of urban development in Chattanooga, TN. In this research, we have compared the viability of using different …

Post-Analysis Of Osm-Gan Spatial Change Detection, Lasith Niroshan Kottawa Hewa Manage, James Carswell

Conference Papers

Keeping crowdsourced maps up-to-date is important for a wide range of location-based applications (route planning, urban planning, navigation, tourism, etc.).We propose a novelmap updatingmechanism that combines the latest freely available remote sensing data with the current state of online vector map data to train a Deep Learning (DL) neural network. It uses a GenerativeAdversarial Network (GAN) to perform image-to-image translation, followed by segmentation and raster-vector comparison processes to identify changes to map features (e.g. buildings, roads, etc.) when compared to existing map data. This paper evaluates various GAN models trained with sixteen different datasets designed for use by our change …

Learning Enriched Features For Fast Image Restoration And Enhancement, Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, Ming-Hsuan Yang, Ling Shao

Computer Vision Faculty Publications

Given a degraded input image, image restoration aims to recover the missing high-quality image content. Numerous applications demand effective image restoration, e.g., computational photography, surveillance, autonomous vehicles, and remote sensing. Significant advances in image restoration have been made in recent years, dominated by convolutional neural networks (CNNs). The widely-used CNN-based methods typically operate either on full-resolution or on progressively low-resolution representations. In the former case, spatial details are preserved but the contextual information cannot be precisely encoded. In the latter case, generated outputs are semantically reliable but spatially less accurate. This paper presents a new architecture with a holistic goal …

Chimney Identification Tool For Automated Detection Of Hydrothermal Chimneys From High-Resolution Bathymetry Using Machine Learning, Isaac Keohane, Scott White

Faculty Publications

Identifying the locations of hydrothermal chimneys across mapped areas of seafloor spreading ridges unlocks the ability to research questions about their correlations to geology, the cooling of the lithosphere, and deep-sea biogeography. We developed a Chimney Identification Tool (CIT) that utilizes a Convolutional Neural Network (CNN) to classify 1 m gridded AUV bathymetry and identify the locations of hydrothermal vent chimneys. A CNN is a type of Machine-Learning model that is able to classify raster data based on the shapes and textures in the input, making it ideal for this task. The criteria that have been used in previous manual …

Land Cover Classification And Change During Mine Reclamation In Northeast Florida Using Multispectral Imagery, Daniel Burow, Robert Brown, Alexis Caldwell, Patrick Hunter, Jett-Ramy Kaddour, Alexander Kingma, Justin Kozicki, Blake Neal, Abigail Neff, Rylan Randolph, Devon Tanner, Isaiah Vahos

Sustainability Conference

Titanium is commonly used in the aerospace industry because it is lightweight and durable in extreme temperatures. The Green Cove Springs Mine, near Green Cove Springs, Florida, was used for mining and processing titanium and other minerals from 1972 until 2009. Since then, the mine area is being reclaimed, or rehabilitated and restored to its natural state, as required by Florida Department of Environmental Protection regulations. In this study, we use high-resolution multispectral satellite and aerial imagery obtained from 2016 to 2022 to examine land cover (LC) changes at the Green Cove Springs Mine during this reclamation period. We use …

Surface Urban Heat Island In South Korea’S New Towns With Different Urban Planning, Kyungil Lee, Yoonji Kim, Hyun Chan Sung, Seung Hee Kim, Seong Woo Jeon

Institute for ECHO Articles and Research

A new town is strategically built within a short period compared to naturally developed cities. It is considered an appropriate study area for analyzing the urban climate problems such as surface urban heat islands (SUHIs) that is differently generated according to urban planning and development. In this study, we suggest comprehensive method for determining and comparing changes in surface UHI distribution during 1989–2048 in two new towns with different urban planning. First, a substantial increase in built-up areas was observed from 1989 (< 5%) to 2018 (> 40%) in both new towns. However, SUHI phenomenon-increasing patterns were different of about 12.25% depending on urban …

Using Remote Sensing Technologies In Relocating Lubrak Village And Visualizing Flood Damages, Ronan Wallace

Independent Study Project (ISP) Collection

As weather patterns change across the world, there are communities impacted by climate change that are left unnoticed. In the Himalayan mountain range, communities have suffered, experiencing an increase in flash flooding and droughts. For Lubrak Village in Lower Mustang, the community faces the threats of flash flooding. Over the last ten years, the amount of flash flooding has increased, occurring more than once each monsoon season. After every flood, concrete-like sediment is left behind, hardening across the riverbed and increasing its elevation. As the riverbed elevation increases, this sediment encroaches on Lu-brak Village’s agricultural fields and ancient mud buildings, …

Disaster Site Structure Analysis: Examining Effective Remote Sensing Techniques In Blue Tarpaulin Inspection, Madeline G. Miles

Theses

This thesis aimed to evaluate three methods of analyzing blue roofing tarpaulin (tarp) placed on homes in post natural disaster zones with remote sensing techniques by assessing the different methods- image segmentation, machine learning (ML), and supervised classification. One can determine which is the most efficient and accurate way of detecting blue tarps. The concept here was that using the most efficient and accurate way to locate blue tarps can aid federal, state, and local emergency management (EM) operations and homeowners. In the wake of a natural disaster such as a tornado, hurricane, thunderstorm, or similar weather events, roofs are …