Remote Sensing Commons^™

Delineating A Stream Network At Gale Crater, Mars, On Arcgis Pro: A Geographic Information Systems Approach, Elpidio Guzman De La Cruz

West Chester University Master’s Theses

The northwestern region of the Gale crater experienced flooding in the past. Delineation of stream networks for the northwestern region of Gale Crater, Mars employing geographic information systems (GIS) techniques is applied. The stream network produced by the algorithm in the study traverses the clay unit in Gediz Vallis, and visual HiRISE imagery analysis correlates with a topologic cross section of an inverted river channel of 750 meters wide and 90 meters deep. HiRISE imagery analysis further confirms a sulfate and clay stratigraphic unit in a stream 125 meters wide and 25 meters deep. Lastly, data smoothing procedures in the …

Impact Of Atmospheric Correction On Classification And Quantification Of Seagrass Density From Worldview-2 Imagery, Victoria J. Hill, Richard C. Zimmerman, Paul Bissett, David Kohler, Blake Schaeffer, Megan Coffer, Jiang Li, Kazi Aminul Islam

OES Faculty Publications

Mapping the seagrass distribution and density in the underwater landscape can improve global Blue Carbon estimates. However, atmospheric absorption and scattering introduce errors in space-based sensors’ retrieval of sea surface reflectance, affecting seagrass presence, density, and above-ground carbon (AGC_seagrass) estimates. This study assessed atmospheric correction’s impact on mapping seagrass using WorldView-2 satellite imagery from Saint Joseph Bay, Saint George Sound, and Keaton Beach in Florida, USA. Coincident in situ measurements of water-leaving radiance (L_w), optical properties, and seagrass leaf area index (LAI) were collected. Seagrass classification and the retrieval of LAI were compared after empirical line …

Linkages Between Atmospheric Circulation, Weather, Climate, Land Cover And Social Dynamics Of The Tibetan Plateau, Shobha Kumari Yadav

Graduate Theses, Dissertations, and Problem Reports (ETD)

The Tibetan Plateau (TP) is an important landmass that plays a significant role in both regional and global climates. In recent decades, the TP has undergone significant changes due to climate and human activities. Since the 1980s anthropogenic activities, such as the stocking of livestock, land cover change, permafrost degradation, urbanization, highway construction, deforestation and desertification, and unsustainable land management practices, have greatly increased over the TP. As a result, grasslands have undergone rapid degradation and have altered the land surface which in turn has altered the exchange of heat and moisture properties between land and the atmosphere. But gaps …

Carnivore And Ungulate Occurrence In A Fire-Prone Region, Sara J. Moriarty-Graves

Cal Poly Humboldt theses and projects

Increasing fire size and severity in the western United States causes changes to ecosystems, species’ habitat use, and interspecific interactions. Wide-ranging carnivore and ungulate mammalian species and their interactions may be influenced by an increase in fire activity in northern California. Depending on the fire characteristics, ungulates may benefit from burned habitat due to an increase in forage availability, while carnivore species may be differentially impacted, but ultimately driven by bottom-up processes from a shift in prey availability. I used a three-step approach to estimate the single-species occupancy of four large mammal species: mountain lion (Puma concolor), coyote …

Monitoring Bull Kelp (Nereocystis Leutkeana) Remotely At High Resolutions, Hannah E. Joss

Cal Poly Humboldt theses and projects

Bull kelp (Nereocystis leutkeana) is a foundational seaweed in nearshore, marine systems, traditionally supporting economically important fisheries, extracting nutrients in its vicinity, and sequestering carbon and transporting it great distances to subsidize shallow and deep-sea environments. Bull kelp is also a culturally important species for some indigenous peoples along the northeastern Pacific coastline and provides a harvestable product with growing demand. Global trends in kelp distribution show patterns of decline, and the immense loss of northern California bull kelp forests in response to climatic changes have highlighted the need for alternative sources of kelp, both for the product …

Relative Importance Of Radar Variables For Nowcasting Heavy Rainfall: A Machine Learning Approach, Yi Victor Wang, Seung Hee Kim, Geunsu Lyu, Choeng-Lyong Lee, Gyuwon Lee, Ki-Hong Min, Menas C. Kafatos

Institute for ECHO Articles and Research

Highly short-term forecasting, or nowcasting, of heavy rainfall due to rapidly evolving mesoscale convective systems (MCSs) is particularly challenging for traditional numerical weather prediction models. To overcome such a challenge, a growing number of studies have shown significant advantages of using machine learning (ML) modeling techniques with remote sensing data, especially weather radar data, for high-resolution rainfall nowcasting. To improve ML model performance, it is essential first and foremost to quantify the importance of radar variables and identify pertinent predictors of rainfall that can also be associated with domain knowledge. In this study, a set of MCS types consisting of …

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 …

Possible Overestimation Of Nitrogen Dioxide Outgassing During The Beirut 2020 Explosion, Ashraf Farahat, Nayla El-Kork, Ramesh P. Singh, Feng Jing

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

On 4 August 2020, a strong explosion occurred near the Beirut seaport, Lebanon and killed more than 200 people and damaged numerous buildings in the vicinity. As Amonium Nitrate (AN) caused the explosion, many studies claimed the release of large amounts of NO₂ in the atmosphere may have resulted in a health hazard in Beirut and the vicinity. In order to reasonably evaluate the significance of NO₂ amounts released in the atmosphere, it is important to investigate the spatio-temporal distribution of NO₂ during and after the blast and compare it to the average day-to-day background emissions from …

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 …

Remote Sensing Application For Landslide Detection: Monitoring Along Eastern Lake Michigan (Miami Park, Mi), Guzalay Sataer

Dissertations

I assessed the nature and spatial and temporal patterns of deformation over the Miami Park bluffs on the eastern margin of Lake Michigan and investigated the factors controlling its observed deformation. Our approach involved the following steps: (1) extracting bluff deformation rates (velocities along the line of sight of the satellite) using a stack of Sentinel-1A radar imagery in ascending acquisition geometry acquired between 2017 and 2021 and applying the Intermittent Small Baseline Subset (ISBAS) InSAR time series analysis method; (2) generating high-resolution (5 cm) elevation models and orthophotos from temporal unmanned aerial vehicle (UAV) surveys acquired in 2017, 2019, …

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 …

Delineating Field Variation Using Apparent Electrical Conductivity In An Ozark Highlands Agroforestry System, Shane Reid Ylagan

Graduate Theses and Dissertations

Little to no work has been conducted assessing field variability using repeated electromagnetic induction (EMI) apparent electrical conductivity (ECa) surveys in agroforestry (AF) systems within regions similar to the Ozark Highlands. The objectives of this thesis were to identify i) spatiotemporal ECa variability; ii) ECa-derived soil management zones (SMZs); iii) correlations among EMI-ECa and in-situ, sentential-site soil properties; iv) whether fewer, EMI-ECa surveys could be conducted to capture similar ECa variance as mid-monthly EMI-ECa surveys; v) correlations between ECa and forage yield, tree growth, and terrain attributes based on plant (forage and tree) species, and fertility treatments, and ECa-derived SMZs, …

Efficient Hierarchical Space-Time Models For Large Areal Datasets With Application To Forest Inventory Mapping Using Remote Sensing Imagery, Md Kamrul Hasan Khan

Graduate Theses and Dissertations

The focus of this dissertation is development of a novel hierarchical framework, that can be used for predictive modeling of Forest Inventory and Analysis (FIA) data over large regions. This dissertation has two significant contributions. Based on a study region in north-central Wisconsin, we analyze satellite imagery, along with a sample of national forest inventory field plots, to monitor and predict changes in forest conditions over time. The auxiliary data from the satellite imagery of this region are relatively dense in space and time, and can be used to learn how forest conditions changed over that decade. However, these records …

Glacier Segmentation From Remote Sensing Imagery Using Deep Learning, Bibek Aryal

Open Access Theses & Dissertations

Large-scale study of glaciers improves our understanding of global glacier change and is imperative for monitoring the ecological environment, preventing disasters, and studying the effects of global climate change. In recent years, remote sensing imagery has been preferred over riskier and resource-intensive field visits for tracking landscape level changes like glaciers. However, periodic manual labeling of glaciers over a large area is not feasible due to the considerable amount of time it requires while automatic segmentation of glaciers has its own set of challenges. Our work aims to study the challenges associated with segmentation of glaciers from remote sensing imagery …

Systematic Review Of A Ramsar Wetland And Unesco Biosphere Reserve In A Climate Change Hotspot (Ichkeul Lake, Tunisia), Sabrine Sahbani, Béchir Béjaoui, Sihem Benabdalla, Rachid Toujani, Afef Fathalli, Noureddine Zaaboub, Jalel Aouissi, Zeineb Kassouk, Nabil Hamdi, Nabiha Ben Mbarek, Hechmi Missaoui, Leila Basti, Reginald Blake, Hamidreza Norouzi

Publications and Research

Tunisia's Ichkeul Lake is among the most productive ecosystems in the Mediterranean, with a great regional value thanks to its diversity of habitats. It is an important overwintering area for waterfowl species. It is a RAMSAR wetland, a National Park, a UNESCO World Heritage, and a Biosphere Reserve. This review paper provides a broad overview of the climatic, hydraulic, biogeochemical features, bio-resources, and bio-productivity of the Lake. The interconnectivity between the different environmental components of the lake is presented, highlighting the main characteristics of this vital ecosystem. Its ecosystem consists of a permanent lake bordered by temporary marshes. It is …

Meteor Radar Vertical Wind Observation Biases And Mathematical Debiasing Strategies Including The 3dvar+Div Algorithm, Alan Z. Liu, Zishun Qiao, Gunter Stober, Alexander Kozlovsky, Ales Kuchar, Christoph Jacobi, Chris Meek, Diego Janches, Guiping Liu, Masaki Tsutsumi, Njål Gulbrandsen, Satonori Nozawa, Mark Lester, Evgenia Belova, Johan Kero, Nicholas Mitchell

Publications

Meteor radars have become widely used instruments to study atmospheric dynamics, particularly in the 70 to 110 km altitude region. These systems have been proven to provide reliable and continuous measurements of horizontal winds in the mesosphere and lower thermosphere. Recently, there have been many attempts to utilize specular and/or transverse scatter meteor measurements to estimate vertical winds and vertical wind variability. In this study we investigate potential biases in vertical wind estimation that are intrinsic to the meteor radar observation geometry and scattering mechanism, and we introduce a mathematical debiasing process to mitigate them. This process makes use of …

Spatio-Temporal Changes In Vegetation In The Last Two Decades (2001–2020) In The Beijing–Tianjin–Hebei Region, Yuan Zou, Wei Chen, Siliang Li, Tiejun Wang, Le Yu, Min Xu, Ramesh P. Singh, Cong-Qiang Liu

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

In terrestrial ecosystems, vegetation is sensitive to climate change and human activities. Its spatial-temporal changes also affect the ecological and social environment. In this paper, we considered the Beijing–Tianjin–Hebei region to study the spatio-temporal vegetation patterns. The detailed analysis of a moderate-resolution imaging spectroradiometer (MODIS) data were carried out through the Google Earth Engine (GEE) platform. Our results show a slow and tortuous upward trend in the average leaf area index (LAI) in the study region for the periods 2001–2020. Specifically, Beijing had the highest LAI value, with an average of 1.64 over twenty years, followed by Hebei (1.30) and …

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 …

Deep Learning Applications In Industrial And Systems Engineering, Winthrop Harvey

Graduate Theses and Dissertations

Deep learning - the use of large neural networks to perform machine learning - has transformed the world. As the capabilities of deep models continue to grow, deep learning is becoming an increasingly valuable and practical tool for industrial engineering. With its wide applicability, deep learning can be turned to many industrial engineering tasks, including optimization, heuristic search, and functional approximation. In this dissertation, the major concepts and paradigms of deep learning are reviewed, and three industrial engineering projects applying these methods are described. The first applies a deep convolutional network to the task of absolute aerial geolocalization - the …

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 …

Differentiating Fissure-Fed Lava Flow Types And Facies Using Radar And Lidar: An Example From The 2014–2015 Holuhraun Lava Flow-Field, Gavin Douglas Tolometti, Catherine D. Neish, Christopher W. Hamilton, Gordon R. Osinski, Antero Kukko, Joana R.C. Voigt

Earth Sciences Publications

Distinguishing between lava types and facies using remote sensing data is important for interpreting the emplacement history of lava flow-fields on Earth and other planetary bodies. Lava facies typically include a mixture of lava types and record the collective emplacement history of material preserved at a particular location. We seek to determine if lava facies in the 2014–2015 Holuhraun lava flow-field are discernible using radar roughness analysis. Furthermore, we also seek to distinguish between lava types using high resolution Light Detection and Ranging (LiDAR) data. We extracted circular polarization ratios (CPR) from the Uninhabited Aerial Vehicle Synthetic Aperture Radar and …

Gigapan® Photogrammetry For Outcrop Description, 3d Modeling, And 3d Printing, Preston Liles, Logan Pearson, Samantha Barnett, Dakota G. Simpson, David B. Fitzpatrick, Erik B. Larson, Maurice Testa

The Compass: Earth Science Journal of Sigma Gamma Epsilon

The collection of 3D information on geological media is fundamental for field geology, however it can be both time consuming and expensive. This report proposes a new method for the collection of 3D information of outcrops using simple to use and inexpensive technology. GigaPan® systems can be used to take high resolution images of outcrops and these images then be either left in 2D for additional description of the outcrop in the lab, or they can be processed in Autodesk 3ds Max® to create realistic 3D models of the outcrops which can then be 3D printed. The collection of this …

Machine Learning With Kay, Lasith Niroshan, James Carswell

Conference Papers

Computational power is very important when training Deep Learning (DL) models with large amounts of data (Wooldridge, 2021). Hence, High-Performance Computing (HPC) can be leveraged to reduce computational cost, and the Irish Centre for High-End Computing (ICHEC) provides significant infrastructure and services for research and development to both academia and industry. A portion of ICHEC's HPC system has been allocated for institutional access, and this paper presents a case study of how to use Kay (Ireland's national supercomputer) in the remote sensing domain. Specifically, this study uses clusters of Kay Graphics Processing Units (GPUs) for training DL models to extract …

Pronounced Changes In Thermal Signals Associated With The Madoi (China) M 7.3 Earthquake From Passive Microwave And Infrared Satellite Data, Feng Jing, Lu Zhang, Ramesh P. Singh

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Thermal variations in surface and atmosphere observed from multiple satellites prior to strong earthquakes have been widely reported ever since seismic thermal anomalies were discovered three decades ago. These thermal changes are related to stress accumulation caused by the tectonic activities in the final stage of earthquake preparation. In the present paper, we focused on the thermal changes associated with the 2021 Madoi M 7.3 earthquake in China and analyzed the temporal and spatial evolution of the Index of Microwave Radiation Anomaly (IMRA) and the Index of Longwave Radiation Anomaly (ILRA) based on 8-year microwave brightness temperature (MWBT) and 14-year …

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 …

Remote Sensing & Land Surface Temperature From Satellite Observations, Isatu Jollah

Publications and Research

The Moderate Resolution Imaging Spectroradiometer (MODIS) instrument is designed and developed in 1995. • It is a critical instrument aboard Terra and Aqua satellites. Terra's orbit around the Earth is timed so that it crosses the equator from north to south in the morning, while Aqua crosses the equator from south to north in the afternoon. • Every 1 to 2 days, Terra MODIS and Aqua MODIS scan the entire Earth's surface, collecting data in groups of wavelengths. • In this research, a whole month of MODIS Land Surface Temperature data from both Aqua and Terra were explored and investigated.

Lake Satellite Temperature Data Validation, Mamadou Balde, Pascal Kouogang

Publications and Research

In environmental remote sensing, satellite data isn't absolutely conclusive, for that reason, there is a natural need to verify the data acquired from the satellite. The most suitable tool to achieve such verification is on ground sensors that have the advantage of proximity. Addressing any possible discrepancies between the satellite data and the ground sensor data is sure to yield ways to come up with improvements of satellite band calibration and sensing capabilities. This research focused on correlating temperature data from the MODIS satellite with the data obtained from the In Situ sensor located in Lake Sunapee. Doing the latter …

Land And Water Resources For Irrigated Agriculture In The Pilbara, Paul Galloway, John A. Simons, Karen Holmes, Dennis Van Gool

Resource management technical reports

This report documents the procedures used to identify suitable locations for irrigation development in the Pilbara region. It is the first study to investigate the potential for irrigated agriculture across the Pilbara. We used a desktop analysis to ascertain water availability and spatial data modelling to determine the potential of the land and soil resource to support irrigated agriculture. This study was part of the Pilbara Hinterland Agricultural Development Initiative (PHADI).

We used existing rangeland land inventory information augmented with digital spatial environmental data, in a process known as map disaggregation, to create soil and landform maps that had a …

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 …