Remote Sensing Commons^™

Application Of Uas Remote Sensing For Cultural Heritage Preservation And Archaeology, Nickolas D. "Dan" Macchiarella, Kevin A. Adkins

Publications

Using small unmanned aircraft systems (sUAS) to gain aerial perspectives for remote sensing with cameras and LiDAR is truly benefiting cultural heritage preservation and archaeological work. Photogrammetric products derived from sUAS captured images are providing precise and detailed data. LiDAR- equipped sUAS are also making precise and detailed data available for analysis. Rapid technological gains associated with all UAS are bringing these remote sensing technologies to bear in exciting ways. Novoberda fortress in the Republic of Kosovo and Creekside Village, Tularosa Basin, New Mexico provide excellent examples of photogrammetric work and LiDAR derived analysis products resulting from the use of …

Lake Huron Shoreline Analysis, Shubham Satish Nandanwar

Theses and Dissertations (Comprehensive)

Lake Huron is a popular tourist destination and is home to several businesses and residents. Since the shoreline is dynamic and is subject to change over the years due to several factors such as a change in water level, soil type, human encroachment, etc., these locations tend to encounter floods due to increased water levels and wind speed. This causes erosion and loss to the properties along the shoreline.

This study is based on two areas of interest named Pinery Provincial Park and Sauble Beach which are located on the shoreline of Lake Huron where Pinery Provincial Park is a …

Industry 4.0 Remanufacturing: A Novel Approach Towards Smart Remanufacturing, Prashansa Ragampeta

Masters Theses

“Smart remanufacturing has become more popular in recent years as a result of its multiple benefits and the growing need for society to encourage a circular economy that leads to sustainability. One of the most common end-of-life (EoL) choices that can lead to a circular economy is remanufacturing. As a result, at the end-of-life stage of a product, it is critical to prioritize this choice over other accessible options because it is the only recovery option that retains the same quality as a new product. This work focuses on the numerous technologies that can aid in the improvement of smart …

Machine Learning Land Cover And Land Use Classification Of 4-Band Satellite Imagery, Lorelei Turner, Torrey J. Wagner, Paul Auclair, Brent T. Langhals

Faculty Publications

Land-cover and land-use classification generates categories of terrestrial features, such as water or trees, which can be used to track how land is used. This work applies classical, ensemble and neural network machine learning algorithms to a multispectral remote sensing dataset containing 405,000 28x28 pixel image patches in 4 electromagnetic frequency bands. For each algorithm, model metrics and prediction execution time were evaluated, resulting in two families of models; fast and precise. The prediction time for an 81,000-patch group of predictions wasmodels, and >5s for the precise models, and there was not a significant change in prediction time when a …

Characterization Of Site-Specific Vegetation Activity In Alaskan Wet And Dry Tundra As Related To Climate And Soil State, Michael Gregory Brown, Kyle C. Mcdonald, Reiner Zimmermann, Nicholas Steiner, Stephanie Devries, Laura Bourgeau-Chavez

Advanced Science Research Center

We present discrete (2-h resolution) multi-year (2008–2017) in situ measurements of seasonal vegetation growth and soil biophysical properties from two sites on Alaska's North Slope, USA, representing dry and wet sedge tundra. We examine measurements of vertical active soil layer temperature and soil moisture profiles (freeze/thaw status), woody shrub vegetation physiological activity, and meteorological site data to assess interrelationships within (and between) these two study sites. Vegetation phenophases (cold de-hardening start, physiological function start, stem growth start, stem growth end, physiological function end, cold hardening completion) were found to have greater interannual day of year (DOY) occurrence variability at the …

Identification Of Poverty Areas By Using Machine Learning Classification Methods From Satellite Imagery In Buraydah City, In The Qassim Region Of Saudi Arabia, Amal Alfawzan

Murray State Theses and Dissertations

Saudi Arabia is a wealthy country with its many resources, but it has seen an increase in poverty recently because of a high rate of population growth with a high rate of unemployment. Some estimate that the number of Saudi Arabians living in poverty is between two and four million. This research aims to develop a way to detect poverty through remote sensing. The study area is Buraydah City, the largest city of the Qassim region, an important agricultural center that plays a significant role in the economy of Saudi Arabia. The research hypothesized that there are poor areas within …

Dynamic Relationship Study Between The Observed Seismicity And Spatiotemporal Pattern Of Lineament Changes In Palghar, North Maharashtra (India), Biswajit Nath, Ramesh P. Singh, Vineet K. Gahalaut, Ajay P. Singh

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

The Palghar region (north Maharashtra, India), located in the northwestern part of the stable continental region of India, experienced a low magnitude earthquake swarm, which was initiated in September 2018 and is continuing to date (as of October 2021). From December 2018 to December 2020, ~5000 earthquakes with magnitudes from M1.2 to M3.8 occurred in a small region of 20 × 10 km². These earthquakes were probably triggered by fluid migration during seasonal rainfall. In this study, we have used multi-temporal Landsat satellite data of the year 2000, 2015, 2018, 2019, and 2020, extracted lineaments, and studied the …

Assessment Of Vertical Accuracy From Uav-Lidar And Structure From Motion Point Clouds In Floodplain Terrain Mapping, Andrew Muller

Dissertations and Theses

Remote sensing technologies are being applied to a variety of uses because of the increase in access to various products (digital sensors, UAVs, software) and its ability to model relatively large areas in a short amount of time. While these new technologies are beginning to be adopted, validation of their merit in floodplain terrain mapping is lacking. The main goal of this study is to evaluate the vertical accuracy of digital elevation models (DEMs) generated with UAV-based LiDAR and Structure from Motion (SfM), also known as photographic LiDAR or PhoDAR. Airborne (manned aircraft) LiDAR has been applied to river research …

Progressive Destabilization And Triggering Mechanism Analysis Using Multiple Data For Chamoli Rockslide Of 7 February 2021, Wenfei Mao, Lixin Wu, Ramesh P. Singh, Yuan Qi, Busheng Xie, Yingjia Liu, Yifan Ding, Zilong Zhou, Jia Li

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

A catastrophic rockslide occurred on 7 February 2021 in Chamoli area in the high Himalaya. In the absence of field data, multiple satellites data of decade span have been used to investigate and understand the progressive destabilization of rockslide body. A 3D geometric model was developed using geospatial information about geology, terrain, and ice cover to understand the triggering mechanism. Several causes are uncovered as: the pronounced long-term change of land surface temperature facilitated local permafrost degradation and led to ice cover shrinking since 2010; the occurrence of ice avalanche nearby in 2016 accompanying with sidewall-to-bedrock fracturing enhanced the ice …

Impacts Of Sea-Level Rise On Urban Properties In Tampa Due To Climate Change, Weiwei Xie

Theses and Dissertations

The fast urbanization produces a large and growing population in coastal areas. However, the rise of sea level, one of the most significant impacts of global warming, makes coastal communities much more vulnerable to flooding than before. This Master’s thesis study investigates sea-level rise impacts on parcel-level property in the specific coastal city of Tampa, Florida, USA. An improved sea-level rise model based on satellite altimeter data is first used to predict future sea levels. Based on high-resolution LiDAR digital elevation data and property map, flooded properties are identified to evaluate property damage cost. This empirical analysis provides an in-depth …

Shipboard Lidar As A Tool For Remotely Measuring The Distribution And Bulk Characteristics Of Marine Particles, Brian Leigh Collister

OES Theses and Dissertations

Light detection and ranging (lidar) can provide remote estimates of the vertical distribution of optical properties in the ocean, potentially revolutionizing our ability to characterize the spatial structure of upper ocean ecosystems. However, challenges associated with quantifying the relationship between lidar measurements and biogeochemical properties of interest have prevented its adoption for routinely mapping the vertical structure of marine ecosystems. To address this, we developed a shipboard oceanographic lidar that measures attenuation (α) and linear depolarization (δ) at scales identical to those of in-water optical and biogeochemical measurements. The instrument’s ability to resolve the distribution of optical and biogeochemical properties …

Spatial-Temporal Modeling Of Agricultural Water Surface Features In Northeastern Arkansas., Daniel Dewayne Shults

Student Theses and Dissertations

The Mississippi River Valley Alluvial Aquifer (MRVA) has been the primary source of irrigation water in Northeastern Arkansas since the early 1900s. Over time the MRVA water level has declined due to over-pumping of farm wells and water restrictive geology. The aquifer is expected to continue declining but with water conservation strategies in place, this vital resource could be preserved for future farmers. This thesis investigated using remotely sensed data to assess landforms associated with agricultural water conservation across Northeastern Arkansas. The remotely sensed data proved to be useful at creating temporal assessments of pre-existing irrigation reservoirs, identifying new irrigation …

Pre-Earthquake Ionospheric Perturbation Identification Using Cses Data Via Transfer Learning, Pan Xiong, Cheng Long, Huiyu Zhou, Roberto Battiston, Angelo De Santis, Dimitar Ouzounov, Xuemin Zhang, Xuhui Shen

Mathematics, Physics, and Computer Science Faculty Articles and Research

During the lithospheric buildup to an earthquake, complex physical changes occur within the earthquake hypocenter. Data pertaining to the changes in the ionosphere may be obtained by satellites, and the analysis of data anomalies can help identify earthquake precursors. In this paper, we present a deep-learning model, SeqNetQuake, that uses data from the first China Seismo-Electromagnetic Satellite (CSES) to identify ionospheric perturbations prior to earthquakes. SeqNetQuake achieves the best performance [F-measure (F1) = 0.6792 and Matthews correlation coefficient (MCC) = 0.427] when directly trained on the CSES dataset with a spatial window centered on the earthquake epicenter with the Dobrovolsky …

Regional High-Resolution Benthic Habitat Data From Planet Dove Imagery For Conservation Decision-Making And Marine Planning, Steven R. Schill, Valerie Pietsch Mcnulty, F. Joseph Pollock, Fritjof Lüthje, Jiwei Li, David E. Knapp, Joe D. Kington, Trevor Mcdonald, George T. Raber, Ximena Escovar-Fadul, Gregory P. Asner

Faculty Publications

High-resolution benthic habitat data fill an important knowledge gap for many areas of the world and are essential for strategic marine conservation planning and implementing effective resource management. Many countries lack the resources and capacity to create these products, which has hindered the development of accurate ecological baselines for assessing protection needs for coastal and marine habitats and monitoring change to guide adaptive management actions. The PlanetScope (PS) Dove Classic SmallSat constellation delivers high-resolution imagery (4 m) and near-daily global coverage that facilitates the compilation of a cloud-free and optimal water column image composite of the Caribbean’s nearshore environment. These …

Pollinator Supplementation Mitigates Pollination Deficits In Smallholder Avocado (Persea Americana Mill.) Production Systems In Kenya, Rose Nyakemiso Sagwe, Marcell K. Peters, Thomas Dubois, Ingolf Steffan-Dewenter, H. Michael G. Lattorff

All Peer-Reviewed Publications

Avocado (Persea americana Mill.) is a major horticultural crop that relies on insect mediated pollination. In avocado production, a knowledge gap exists as to the importance of insect pollination, especially in East African smallholder farms. In this study, conducted in a leading smallholder avocado production region in Kenya, we assessed the dependence of avocado fruit set on insect pollination and whether current smallholder production systems suffer from a deficit in pollination services. Furthermore, we assessed if supplementation with colonies of the Western honey bee (Apis mellifera L.) to farms mitigated potential pollination deficits. Our results revealed a very high reliance …

Assessing The Vertical Displacement Of The Grand Ethiopian Renaissance Dam During Its Filling Using Dinsar Technology And Its Potential Acute Consequences On The Downstream Countries, Hesham El-Askary, Amr Fawzy, Rejoice Thomas, Wenzhao Li, Nicholas Lahaye, Erik Linstead, Thomas Piechota, Daniele Struppa, Mohamed Abdelaty Sayed

Mathematics, Physics, and Computer Science Faculty Articles and Research

The Grand Ethiopian Renaissance Dam (GERD), formerly known as the Millennium Dam, is currently under construction and has been filling at a fast rate without sufficient known analysis on possible impacts on the body of the structure. The filling of GERD not only has an impact on the Blue Nile Basin hydrology, water storage and flow but also poses massive risks in case of collapse. Rosaries Dam located in Sudan at only 116 km downstream of GERD, along with the 20 million Sudanese benefiting from that dam, would be seriously threatened in case of the collapse of GERD. In this …

Tracking The Change In The Number Of Residential Buildings Using Remote Sensing Techniques: A Case Study For An Area In The North Of Riyadh, Abdulaziz Aldegheishem, Nayef Alharbi

Emirates Journal for Engineering Research

This study aims to determine the urban expansion in a specific area in the north of the city of Riyadh using Remote Sensing techniques and Geographic Information Systems based on visuals and satellite images. The study seeks to determine the size of the increase in housing units in a selected area in the north of Riyadh during the period from 2007 to 2019 by studying the change in the number of residential buildings and comparing the changes that occurred during this period based on data extracted from high-resolution satellite images. Many programs have been used in correcting and balancing satellite …

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 …