Remote Sensing Commons^™

Direct Aerial Visual Geolocalization Using Deep Neural Networks, Winthrop Harvey, Chase Rainwater, Jackson Cothren

Industrial Engineering Faculty Publications and Presentations

Unmanned aerial vehicles (UAVs) must keep track of their location in order to maintain flight plans. Currently, this task is almost entirely performed by a combination of Inertial Measurement Units (IMUs) and reference to GNSS (Global Navigation Satellite System). Navigation by GNSS, however, is not always reliable, due to various causes both natural (reflection and blockage from objects, technical fault, inclement weather) and artificial (GPS spoofing and denial). In such GPS-denied situations, it is desirable to have additional methods for aerial geolocalization. One such method is visual geolocalization, where aircraft use their ground facing cameras to localize and navigate. The …

Forest Fire Effects On The Temporal Variability Of Landscape Snow Albedo Relative To Burn Severity, Max Gersh

Dissertations and Theses

Snow-water storage is decreasing, while forest fires are increasing in duration, size, frequency, and intensity, due to climate change. Most forest fires occur in the seasonal snow zone, altering snow mass and energy balance for many years following fire. Following forest fires, Surface snow albedo (SSA) decreases, as light absorbing particles (LAP), particularly black carbon (BC) produced in forest fires get deposited throughout the snowpack, altering snowpack energy balance driving earlier snowmelt in burned forests. While SSA decreases, landscape snow albedo (LSA) increases following fire, as more of the snow-covered surface becomes visible beneath the burned forest canopy, brightening the …

High-Throughput Phenotyping Of Rice Grains Subjected To High Nighttime Temperature Stress, Shannon Shareice Cunningham

Student Theses and Dissertations

Rice grain size is affected by high nighttime temperature stress (HNT). Although studied in small subsets, the Rice Diversity Panel 1 has not been extensively studied to determine HNT effects on grain size. Accessions have been identified as tolerant and sensitive to HNT under greenhouse conditions (Dhatt et al., 2020). A high throughput phenotyping (HTPP) method and a PlantCV2 workflow were implemented in this work to determine grain dimensions. Seed area was found to be a good indicator of HNT tolerance with a coefficient of variation being 15%. Among tolerant accessions, seed area increased by an average of 1.57 mm2 …

Observations Of Post-Wildfire Landcover Trends In Boreal Alaska Using A Suite Of Remote Sensing Approaches, Eric John Deutsch

Theses - ALL

Wildfires are a common occurrence in the boreal ecosystems of the Pacific Northwest. Studies suggest that anthropogenic climate change has fostered more frequent and higher severity fires in recent decades in these forests, which may result in substantial changes in vegetation structure and ecosystem functioning. However, large-scale studies examining the linkages between changing boreal wildfire regimes and vegetation structure have historically been limited in spatial scope due to the broad area and inaccessibility of many boreal regions, including the Alaskan interior. The development and advancement of satellite remote sensing instruments and geospatial analysis techniques provide researchers with unmatched abilities to …

Changes In The Flood Plains And Water Quality Along The Himalayan Rivers After The Chamoli Disaster Of 7 February 2021, Sansar Raj Meena, Kushanav Bhuyan, Akshansa Chauhan, Ramesh P. Singh

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

The Himalayan regions are vulnerable to all kinds of natural hazards. On 7 February 2021, a deadly disaster occurred near the Tapovan, in Uttarakhand, Himalayas. During the event, large volume of debris along with broken glacial fragments flooded the Rishi Ganga River and washed away the nearby hydropower plants (Rishi Ganga and Tapovan), which was revealed from detailed analysis of multi spectral and bi-temporal satellite data. We present the impact of the Chamoli disaster on the flood plains and water quality of Himalayan rivers, Rishi Ganga near Tapovan, Alaknanda near Srinagar and Ganga near Haridwar and Bijnor. We used four …

Unmanned Aircraft Systems For Archaeology Using Photogrammetry And Lidar In Southwestern United States, Imai Bates-Domingo, Alexandra Gates, Patrick Hunter, Blake Neal, Kyle Snowden, Destin Webster

Study America

Researchers can use small unmanned aircraft systems (sUAS), also known as drones, to make observations of historical sites, help interpret locations, and make new discoveries that may not be visible to the naked eye. A student team from Embry-Riddle Aeronautical University gathered data for historical site documentation in New Mexico using the DJI Phantom 4 Pro V2, DJI Mavic Pro 2, DJI M210 and DJI M600, and senseFly eBee. Utilizing these drones, student analysts were able to take the data gathered and create georectified orthomosaic images and 3D virtual objects. At Tularosa Canyon, at a site known as the Creekside …

Downscaling Of Goes-16'S Land Surface Temperature Product Using Epitomes, Roberto Garcia

Open Access Theses & Dissertations

Land surface temperature (LST) is an environmental variable derived from thermal infrared (TIR) imagery. Satellite platforms are a good source of TIR imagery because of their ability to provide widespread and frequent coverage of the Earthâ??s surface. It is common that a single satellite remote sensing platform is able to provide images with good spatial resolution or temporal resolution but not both. LST is an important parameter for studies on the urban heat island (UHI) effect. These studies are limited by the spatial or temporal resolutions of available LST products. This Thesis presents an algorithm to estimate land surface temperature …

Leveraging Of Hyperspectral Remote Sensing On Estimating Biomass Yield Of Moringa Oleifera Lam. Medicinal Plant, Thulani Tshabalala, Elfatih M. Abdel-Rahman, Bhekumthetho Ncube, Ashwell R. Ndhlala, Onisimo Mutanga

All Peer-Reviewed Publications

Moringa oleifera Lam. is a functional plant considered to be high in nutrients as well as medicinal properties, largely utilised in most of the developing countries. Therefore, early prediction of M. oleifera biomass yield is a valuable pre- and post-harvest planning strategy for ensuring a reliable supply of the plant products and for marketing purposes. Subsequently, the objective of the current study was to explore the potential use of hyperspectral data in predicting biomass yield of different cultivars of M. oleifera. Canopy hyperspectral data were collected on five M. oleifera cultivars when they were one month and two months old …

Use Of Earth Observation Satellite Data To Guide The Implementation Of Integrated Pest And Pollinator Management (Ippm) Technologies In An Avocado Production System, Marian Adan, Elfatih M. Abdel-Rahman, Stella Gachoki, Beatrice W. Muriithi, H. Michael G. Lattorff, Vivian Kerubo, Tobias Landmann, Samira A. Mohamed, Henri E.Z. Tonnang, Thomas Dubois

All Peer-Reviewed Publications

Insect pollinators provide an important ecosystem service by improving agricultural productivity. However, their populations have been declining in recent years due to excessive use of synthetic pesticides, climate and land use/land cover (LULC) changes. Climate and LULC changes have resulted in land fragmentation and consequently pollinator habitat loss. To conserve pollinators, there is a need for sustainable agricultural practices such as integrated pest and pollinator management (IPPM), which is a holistic landscape management approach that minimizes pesticides use while conserving pollinator abundance and diversity. This study aimed to use earth observation (EO) data to characterize landscape dynamics in terms of …

Relationship Between Image Spectroscopy Spatial Resolution And Crown Level Tree Species Classification Accuracy, Andrew Richard Fritter

Dissertations and Theses

Hyperspectral imagery has become a common remote sensing data type used in tree species classifications because of its rich spectral signals that allow the detection of the variations in canopy reflectance. While high spatial resolution hyperspectral imagery provides fine spatial resolution for discerning surface objects, it has the inherent drawbacks of expensive acquisition costs, large data sizes, and can be computationally taxing to use. This study attempts to determine a relationship between crown level tree species classification accuracy and hyperspectral spatial resolution. Future tree species classification projects can make use of this relationship by targeting a spatial resolution that best …

An Operational Overview Of The Export Processes In The Ocean From Remote Sensing (Exports) Northeast Pacific Field Deployment, David A. Siegel, Ivona Cetinić, Jason R. Graff, Craig M. Lee, Norman Nelson, Mary Jane Perry, Inia Soto Ramos, Deborah K. Steinberg, Ken Buesseler, Roberta Hamme, Andrea J. Fassbender, David Nicholson, Melissa M. Omand, Marie Robert, Andrew Thompson, Vinicius Amaral, Michael Behrenfeld, Claudia Benitez-Nelson, Kelsey Bisson, Emmanuel Boss, Philip W. Boyd, Mark Brzezinski, Kristen Buck

Faculty Publications

The goal of the EXport Processes in the Ocean from RemoTe Sensing (EXPORTS) field campaign is to develop a predictive understanding of the export, fate, and carbon cycle impacts of global ocean net primary production. To accomplish this goal, observations of export flux pathways, plankton community composition, food web processes, and optical, physical, and biogeochemical (BGC) properties are needed over a range of ecosystem states. Here we introduce the first EXPORTS field deployment to Ocean Station Papa in the Northeast Pacific Ocean during summer of 2018, providing context for other papers in this special collection. The experiment was conducted with …

Analyzing Satellite Ocean Color Match-Up Protocols Using The Satellite Validation Navy Tool (Savant) At Moby And Two Aeronet-Oc Sites, Adam Lawson, Jennifer Bowers, Sherwin Ladner, Richard Crout, Christopher Wood, Robert Arnone, Paul Martinolich, David Lewis

Faculty Publications

The satellite validation navy tool (SAVANT) was developed by the Naval Research Laboratory to help facilitate the assessment of the stability and accuracy of ocean color satellites, using numerous ground truth (in situ) platforms around the globe and support methods for match-up protocols. The effects of varying spatial constraints with permissive and strict protocols on match-up uncertainty are evaluated, in an attempt to establish an optimal satellite ocean color calibration and validation (cal/val) match-up protocol. This allows users to evaluate the accuracy of ocean color sensors compared to specific ground truth sites that provide continuous data. Various match-up constraints may …

Deep Learning Reveals Extent Of Archaic Native American Shell-Ring Building Practices, Dylan Davis, Gino Capsari, Carl P. Lipo, Matthew Sanger

Anthropology Faculty Scholarship

In the mid-Holocene (5000 - 3000 cal B.P.), Native American groups constructed shell rings, a type of circular midden, in coastal areas of the American Southeast. These deposits provide important insights into Native American socioeconomic organization but are also quite rare: only about 50 such rings have been documented to date. Recent work using automated LiDAR analysis demonstrates that many more shell rings likely exist than are currently recorded in state archaeological databases. Here, we use deep learning, a form of machine intelligence, to detect shell ring deposits and identify their geographic range in LiDAR data from South Carolina. We …

Machine Learning & Big Data Analyses For Wildfire & Air Pollution Incorporating Gis & Google Earth Engine, Abdullah Al Saim

Graduate Theses and Dissertations

The climatic condition, the vegetation type, and the landscape of the United States have made it susceptible to wildfires. This research is divided into two parts based on the analysis of two different aspects of wildfires of two distinct regions. The first part of the study investigates the wildfire susceptibility in Arkansas. Arkansas is a natural state, and it is heavily dependent on its forest and agricultural resources. During the last 30 years, more than 1,000 wildfires occurred in Arkansas and caused more than 10,000 acres of burned areas. Therefore, identifying wildfire-susceptible areas is crucial for ensuring sustainable forest and …

Economically Optimal Nitrogen Side-Dressing Based On Vegetation Indices From Satellite Images Through On-Farm Experiments, Qianqian Du

Department of Agricultural Economics: Dissertations, Theses, and Student Research

Optimal N fertilizer rates for corn (Zea mays L.) vary substantially within and among fields, and by corn growth stages. Improving N side-dressing management can improve fertilizer use efficiency, farmers’ profitability, and the sustainability of crop production. The objective of this study is to introduce a framework along with a methodology that can find the site-specific economically optimal N rates (EONRs) within one field for a particular growing season. An on-farm experiment was conducted in the 2019 corn growing season. A base N rate was applied uniformly on the field. NDRE images from the Sentinel-2 satellite were observed during …

Towards An Integrated Assessment Of Sea-Level Observations Along The U.S. Atlantic Coast, Brett A. Buzzanga

OES Theses and Dissertations

Sea levels are rising globally due to anthropogenic climate change. However, local sea levels that impact coastal ecosystems often differ from the global trend, sometimes by a factor of two or more. Improved understanding of this regional variability provides insights into geophysical processes and has implications for coastal communities developing resilience to ongoing sea-level rise. This dissertation conducts an investigation of sea level and its contributing processes at multiple spatial scales. Focusing on primarily interannual time-scales and data-driven approaches, new data sources and technologies are utilized to reduce current uncertainties.

First, sea-level trends are assessed over the global ocean and …

Deep Learning Approaches For Seagrass Detection In Multispectral Imagery, Kazi Aminul Islam

Electrical & Computer Engineering Theses & Dissertations

Seagrass forms the basis for critically important marine ecosystems. Seagrass is an important factor to balance marine ecological systems, and it is of great interest to monitor its distribution in different parts of the world. Remote sensing imagery is considered as an effective data modality based on which seagrass monitoring and quantification can be performed remotely. Traditionally, researchers utilized multispectral satellite images to map seagrass manually. Automatic machine learning techniques, especially deep learning algorithms, recently achieved state-of-the-art performances in many computer vision applications. This dissertation presents a set of deep learning models for seagrass detection in multispectral satellite images. It …

Assessing Impacts Of Winter-Hay Feeding On Soil And Forage Nutrient Dynamics In A Rotationally-Grazed Pasture System In Arkansas, Lawrence Gordon Berry Iv

Graduate Theses and Dissertations

More than 38 % of United States’ rural land area was used for grazing (i.e., pastureland or rangeland) ruminant animals in 2017, constituting the largest private land use group. The expansive nature of these lands means that grazing and pasture management decisions have potential to impact water quality as well as profit margins. As a result, beef producers are under increased pressure from economic and environmental standpoints to limit application of nutrients beyond those required to grow the forage needed for animal consumption. At the same time, a large amount of nutrients is recycled back to pasture systems directly from …

Geolocation Of Monitoring Wells Using Small Unmanned Aircraft Systems, Joel Deyoung

Graduate Theses and Dissertations

Groundwater monitoring wells are commonly installed on a property as part of an environmental investigation to observe hydrological subsurface conditions, facilitate the collection of groundwater samples, and predict the flow of groundwater across a site. In addition to their installation, monitoring wells should be surveyed or mapped as accurately as possible. Traditional surveying techniques have employed the use of global navigation satellite systems (GNSS) technologies or other surveying equipment. A common surveying approach is to use real-time kinematic (RTK) GNSS to accurately measure the coordinates of each monitoring well on the site.In recent years, drones, or small unmanned aircraft systems …

Examining Melt Pond Dynamics And Light Availability In The Arctic Ocean Via High Resolution Satellite Imagery, Austin Wesley Abbott

OES Theses and Dissertations

As the Arctic experiences consequences of climate change, a shift from thicker, multi-year ice to thinner, first-year ice has been observed. First-year ice is prone to extensive pools of meltwater (“melt ponds”) forming on its surface, which enhance light transmission to the ocean. Changes in the timing and distribution of melt pond formation and associated increases in under-ice light availability are the primary drivers for seasonal progression of water column primary production and warming. Observations of melt pond development and distribution require meter scale resolution and have traditionally been limited to airborne images. However, recent advances in high spatial resolution …