Physical Sciences and Mathematics Commons^™

Climate Change-Associated Declines In Water Clarity Impair Feeding By Common Loons, Walter H. Piper, Max R. Glines, Kevin C. Rose

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Climate change has myriad impacts on ecosystems, but the mechanisms by which it affects individual species can be difficult to pinpoint. One strategy to discover such mechanisms is to identify a specific ecological factor related to survival or reproduction and determine how that factor is affected by climate. Here we used Landsat imagery to calculate water clarity for 127 lakes in northern Wisconsin from 1995 to 2021 and thus investigate the effect of clarity on the body condition of an aquatic visual predator, the common loon (Gavia immer). In addition, we examined rainfall and temperature as potential predictors …

Quantifying Current Soil Brine Contamination Within The Smackover Oil Field In Arkansas Using Multispectral Digital Imagery, Victoria Williams

Electronic Theses and Dissertations

A remote sensing study was performed to quantify current soil brine contamination across the historic Smackover Oil Field in south-central Arkansas, United States. The oil field was established in 1922 and was not subject to the future waste regulations created by the Arkansas Oil and Gas Commission. Brine is a waste product of oil manufacturing which contains water with high salt levels. The storage and transport of brine in the oil field created landscape scarring across the study area.

Landsat 9 multispectral digital imagery was utilized to create supervised classification maps based on earthen pits and creek scarring across the …

Using Landsat Imagery To Analyse Land Cover Change In The Njoro Watershed, Kenya, T. J. Baldyga, S. N. Miller, K. L. Driese, C. Maina-Gichaba

IGC Proceedings (1997-2023)

In developing nations where resources are scarce and increased population pressures create stress on available resources, methods are needed to examine effects of human migration and resultant changes in land cover. Widespread availability and low cost of remotely sensed imagery and Geographic Information Systems (GIS) are making such methods a reality to develop quantitative resource mapping and land cover change detection in developing nations (Sheng et al., 1997). However, difficulties arise in tropical regions when trying to analyse traditional vegetation bands (Bands 3 and 4), or indices such as NDVI because saturated pixels limit spectral distinction.

Modeling Growth And Stress Factors For Converted Silvopasture Systems In The Missouri Ozarks, Bailee N. Suedmeyer

MSU Graduate Theses

Silvopasture systems are becoming increasingly popular among sustainable agriculture ranchers, due to the increase in knowledge of benefits to the cattle and ability to grow cool season grasses beneath the canopy. This project focuses on the forest crop aspect of silvopasture systems from monitoring of the health of the trees over time to recommendations for thinning management to keep it functioning as viable silvopasture. The study site consists of five acres of upland hardwood forest area in Southern Missouri with 18 monumented fixed area plots. Arial and ground data was collected at each plot throughout the growing season, along with …

Evaluating Optical Remote Sensing Methods For Estimating Leaf Area Index For Corn And Soybean, Rohit Nandan, Varaprasad Bandaru, Jiaying He, Craig Daughtry, Prasanna Gowda, Andrew E. Suyker

School of Natural Resources: Faculty Publications

The leaf area index (LAI) is a key crop biophysical variable influencing many vegetation processes. Spatial LAI estimates are essential to develop and improve spatial modeling tools to monitor vegetation conditions at large regional scales. Numerous optical remote sensing methods have been explored to retrieve crop-specific LAI at a regional scale using satellite observations. However, a major challenge is selecting a method that performance well under various conditions without local scale calibration. As such, we assessed the performance of existing statistical and physical approaches, developed based on parametric, non-parametric and radiative transfer model (RTM)-look-up-table based inversion, using field observations from …

Greater Loss And Fragmentation Of Savannas Than Forests Over The Last Three Decades In Yunnan Province, China, R Sedricke Lapuz, Angelica Kristina M. Jaojoco, Sheryl Rose C. Reyes, Jose Don T. De Alban, Kyle W. Tomlinson

SOSE Affiliate: Manila Observatory

Yunnan Province, southwest China, has a monsoonal climate suitable for a mix of fire-driven savannas and fire-averse forests as alternate stable states, and has vast areas with savanna physiognomy. Presently, savannas are only formally recognised in the dry valleys of the region, and a no-fire policy has been enforced nationwide since the 1980s. Misidentification of savannas as forests may have contributed to their low protection level and fire-suppression may be contributing to vegetation change towards forest states through woody encroachment. Here, we present an analysis of vegetation and land-use change in Yunnan for years 1986, 1996, 2006, and 2016 by …

Temporal Stability Of Seagrass Extent, Leaf Area, And Carbon Storage In St. Joseph Bay, Florida: A Semi-Automated Remote Sensing Analysis, Marie Cindy Lebrasse, Blake A. Schaeffer, Megan M. Coffer, Peter J. Whitman, Richard C. Zimmerman, Victoria J. Hill, Kazi A. Islam, Jiang Li, Christopher L. Osburn

OES Faculty Publications

Seagrasses are globally recognized for their contribution to blue carbon sequestration. However, accurate quantification of their carbon storage capacity remains uncertain due, in part, to an incomplete inventory of global seagrass extent and assessment of its temporal variability. Furthermore, seagrasses are undergoing significant decline globally, which highlights the urgent need to develop change detection techniques applicable to both the scale of loss and the spatial complexity of coastal environments. This study applied a deep learning algorithm to a 30-year time series of Landsat 5 through 8 imagery to quantify seagrass extent, leaf area index (LAI), and belowground organic carbon (BGC) …

Monitoring Agroecosystem Productivity And Phenology At A National Scale: A Metric Assessment Framework, Dawn M. Browning, Eric S. Russell, Guillermo E. Ponce-Campos, Nicole Kaplan, Andrew D. Richardson, Bijan Seyednasrollah, Sheri Spiegal, Nicanor Saliendra, Joseph G. Alfieri, John Baker, Carl Bernacchi, Brandon T. Bestelmeyer, David Bosch, Elizabeth H. Boughton, Raoul K. Boughton, Pat Clark, Gerald Flerchinger, Nuria Gomez-Casanovas, Sarah Goslee, Nick M. Haddad, David Hoover, Abdullah Jaradat, Marguerite Mauritz, Gregory W. Mccarty, Gretchen R. Miller, John Sadler, Amartya Saha, Russell L. Scott, Andrew Suyker, Craig Tweedie, Jeffrey D. Wood, Xukai Zhang, Shawn D. Taylor

School of Natural Resources: Faculty Publications

Effective measurement of seasonal variations in the timing and amount of production is critical to managing spatially heterogeneous agroecosystems in a changing climate. Although numerous technologies for such measurements are available, their relationships to one another at a continental extent are unknown. Using data collected from across the Long-Term Agroecosystem Research (LTAR) network and other networks, we investigated correlations among key metrics representing primary production, phenology, and carbon fluxes in croplands, grazing lands, and crop-grazing integrated systems across the continental U.S. Metrics we examined included gross primary productivity (GPP) estimated from eddy covariance (EC) towers and modelled from the Landsat …

Monitoring Agroecosystem Productivity And Phenology At A National Scale: A Metric Assessment Framework, Dawn M. Browning, Eric S. Russell, Guillermo E. Ponce-Campos, Nicole Kaplan, Andrew D. Richardson, Bijan Seyednasrollah, Sheri Spiegal, Nicanor Saliendra, Joseph G. Alfieri, John Baker, Carl Bernacchi, Brandon T. Bestelmeyer, David Bosch, Elizabeth H. Boughton, Raoul K. Boughton, Pat Clark, Gerald Flerchinger, Nuria Gomez-Casanovas, Sarah Goslee, Nick M. Haddad, David Hoover, Abdullah Jaradat, Marguerite Mauritz, Gregory W. Mccarty, Gretchen R. Miller, John Sadler, Amartya Saha, Russell L. Scott, Andrew Suyker, Craig Tweedie, Jeffrey D. Wood, Xukai Zhang, Shawn D. Taylor

School of Natural Resources: Faculty Publications

Effective measurement of seasonal variations in the timing and amount of production is critical to managing spatially heterogeneous agroecosystems in a changing climate. Although numerous technologies for such measurements are available, their relationships to one another at a continental extent are unknown. Using data collected from across the Long-Term Agroecosystem Research (LTAR) network and other networks, we investigated correlations among key metrics representing primary production, phenology, and carbon fluxes in croplands, grazing lands, and crop-grazing integrated systems across the continental U.S. Metrics we examined included gross primary productivity (GPP) estimated from eddy covariance (EC) towers and modelled from the Landsat …

Temporal And Spatial Evolution Of Surface Thermal Environment In Huainan Mining Area In The Last Decade, Fang Liangcheng, Chen Yongchun, An Shikai, Xu Yanfei, Zhao Yuejiao, Wang Ning, Li Zhihui, Zhao Ping

Coal Geology & Exploration

Temporal and spatial evolution of surface thermal environment in Huainan Mining Area in the last decade

Examining Satellite Images Market Stability Using The Records Theory: Evidence From French Spatial Data Infrastructures, Chadi Jabbour, Anis Hoayek, Pierre Maurel, Zaher Khraibani, Latifa Ghalayini

Journal of Spatial Information Science

The spatial data infrastructures (SDIs) which constitute a direct link between spatial data users and the large Earth observation industry, have a leading role in establishing market opportunities in the space sector. The spatial information supplied through various forms of SDI platforms exhibits large increases in demand volatility. The users' demand is unpredictable and the market is vulnerable to high evolution shifts. We study the effect of extreme demands for a particular type of spatial information, the satellite images. Drawing on two French SDIs, GEOSUD and PEPS, we examine the shifts occurring on their platforms and assess the probability of …

Improving Landsat Predictions Of Rangeland Fractional Cover With Multi-Task Learning And Uncertainty, B.W. Allred, B. Bestelmeyer, C.S. Boyd, C. Brown, K.W. Davies, M. Ellsworth, T. Erickson, S.D. Fuhlendorf, T.V. Griffiths, V. Jansen, M.O. Jones, J. Karl, A. Knight, J.D. Maestas, J.J. Maynard, S.E. Mccord, D.E. Naugle, H.D. Starns, D. Twidwell, D.R. Uden

School of Natural Resources: Faculty Publications

No abstract provided.

Aquatic Habitat Changes Within The Channelized And Impounded Arkansas River, Arkansas, Usa, Jonathan J. Spurgeon, Mike Rhodes, J. Wesley Neal, Kristine O. Evans

School of Natural Resources: Faculty Publications

River-wide changes in morphologic character following channelization and impoundment alter the occurrence and distribution of surface water and available habitats for aquatic organisms. Quantifying patterns of creation, redistribution or disappearance of habitats at river-wide and decadal spatiotemporal scales can promote understanding regarding trajectories of different habitat types following alteration and prospects of direct habitat enhancement projects within altered alluvial rivers. Newly available remote-sensing tools and databases may improve detection of river-wide changes in habitat through time. We used a combination of remote-sensing data and generalized linear models to assess changes in surface water coverage from 1984 to 2015 among aquatic …

Satellite-Based Phenology Analysis In Evaluating The Response Of Puerto Rico And The United States Virgin Islands' Tropical Forests To The 2017 Hurricanes, Melissa Collin

Cal Poly Humboldt theses and projects

The functionality of tropical forest ecosystems and their productivity is highly related to the timing of phenological events. Understanding forest responses to major climate events is crucial for predicting the potential impacts of climate change. This research utilized Landsat satellite data and ground-based Forest Inventory and Analysis (FIA) plot data to investigate the dynamics of Puerto Rico and the U.S. Virgin Islands’ (PRVI) tropical forests after two major hurricanes in 2017. Analyzing these two datasets allowed for validation of the remote sensing methodology with field data and for the investigation of whether this is an appropriate approach for estimating forest …

Long-Term Ndvi And Recent Vegetation Cover Profiles Of Major Offshore Island Nesting Sites Of Sea Turtles In Saudi Waters Of The Northern Arabian Gulf, Rommel H. Maneja, Jeffrey D. Miller, Wenzhao Li, Hesham El-Askary, Ace Vincent B. Flandez, Joshua J. Dagoy, Joselito Francis A. Alcaria, Abdullajid U. Basali, Khaled A. Al-Abdulkader, Ronald A. Loughland, Mohamed A. Qurban

Mathematics, Physics, and Computer Science Faculty Articles and Research

Vegetation is an important ecological component of offshore islands in the Arabian Gulf (AG), which maintains long-term resilience of these islands. This is achieved by influencing sediment retention and moisture acquisition via condensation during periods of high humidity and by providing a variety of microhabitats for island fauna. The resilience of offshore islands’ ecosystems in the Saudi waters is important because they host the largest number of nesting hawksbill and green turtles in the AG. This study defines the characteristics and the long-term trends in vegetation cover of the offshore islands used by sea turtles as nesting grounds in the …

Global Production And Free Access To Landsat-Scale Evapotranspiration With Eeflux And Eemetric, Ayse Kilic, R G. Allen, Philip A. Blankenau, Peter Revelle, Doruk Ozturk, Justin L. Huntington

School of Natural Resources: Faculty Publications

EEFlux (Earth Engine Evapotranspiration Flux) is a version of the METRIC (mapping evapotranspiration at high resolution with internal calibration) application that operates on the Google Earth Engine (EE). EEFlux has a web-based interface and provides free public access to transform Landsat images into 30 m spatial evapotranspiration (ET) data for terrestrial land areas around the globe. EE holds the entire Landsat archive to power EEFlux along with NLDAS/CFSV2 gridded weather data for estimating reference ET. EEFlux is a part of the upcoming OpenET platform (https://openetdata.org/ ) that has leveraged nonprofit funding to provide ET information to all of the lower …

Change Points Detected In Decadal And Seasonal Trends Of Outlet Glacier Terminus Positions Across West Greenland, Ashley V. York, Karen E. Frey, Sadegh Jamali, Sarah B. Das

Geography

We investigated the change in terminus position between 1985 and 2015 of 17 marine-terminating glaciers that drain into Disko and Uummannaq Bays, West Greenland, by manually digitizing over 5000 individual frontal positions from over 1200 Landsat images. We find that 15 of 17 glacier termini retreated over the study period, with ~80% of this retreat occurring since 2000. Increased frequency of Landsat observations since 2000 allowed for further investigation of the seasonal variability in terminus position. We identified 10 actively retreating glaciers based on a significant positive relationship between glaciers with cumulative retreat >300 m since 2000 and their average …

Coral Reef Change Detection In Remote Pacific Islands Using Support Vector Machine Classifiers, Justin J. Gapper, Hesham El-Askary, Erik Linstead, Thomas Piechota

Mathematics, Physics, and Computer Science Faculty Articles and Research

Despite the abundance of research on coral reef change detection, few studies have been conducted to assess the spatial generalization principles of a live coral cover classifier trained using remote sensing data from multiple locations. The aim of this study is to develop a machine learning classifier for coral dominated benthic cover-type class (CDBCTC) based on ground truth observations and Landsat images, evaluate the performance of this classifier when tested against new data, then deploy the classifier to perform CDBCTC change analysis of multiple locations. The proposed framework includes image calibration, support vector machine (SVM) training and tuning, statistical assessment …

Repairing Landsat Satellite Imagery Using Deep Machine Learning Techniques, Griffin J. Lane, Patricia Goresen, Robert Slater

SMU Data Science Review

Satellite Imagery is one of the most widely used sources to analyze geographic features and environments in the world. The data gathered from satellites are used to quantify many vital problems facing our society, such as the impact of natural disasters, shore erosion, rising water levels, and urban growth rates. In this paper, we construct machine learning and deep learning algorithms for repairing anomalies in the Landsat satellite imagery data which arise for various reasons ranging from cloud obstruction to satellite malfunctions. The accuracy of GIS data is crucial to ensuring the models produced from such data are as close …

Optimal Algorithms For Deriving Estimates Of Phytoplankton Biomass In Lakes From Landsat Satellite Imagery, Michael A. Dallosch

Electronic Thesis and Dissertation Repository

The frequency, intensity, and geographical distribution of harmful phytoplankton blooms are on the rise globally. There is a scientific need for estimates of historical and current phytoplankton data. This research develops mathematical algorithms for accurate assessment of surface chlorophyll-a (chl-a), a proxy for phytoplankton biomass, within freshwater lakes. Landsat satellite images (4-5 TM, 7 ETM and 8 OLI) were used to create predictive models (from 1984 to 2017) for seven ecoregions (ranging from the tropics to arctic). Correlation tests for 82 algorithms were conducted to establish the best fit models (linear, exponential, logarithmic, power) for chl-a …

Using Multi-Indices Approach To Quantify Mangrove Changes Over The Western Arabian Gulf Along Saudi Arabia Coast, Wenzhao Li, Hesham El-Askary, Mohamed A. Qurban, Jingjing Li, K. P. Manikandan, Thomas Piechota

Mathematics, Physics, and Computer Science Faculty Articles and Research

Mangroves habitat present an important resource for large coastal communities benefiting from activities such as fisheries, forest products and clean water as well as protection against coastal erosion and climate related extreme events. Yet they are increasingly threatened by natural pressure and anthropogenic activities. We observed an inaccurate distribution of mangroves over the Western Arabian Gulf (WAG) which is a vital habitat and resource for the local ecosystem, according to the United Stated Geological Survey (USGS) mangrove database through spectral analysis. Change detection analysis is conducted on mangrove forests along the Saudi Arabian coast of the WAG for the years …

Change Detection Using Landsat And Worldview Images, Chiman Kwan, Bryan Chou, Leif Hagen, Daniel Perez, Yuzhong Shen, Jiang Li, Krzysztof Koperski

Computational Modeling & Simulation Engineering Faculty Publications

This paper presents some preliminary results using Landsat and Worldview images for change detection. The studied area had some significant changes such as construction of buildings between May 2014 and October 2015. We investigated several simple, practical, and effective approaches to change detection. For Landsat images, we first performed pansharpening to enhance the resolution to 15 meters. We then performed a chronochrome covariance equalization between two images. The residual between the two equalized images was then analyzed using several simple algorithms such as direct subtraction and global Reed-Xiaoli (GRX) detector. Experimental results using actual Landsat images clearly demonstrated that the …

How Are Interannual Variations Of Land Surface Phenology In The Highland Pastures Of Kyrgyzstan Modulated By Terrain, Snow Cover Seasonality, And Climate Oscillations? An Investigation Using Multi-Source Remote Sensing Data, Monika Anna Tomaszewska

Electronic Theses and Dissertations

In the semiarid, continental climates of montane Central Asia, with its constant moisture deficit and low relative humidity, agropastoralism constitutes the foundation of the rural economy. In Kyrgyzstan, an impoverished, landlocked republic in Central Asia, herders of the highlands practice vertical transhumance—the annual movement of livestock to higher elevation pastures to take advantage of seasonally available forage resources. Dependency on pasture resource availability during the short mountain growing season makes herds and herders susceptible to changing weather and climate patterns. This dissertation focuses on using remote sensing observations over the highland pastures in Kyrgyzstan to address five interrelated topics: (i) …

Utilization Of Various Methods And A Landsat Ndvi/Google Earth Engine Product For Classifying Irrigated Land Cover, Andrew Nemecek

Graduate Student Theses, Dissertations, & Professional Papers

Methods for classifying irrigated land cover are often complex and not quickly reproducible. Further, moderate resolution time-series datasets have been consistently utilized to produce irrigated land cover products over the past decade, and the body of irrigation classification literature contains no examples of subclassification of irrigated land cover by irrigation method. Creation of geospatial irrigated land cover products with higher resolution datasets could improve reliability, and subclassification of irrigation by method could provide better information for hydrologists and climatologists attempting to model the role of irrigation in the surface-ground water cycle and the water-energy balance. This study summarizes a simple, …

Assessing Responses Of Betula Papyrifera To Climate Variability In A Remnant Population Along The Niobrara River Valley In Nebraska U.S. Through Dendroecological And Remote Sensing Techniques, Evan Bumann, Tala Awada, Brian Wardlow, Michael Hayes, Jane A. Okalebo, C. Helzer, Anastasios Mazis, J. Hiller, Paolo Cherubini

School of Natural Resources: Faculty Publications

Remnant populations of Betula papyrifera have persisted in the Great Plains after the Wisconsin Glaciation along the Niobrara River Valley, Nebraska. Population health has declined in recent years, and has been hypothesized to be due to climate change. We used dendrochronological techniques to assess the response of B. papyrifera to microclimate (1950-2014), and satellite imagery [Landsat 5 TM (1985-2011) and MODIS (2000-2014)] derived NDVI as a proxy for population health. Growing-season streamflow and precipitation were positively correlated with raw and standardized tree-ring widths and basal area increment increase. Increasing winter and spring temperatures were unfavorable for tree growth while increasing …

Estimating The Creation And Removal Date Of Fracking Ponds Using Trend Analysis Of Landsat Imagery, Rutherford V. Platt, David Manthos, John Amos

Environmental Studies Faculty Publications

Hydraulic fracturing, or fracking, is a process of introducing liquid at high pressure to create fractures in shale rock formations, thus releasing natural gas. Flowback and produced water from fracking operations is typically stored in temporary open-air earthen impoundments, or frack ponds. Unfortunately, in the United States there is no public record of the location of impoundments, or the dates that impoundments are created or removed. In this study we use a dataset of drilling-related impoundments in Pennsylvania identified through the FrackFinder project led by SkyTruth, an environmental non-profit. For each impoundment location, we compiled all low cloud Landsat imagery …

Field-Scale Mapping Of Evaporative Stress Indicators Of Crop Yield: An Application Over Mead, Ne, Usa, Yang Yang, Martha C. Anderson, Feng Gao, Brian D. Wardlow, Christopher R. Hain, Jason A. Otkin, Joseph Alfieri, Yun Yang, Liang Sun, Wayne Dulaney

School of Natural Resources: Faculty Publications

The Evaporative Stress Index (ESI) quantifies temporal anomalies in a normalized evapotranspiration (ET) metric describing the ratio of actual-to-reference ET (f_RET) as derived from satellite remote sensing. At regional scales (3–10 km pixel resolution), the ESI has demonstrated the capacity to capture developing crop stress and impacts on regional yield variability in water-limited agricultural regions. However, its performance in some regions where the vegetation cycle is intensively managed appears to be degraded due to spatial and temporal limitations in the standard ESI products. In this study, we investigated potential improvements to ESI by generating maps of ET, …

Assessing Responses Of Betula Papyrifera To Climate Variability In A Remnant Population Along The Niobrara River Valley In Nebraska, U.S.A., Through Dendroecological And Remote-Sensing Techniques, E. Bumann, T. Awada, B. Wardlow, M. Hayes, J. Okalebo, C. Helzer, A. Mazis, J. Hiller, P. Cherubini

School of Natural Resources: Faculty Publications

No abstract provided.

Predicting Northern Bobwhite Habitat In Semiarid Rangeland Using Landsat Imagery, Jeffrey G. Whitt, Kelly S. Reyna

National Quail Symposium Proceedings

Multiple studies have attempted to model northern bobwhite (Colinus virginianus) distribution using classified remotely sensed imagery in combination with pattern recognition software. These models tend to be more accurate in humid subtropical regions. To identify bobwhite habitat in subhumid and semiarid rangeland, we performed our own classification on 4 LANDSAT scenes of Clay County, Texas, from July and December 2015. Stands of mature little bluestem (Schizachyrium scoparium) provide excellent bobwhite nesting cover and could be identified using LANDSAT imagery. Habitat was scored from 0 to 1.0 based on estimated range health, presence of little bluestem, and …

Aeromagnetic And Spectral Expressions Of Rare Earth Element Deposits In Gallinas Mountains Area, Central New Mexico, Usa, Mo Li

Graduate Theses & Non-Theses

The Gallinas Mountains located in the conjunction of Lincoln County and Torrance County, New Mexico, USA are a series of alkaline volcanic rocks intruded into Permian sedimentary rocks. The Gallinas Mountains area is known to host fluorite and copper as veins containing bastnasite while hydrothermally altered rocks associated with iron oxides have been found in the area as well. In this study, multispectral band ratio method was used for surface mineral interpretation by processing satellite image, while aeromagnetic inversion method was applied using aeromagnetic data, digital elevation model and physical properties for 2-D subsurface structure modeling. Bastnasite has higher magnetic …