Remote Sensing Commons^™

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 …

A Quantitative Validation Of Multi-Modal Image Fusion And Segmentation For Object Detection And Tracking, Nicholas Lahaye, Michael J. Garay, Brian D. Bue, Hesham El-Askary, Erik Linstead

Mathematics, Physics, and Computer Science Faculty Articles and Research

In previous works, we have shown the efficacy of using Deep Belief Networks, paired with clustering, to identify distinct classes of objects within remotely sensed data via cluster analysis and qualitative analysis of the output data in comparison with reference data. In this paper, we quantitatively validate the methodology against datasets currently being generated and used within the remote sensing community, as well as show the capabilities and benefits of the data fusion methodologies used. The experiments run take the output of our unsupervised fusion and segmentation methodology and map them to various labeled datasets at different levels of global …

Per-Pixel Cloud Cover Classification Of Multispectral Landsat-8 Data, Salome E. Carrasco, Torrey J. Wagner, Brent T. Langhals

Faculty Publications

Random forest and neural network algorithms are applied to identify cloud cover using 10 of the wavelength bands available in Landsat 8 imagery. The methods classify each pixel into 4 different classes: clear, cloud shadow, light cloud, or cloud. The first method is based on a fully connected neural network with ten input neurons, two hidden layers of 8 and 10 neurons respectively, and a single-neuron output for each class. This type of model is considered with and without L2 regularization applied to the kernel weighting. The final model type is a random forest classifier created from an ensemble of …

Using Uncrewed Aerial Vehicles For Identifying The Extent Of Invasive Phragmites Australis In Treatment Areas Enrolled In An Adaptive Management Program, Colin Brooks, Charlotte Weinstein, Andrew Poley, Amanda Grimm, Nicholas Marion, Laura Bourgeau-Chavez, Dana Hansen, Kurt Kowalski

Michigan Tech Publications, Part 1

Higher spatial and temporal resolutions of remote sensing data are likely to be useful for ecological monitoring efforts. There are many different treatment approaches for the introduced European genotype of Phragmites australis, and adaptive management principles are being integrated in at least some long-term monitoring efforts. In this paper, we investigated how natural color and a smaller set of near-infrared (NIR) images collected with low-cost uncrewed aerial vehicles (UAVs) could help quantify the aboveground effects of management efforts at 20 sites enrolled in the Phragmites Adaptive Management Framework (PAMF) spanning the coastal Laurentian Great Lakes region. We used object-based image …

Investigating Water Usage Patterns Tied To California State Water Project, Xiaoqing Wu

Publications and Research

California (USA) is the largest agricultural producer and one of the populous states in the United State. As the population and agriculture grows, water consumption patterns become crucial to keep track of especially surface water. In this research project, we studied possible changes in water consumption patterns in different counties and water rights holders who obtain surface water supply from the State Water Project (SWP) in California. We conducted a time series analysis on the California Monthly Diverted Surface Water dataset through two different time series forecasting models. Our analysis indicates that the total diverted surface water presents a periodic …

Downscaling Methodology For Satellite Land Surface Temperatures Over Urban Environments, Naved Khan, Ruben Vecino

Publications and Research

The objective of this study is to develop high spatial and temporal resolution Land Surface Temperature (LST) data using a combination of Landsat 8, infrared satellite sensors such as the Moderate Resolution Imaging Spectroradiometer (MODIS), and the Geostationary Operational Environmental Satellite-R Series (GOES-16). The Landsat 8 Thermal Infrared Sensor (TIRS) provides higher spatial resolution (30 m) estimates of skin temperature every 16 days. MODIS makes daytime and nighttime observations of the Earth’s thermal emission at a coarser spatial resolution (1000 m), while GOES-16, which has lower spatial resolution (2 km), measures the skin temperature at a much higher temporal resolution …

The Role Of Elevation As A Control On Salt Marsh-Upland Ecotones Along The Mississippi Gulf Coast, Carlton P. Anderson

Dissertations

Salt marshes are critical ecological gems that serve as habitat for many specialized species of flora and fauna, while providing a natural buffer to human populations from tropical cyclone impacts. However, rises growth of coastal populations has led to greater strain on the natural services these ecosystems provide. To better understand and project the future of coastal evolution, the physical, mechanical, and biological feedbacks between the natural and human coupled systems need to be more defined and thoroughly understood. Human encroachment towards naturally retreating shorelines will lead to coastal communities being more susceptible to nuisance tidal flooding and minor tropical …

Monitoring White-Tailed Deer Abundance And Habitat Selection In The Albany Pine Bush Preserve Using Unmanned Aerial Systems, Christopher Plummer

Legacy Theses & Dissertations (2009 - 2024)

Unmanned aerial systems (UAS) have seen recent advancements in technology that gave rise to their increasing use in recreational and commercial application, including wildlife conservation. Adaptive management is a must for wildlife conservation, with the goal of learning from management decisions to improve future management strategies, especially in the face of growing human related stressors such as climate change and habitat loss. Monitoring is a critical step for adaptive management, as it allows the manger to learn about the ecology of the natural system and quantify the impacts of management strategies. Species and habitats are frequently monitored for wildlife conservation …

Kaleidoscope Of Urban Evapotranspiration: Exploring The Science And Modeling Approaches, Rubab Saher

UNLV Theses, Dissertations, Professional Papers, and Capstones

Urban evapotranspiration is a complex physical process. It depends on various critical drivers, including the land surface temperature (LST), surface albedo, landscape types, and building orientations. All of these factors create difficulties in the estimation of evapotranspiration (ET) by changing the microclimate conditions. The literature has oversimplified microclimate conditions by considering temperature difference as the only variable defining climate. The physical process depends on land-use changes, building proximities, and landscape types. This study devised three objectives to understand the microclimate effects on ET.

In the first objective, land-use change effects on LST, surface albedo, and ET were analyzed over a …

Estimation Of Spatial Change In Cropland Area And Evaluation Of Irrigation Performance In Imperial Valley Using Remotely Sensed Data, Usha Poudel

UNLV Theses, Dissertations, Professional Papers, and Capstones

The Imperial Valley (IV) in the US is an extensively irrigated agricultural region, which includes multiple crops changing on an annual and semiannual basis. The valley is facing grave concerns about water management due to its semi-arid environment, water intensive crops, and limited water supply. A simple, inexpensive, and repeatable method to detect changes in cropping patterns may assist irrigation managers to understand crop diversification and associated consumptive use. In addition, a spatial assessment of existing water irrigation system performance and productivity is crucial to benchmark and improve current water management strategies. This thesis estimates the spatial pattern of change …

Climatic Controls On The Kinematics Of The Hooskanaden Landslide, Curry County, Oregon, Kara Kingen

Dissertations and Theses

Slow-moving earthflows represent major sources of sediment transport and erosion and are problematic for the management of critical infrastructure. The Hooskanaden Landslide -- a slow-moving earthflow on the southwest coast of Oregon -- crosses US Highway 101 and has been a site of continued interest to the Oregon Department of Transportation (ODOT) due to the weak lithology, erosive environment, and recurrent surge behavior (every ~15 years). Past surges, including the most recent (2019), have occurred during the winter, suggesting that velocity changes are predominantly controlled by climatic inputs. To examine the response of the Hooskanaden Landslide to seasonal and other …

Understanding The Effect Of Internal Climate Variability On 20th Century Indian Ocean Sea Level: Results From Newly Reconstructed Sea Level Data, Praveen Kumar

OES Theses and Dissertations

Densely populated low-lying coastal zones of countries that border the Indian Ocean are at risk due to sea level rise. However, sea level change in the Indian Ocean is poorly understood primarily due to short and sparse tide gauge observations. Although satellite altimetry provides accurate basin-wide sea level measurements, trends computed from its relatively short (~27-year) data record are heavily influenced by interannual to multi-decadal variability. To accurately project future Indian Ocean sea level trends using altimeter data it is imperative that trends associated with fluctuating internal variability (interannual-decadal) be identified and extracted, which in turn requires long (~100-year) data. …

Investigating Decadal Changes Of Multiple Hydrological Products And Land-Cover Changes In The Mediterranean Region For 2009–2018, Wenzhao Li, Sachi Perera, Erik Linstead, Rejoice Thomas, Hesham El-Askary, Thomas Piechota, Daniele Struppa

Mathematics, Physics, and Computer Science Faculty Articles and Research

Land-cover change is a critical concern due to its climatic, ecological, and socioeconomic consequences. In this study, we used multiple variables including precipitation, vegetation index, surface soil moisture, and evapotranspiration obtained from different satellite sources to study their association with land-cover changes in the Mediterranean region. Both observational and modeling data were used for climatology and correlation analysis. Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS) and Global Land Data Assimilation System (GLDAS) were used to extract surface soil moisture and evapotranspiration data. Intercomparing the results of FLDAS and GLDAS suggested that FLDAS data had better …

Evaluation Of Manual And Semi-Automated Deep-Seated Landslide Inventory Processes: Willapa Hills, Washington, Tiffany E. Justice

Dissertations and Theses

Recent advances in remote sensing data and technology have allowed for computational models to be designed that successfully extract landforms from the landscape. The goal of this work is to create one such semi-automated model to extract deep-seated landslides located in complex geomorphic terrain. This is accomplished using geographic object-based image analysis (GEOBIA) techniques, considered by leaders in the field of image analysis to have an advantage over traditional automated classification methods. GEOBIA methods can mimic human visual interpretation by including more characteristic features used to assess the relationship between image data and the ground surface such as color reflectance …

Diurnal Cycle Of Passive Microwave Brightness Temperatures Over Land At A Global Scale, Zahra Sharifnezhad, Hamid Norouzi, Satya Prakash, Reginald Blake, Reze Khanbilvard

Publications and Research

Satellite-borne passive microwave radiometers provide brightness temperature (TB) measurements in a large spectral range which includes a number of frequency channels and generally two polarizations: horizontal and vertical. These TBs are widely used to retrieve several atmospheric and surface variables and parameters such as precipitation, soil moisture, water vapor, air temperature profile, and land surface emissivity. Since TBs are measured at different microwave frequencies with various instruments and at various incidence angles, spatial resolutions, and radiometric characteristics, a mere direct integration of them from different microwave sensors would not necessarily provide consistency. However, when appropriately harmonized, they can provide a …

An Assessment Of The Filling Process Of The Grand Ethiopian Renaissance Dam And Its Impact On The Downstream Countries, Prakrut Kansara, Wenzhao Li, Hesham El-Askary, Venkat Lakshmi, 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, has been filling at a fast rate. This project has created issues for the Nile Basin countries of Egypt, Sudan, and Ethiopia. The filling of GERD has an impact on the Nile Basin hydrology and specifically the water storages (lakes/reservoirs) and flow downstream. In this study, through the analysis of multi-source satellite imagery, we study the filling of the GERD reservoir. The time-series generated using Sentinel-1 SAR imagery displays the number of classified water pixels in the dam from early June 2017 to September 2020, indicating a contrasting …

Multi-Source Eo For Dynamic Wetland Mapping And Monitoring In The Great Lakes Basin, Michael Battaglia, Sarah Banks, Amir Behnamian, Laura Bourgeau-Chavez

Michigan Tech Publications, Part 1

Wetland managers, citizens and government leaders are observing rapid changes in coastal wetlands and associated habitats around the Great Lakes Basin due to human activity and climate variability. SAR and optical satellite sensors offer cost effective management tools that can be used to monitor wetlands over time, covering large areas like the Great Lakes and providing information to those making management and policy decisions. In this paper we describe ongoing efforts to monitor dynamic changes in wetland vegetation, surface water extent, and water level change. Included are assessments of simulated Radarsat Constellation Mission data to determine feasibility of continued monitoring …

Statistical Analysis And Comparison Of Optical Classification Of Atmospheric Aerosol Lidar Data, Mohammed Alqawba, Norou Diawara, Kwasi G. Afrifa, Mohamed I. Elbakary, Mecit Cetin, Khan Iftekharuddin

Mathematics & Statistics Faculty Publications

In this article, we present a new study for the analysis and classification of atmospheric aerosols in remote sensing LIDAR data. Information on particle size and associated properties are extracted from these remote sensing atmospheric data which are collected by a ground-based LIDAR system. This study first considers optical LIDAR parameter-based classification methods for clustering and classification of different types of harmful aerosol particles in the atmosphere. Since accurate methods for aerosol prediction behaviors are based upon observed data, computational approaches must overcome design limitations, and consider appropriate calibration and estimation accuracy. Consequently, two statistical methods based on generalized linear …

Towards Advancing The Earthquake Forecasting By Machine Learning Of Satellite Data, Pan Xiong, Lei Tong, Kun Zhang, Xuhui Shen, Roberto Battiston, Dimitar Ouzounov, Roberto Iuppa, Danny Crookes, Cheng Long, Huyui Zhou

Mathematics, Physics, and Computer Science Faculty Articles and Research

Earthquakes have become one of the leading causes of death from natural hazards in the last fifty years. Continuous efforts have been made to understand the physical characteristics of earthquakes and the interaction between the physical hazards and the environments so that appropriate warnings may be generated before earthquakes strike. However, earthquake forecasting is not trivial at all. Reliable forecastings should include the analysis and the signals indicating the coming of a significant quake. Unfortunately, these signals are rarely evident before earthquakes occur, and therefore it is challenging to detect such precursors in seismic analysis. Among the available technologies for …

Rapid Mapping Of Landslides In The Western Ghats (India) Triggered By 2018 Extreme Monsoon Rainfall Using A Deep Learning Approach, Sansar Raj Meena, Omid Ghorbanzadeh, Cees J. Van Westen, Thimmaiah Gudiyangada Nachappa, Thomas Blaschke, Ramesh P. Singh, Raju Sarkar

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Rainfall-induced landslide inventories can be compiled using remote sensing and topographical data, gathered using either traditional or semi-automatic supervised methods. In this study, we used the PlanetScope imagery and deep learning convolution neural networks (CNNs) to map the 2018 rainfall-induced landslides in the Kodagu district of Karnataka state in theWestern Ghats of India.We used a fourfold cross-validation (CV) to select the training and testing data to remove any random results of the model. Topographic slope data was used as auxiliary information to increase the performance of the model. The resulting landslide inventory map, created using the slope data with the …

Modelling Acoustics In Ancient Maya Cities: Moving Towards A Synesthetic Experience Using Gis & 3d Simulation, Graham Goodwin, Heather Richards-Rissetto

Department of Anthropology: Faculty Publications

Archaeological analyses have successfully employed 2D and 3D tools to measure vision and movement within cityscapes; however, built environments are often designed to invoke synesthetic experiences. GIS and Virtual Reality (VR) now enable archaeologists to also measure the acoustics of ancient spaces. To move toward an understanding of synesthetic experience in ancient Maya cities, we employ GIS and 3D modelling to measure sound propagation and reverberation using the main civic-ceremonial complex in ancient Copán as a case study. For the ancient Maya, sight and sound worked in concert to create ritually-charged atmospheres and architecture served to shape these experiences. Together …

Quantifying The Impacts Of Land Use, Management And Climate Change On Water Resources In Missouri River Basin, Arun Bawa

Electronic Theses and Dissertations

A location-specific evaluation of hydrological landscape responses concerning past and projected climate and land use land cover (LULC) changes can provide a powerful intellectual basis for developing efficient and profitable agroecosystems, and overcoming uncertain and detrimental consequences of LULC and climate shifts. This dissertation assessed the impacts of land use, management, and climate change on water resources in the Missouri River Basin (MRB) through four specific studies that included: (i) to study the responses of leached nutrient concentrations and soil health to winter rye cover crop (CC) under no-till corn (Zea mays L.)-soybean [Glycine max (L.) Merr.] rotation, (ii) to …

Assessing And Forecasting Chlorophyll Abundances In Minnesota Lake Using Remote Sensing And Statistical Approaches, Ben Von Korff

All Graduate Theses, Dissertations, and Other Capstone Projects

Harmful algae blooms (HABs) can negatively impact water quality, lake aesthetics, and can harm human and animal health. However, monitoring for HABs is rare in Minnesota. Detecting blooms which can vary spatially and may only be present briefly is challenging, so expanding monitoring in Minnesota would require the use of new and cost efficient technologies. Unmanned aerial vehicles (UAVs) were used for bloom mapping using RGB and near-infrared imagery. Real time monitoring was conducted in Bass Lake, in Faribault County, MN using trail cameras. Time series forecasting was conducted with high frequency chlorophyll-a data from a water quality sonde. Normalized …

A Karst Feature Prediction Model For Prince Of Wales Island, Alaska Based On High Resolution Lidar Imagery, Alexander Lyles

Master's Theses or Doctor of Nursing Practice

Investigation into surface karst formation is significant to hazard prediction, hydrogeologic drainage, and land management. Southeast Alaska contains over 600,000 acres of mapped carbonate bedrock, and some of the fastest recorded karst dissolution in the world. The objectives of this study are to develop and compare multiple semi-automated models to map and delineate karst features from bare-earth LiDAR imagery using ArcGIS Desktop 10.7, and to apply a preliminary geostatistical analysis of sinkhole morphometric parameters to highlight potential spatial patterns of karst evolution on Prince of Wales Island, Alaska. A semi-automated approach of mapping karst features provides a dataset that minimizes …

The Kiwanis Site: A Multi-Method Geophysical Approach To Investigating Mound Features, Luke Burds

All Graduate Theses, Dissertations, and Other Capstone Projects

Subtle mound-like landforms can be genetically ambiguous features within a landscape. A variety of geomorphological and anthropological processes can result in these equifinal forms being difficult to interpret. Being able to reliably and noninvasively differentiate them is important for legal as well as cultural and spiritual reasons. A suite of non-invasive geophysical methods were thus used on mounds at the Kiwanis site in western Wisconsin in order to determine if culturally diagnostic indicators could be recorded in geophysical data. Genesis of these mounds is ambiguous given the presence of aeolian landforms in immediate proximity. As a control, the same geophysical …