Other Earth Sciences Commons^™

Integrating Multi-Source Data With Machine Learning Techniques To Upscale Wetland Carbon Dioxide Fluxes, Abdullah Sulaiman Abdullah Al Fazari

Electronic Theses and Dissertations

Accurate quantification of atmospheric carbon dioxide (CO₂) fluxes in wetland ecosystems is essential for understanding their role in both regional and global carbon dynamics, particularly in the context of climate change. However, the spatial and temporal heterogeneity of wetlands presents major challenges for developing reliable upscaling models. This research developed and validated a comprehensive framework to upscale CO₂ fluxes across the Everglades National Park (ENP) and Big Cypress National Preserve (BCNP) in South Florida through the integration of multi-source datasets, including AmeriFlux eddy covariance (EC) tower measurements, NASA’s BlueFlux airborne CO₂ data, and multispectral satellite imagery from Landsat 8 OLI …

Revealing Hidden Histories: A Multi-Sensor Aerial Survey For Detecting Unmarked Burials At Sinking Spring Cemetery, Abingdon, Va, Noah Hall

Electronic Theses and Dissertations

The Sinking Spring Cemetery, established in 1773 in Abingdon, Virginia, spans 11 acres and is divided by a road. The 9-acre southern section was reserved for white church members. Enslaved individuals and free people of color were buried in the smaller northern section, where few headstones remain today. This study aimed to map the unmarked graves using thermal, multispectral, and Light Detection and Ranging (LiDAR) sensors deployed on unmanned aerial systems. Graves were characterized by subtle topographic depressions mapped by LiDAR and cooler radiant temperature anomalies in thermal imagery. Thermal data collected at different times of the day and year …

Spatiotemporal Economic Impact Analysis Of The Taal Volcano Eruption Using Electricity Consumption And Nighttime Light Data, Ma Flordeliza P. Del Castillo, Toshio Fujimi, Hirokazu Tatano

SOSE Affiliate: Manila Observatory

Analyzing the spatiotemporal dimension of the economic impacts of disasters is critical for providing timely and proportionate support. However, traditional economic impact measures often lack spatiotemporal details. Hence, we estimated the daily electricity consumption (EC) loss using high-frequency EC data and analyzed temporal dimensions of the immediate impacts of Taal Volcano’s eruption on January 12, 2020. Subsequently, we computed the nighttime light (NTL) change using high-resolution NTL data to analyze the spatial distribution of these impacts. The temporal analysis revealed two EC loss peaks. The first peak coincided with the power outage and decreased energy demand, followed by a brief …

Applications Of Remote Sensing Data To Understanding Geohazards In Wyoming And Kentucky, Meredith Swallom

Theses and Dissertations--Earth and Environmental Sciences

Shallow geohazards such as earthquakes, landslides, and floods profoundly impact communities globally. Constraining susceptibility to these hazards is critical for effective hazard mitigation and building more resilient communities. This dissertation includes multiple studies that leverage remotely sensed datasets to address hazard susceptibility, including: (1) characterizing a potential northern extension of the Teton fault system, (2) deriving a vegetation-based metric to improve landslide susceptibility maps in eastern Kentucky, with potential global implications, and (3) combining numerical modeling, landscape models, and field constraints to understand how anthropogenic factors affect flood severity in southern Appalachian catchments.

In the first study, analysis of new …

Estimating Medium-Term Regional Monthly Economic Activity Reductions During The Covid-19 Pandemic Using Nighttime Light Data, Ma Flordeliza P. Del Castillo, Toshio Fujimi, Hirokazu Tatano

SOSE Affiliate: Manila Observatory

Economic impact estimates of the initial lockdowns due to the COVID-19 pandemic showed a significant reduction in economic activities globally. However, the succeeding impacts and their spatiotemporal distribution within countries remain unknown. Studies showed that nighttime light data (NTL) has effectively revealed the spatiotemporal dimensions of the economic effects of COVID-19. Thus, this study used NTL data to determine the medium-term regional monthly economic impacts of the pandemic in the Philippines in terms of the Economic Activity Reduction (EAR) index. We generated a spatial error model, regressing pre-pandemic NTL on mean temperature, maximum rainfall, and built-up area. This model explained …

Characterizing The Vegetation And Effects Of Climate Change On Parris Island, A Sea Island Ecosystem, Cody Hart Goodson

Theses, Dissertations and Capstones

Coastal habitats provide many ecosystem services, protecting coastlines from storm surges and erosion, diminishing the effects of eutrophication, sequestering large amounts of carbon, and acting as vital wildlife habitat. Sea-level rise and increased storm surge intensity associated with climate change are increasingly disrupting coastal habitats. These disturbances can shift environmental gradients that drive the zonation of coastal vegetation types, driving habitat conversion. Monitoring coastal habitat conversion can improve our understanding of the dynamic effects of climate change on these landscapes. Therefore, our objectives for chapter 1 were to identify and describe the distributions of vegetation types present on Marine Corps …

A Workshop On Using Nasa Airs Data To Monitor Drought For The U.S. Drought Monitor, Alireza Farahmand,, Sharon Ray, Heidar Thrastarson, Stephen Licata, Stephanie Granger, Brian Fuchs

National Drought Mitigation Center: Faculty Publications

Recent studies indicate that drought indicators based on near-surface air relative humidity (RH), air temperature (T), and air vapor pressure deficit (VPD), derived from the Atmospheric Infrared Sounder (AIRS) instrument aboard NASA’s Aqua satellite can detect the onset of drought earlier than other drought indicators, specifically standardized precipitation index (SPI), which is widely used for drought onset detection. A recent study showed that standardized relative humidity index (SRHI) can detect drought signals earlier than SPI (Farahmand et al. 2015). Relative humidity is a climate variable defined as the ratio of air vapor pressure to saturated vapor pressure. Precipitation and relative …

Fine Scale Mapping Of Laurentian Mixed Forest Natural Habitat Communities Using Multispectral Naip And Uav Datasets Combined With Machine Learning Methods, Parth P. Bhatt

Dissertations, Master's Theses and Master's Reports

Natural habitat communities are an important element of any forest ecosystem. Mapping and monitoring Laurentian Mixed Forest natural communities using high spatial resolution imagery is vital for management and conservation purposes. This study developed integrated spatial, spectral and Machine Learning (ML) approaches for mapping complex vegetation communities. The study utilized ultra-high and high spatial resolution National Agriculture Imagery Program (NAIP) and Unmanned Aerial Vehicle (UAV) datasets, and Digital Elevation Model (DEM). Complex natural vegetation community habitats in the Laurentian Mixed Forest of the Upper Midwest. A detailed workflow is presented to effectively process UAV imageries in a dense forest environment …

Evaluation Of Remotely Sensed Precipitation Estimates From The Nasa Power Project For Drought Detection Over Jordan, Muhammad Rasool Al‑Kilani, Michel Rahbeh, Jawad Al‑Bakri, Tsegaye Tadesse, Cody Knutson

National Drought Mitigation Center: Faculty Publications

Droughts can cause devastating impacts on water and land resources and therefore monitoring these events forms an integral part of planning. The most common approach for detecting drought events and assessing their intensity is use of the Standardized Precipitation Index (SPI), which requires abundant precipitation records at good spatial distribution. This may restrict SPI usage in many regions around the world, particularly in areas with limited numbers of ground meteorological stations. Therefore, the use of remotely sensed derived data of precipitation can contribute to drought monitoring. In this study, remotely sensed precipitation estimates from the POWER/Agroclimatology archive of NASA and …

A Sense Of Scale: Mapping Exotic Annual Grasses With Satellite Imagery Across A Landscape And Quantifying Their Biomass At A Plot Level With Structure-From-Motion In A Semi-Arid Ecosystem, Monica Vermillion

Boise State University Theses and Dissertations

The native vegetation communities in the sagebrush steppe, a semi-arid ecosystem type, are under threat from exotic annual grasses. Exotic annual grasses increase fire severity and frequency, decrease biodiversity, and reduce soil carbon storage amongst other ecosystem services. The invasion of exotic annual grasses is causing detrimental impacts to land use by eliminating forage for livestock and creating a huge economic cost from fire control and post-fire restoration. To combat invasion, land managers need to know what exotic annual grasses are present, where they are invading, and estimates of their biomass. Mapping exotic annual grasses is challenging because many areas …

Characterizing Dryland Ecosystems Using Remote Sensing And Dynamic Global Vegetation Modeling, Abdolhamid Dashtiahangar

Boise State University Theses and Dissertations

Drylands include all terrestrial regions where the production of crops, forage, wood and other ecosystem services are limited by water. These ecosystems cover approximately 40% of the earth terrestrial surface and accommodate more than 2 billion people (Millennium Ecosystem Assessment, 2005). Moreover, the interannual variability of the global carbon budget is strongly regulated by vegetation dynamics in drylands. Understanding the dynamics of such ecosystems is significant for assessing the potential for and impacts of natural or anthropogenic disturbances and mitigation planning, and a necessary step toward enhancing the economic and social well-being of dryland communities in a sustainable manner (Global …

Informing Field Management Decisions To Enhance Alfalfa Seed Production Using Remote Sensing, Thomas V. Van Der Weide

Boise State University Theses and Dissertations

The development rate of alfalfa seed crop depends on both environmental conditions and management decisions. Crop management decisions, such as determining when to release pollinators to optimize pollination, can be informed by the identification of plant development stages from remote sensing data. I first identify what electromagnetic wavelengths are sensitive to alfalfa plant development stages using hyperspectral data. A Random Forest regression is used to determine the best Vegetation Index (VI) to monitor how much of the plant is covered in flower. The results indicate that Blue, Green, and Near-Infrared are the important electromagnetic wavelengths for the VI. Imagery collected …

Remote Sensing Time-Series Analysis, Machine Learning, And K-Means Clustering Improves Dryland Vegetation And Biological Soil Crust Classification, Joshua Enterkine

Boise State University Theses and Dissertations

Dryland and semi-arid vegetation communities, although appearing to the casual observer as relatively simplistic and homogeneous, are in fact the opposite. Upon further inspection, semi-arid vegetation is highly complex and heterogeneous at almost any scale. The same holds true for biological soil crust. Growing concern about global changes in climate, nutrient cycles, and land use have required increasing scrutiny of our understanding of these communities and all of their constituents, as we seek to improve forecasting models and inform land management decisions. This thesis aims to provide insight to the paradigm of how we create and interpret vegetation classifications in …

Estimating Coastal Water Turbidity Using Viirs Nighttime Measurement, Chih-Wei Huang

USF Tampa Graduate Theses and Dissertations

Coastal water turbidity is a key environmental factor that influences the relative clarity of the water, which therefore reduces sunlight penetration. The comprehensive spatial and temporal coverage of remote sensing allows mapping of water turbidity near the coast. Even in locations where time-consuming and expensive conventional turbidity monitoring programs exist, local technological limitations prevent complete coverage. Traditional optical satellite techniques using the visible band also have limitations in monitoring turbidity due to non-optimal observing conditions such as clouds, sun-glint, and thick aerosols. In this study, in order to complement the daytime satellite measurements, I used the data from Visible Infrared …

Assessing The Cooling Effects Of Urban Vegetation On Urban Heat Mitigation In Selected U.S. Cities, Qiuyan Yu

USF Tampa Graduate Theses and Dissertations

Urban Heat Island (UHI) is a growing problem worldwide. Mitigation of UHI is necessary for cities to adapt to climate change and enhance sustainable development at a city scale. Cooling cities with urban vegetation management is a sustainable solution for urban heat mitigation. Urban vegetation influences urban microclimate through the shading effect, surface roughness, and evapotranspiration. The differences in horizontal and vertical structures of urban vegetation determine the shading effect, surface roughness, and evapotranspiration. Enhancing the cooling effect of urban vegetation requires a comprehensive understanding of how vegetation structure affects UHI. The effects of horizontal structure on land surface temperature …

Remote Estimation Of Surface Water PCo2 In The Gulf Of Mexico, Shuangling Chen

USF Tampa Graduate Theses and Dissertations

Surface ocean partial pressure of CO₂ (pCO₂) is a critical parameter in the quantification of air-sea CO₂ flux, which further plays an important role in quantifying the global carbon budget and understanding ocean acidification. The demand for a clearer understanding of how, and how fast, the ocean is changing due to atmospheric CO₂ absorption, requires accurate and synoptic estimation of surface pCO₂.

Surface ocean pCO₂ is mainly controlled by four oceanic processes – thermodynamics, ocean mixing, biological activities, and air-sea CO₂ exchange. Surface ocean pCO_{2 …}

Spatial And Temporal Distributions Of Pelagic Sargassum In The Intra-Americas Sea And Atlantic Ocean, Mengqiu Wang

USF Tampa Graduate Theses and Dissertations

Pelagic Sargassum is one type of marine macroalgae that is known to be abundant in the Gulf of Mexico and Sargasso Sea. It is also known to serve as a critical habitat for many marine animals. In the past few years, large amounts of Sargassum have been reported in the Tropical Atlantic and Caribbean Sea (CS), causing significant environmental and economic problems. The goal of this study is to improve the understanding of Sargassum distributions, quantity, transport pathways, and bloom mechanisms in the CS and Tropic Atlantic through combining a variety of techniques including satellite remote sensing, field and laboratory …

A Comparative Study On Coastal Zone Changes And Anthropogenic Impacts Between Tampa Bay, Usa, And Xiangshan Harbor, China, During The Last 30 Years, Qiandong Guo

USF Tampa Graduate Theses and Dissertations

Currently, the U.S. and China are the two largest national economic entities in the world. However, it is noticeable that the two countries have considerably different strategies for economic development, environmental protection and land supply in coastal zones. In order to understand the coastline dynamics, land use land cover (LULC) changes and land management policies in the U.S. and China, a case study of the Tampa Bay (TB) watershed, Florida, U.S., and Xiangshan Harbor (XH), Zhejiang Province, China was conducted. The two areas possess similar humid subtropical climate and dense population, but experienced different anthropogenic impacts. TB sat at a …

Spectrally Based Bathymetric Mapping Of A Dynamic, Sandbedded Channel: Niobrara River, Nebraska, Usa, E. Dilbone, C.J. Legleiter, J.S. Alexander, B. Mcelroy

United States Geological Survey: Staff Publications

Methods for spectrally based mapping of river bathymetry have been developed and tested in clear‐flowing, gravel‐bed channels, with limited application to turbid, sandbed rivers. This study used hyperspectral images and field surveys from the dynamic, sandy Niobrara River to evaluate three depth retrieval methods. The first regressionbased approach, optimal band ratio analysis (OBRA), paired in situ depth measurements with image pixel values to estimate depth. The second approach used ground‐based field spectra to calibrate an OBRA relationship. The third technique, image‐to‐depth quantile transformation (IDQT), estimated depth by linking the cumulative distribution function (CDF) of depth to the CDF of an …

Application Of Remote Sensing And Machine Learning Modeling To Post-Wildfire Debris Flow Risks, Priscilla Addison

Dissertations, Master's Theses and Master's Reports

Historically, post-fire debris flows (DFs) have been mostly more deadly than the fires that preceded them. Fires can transform a location that had no history of DFs to one that is primed for it. Studies have found that the higher the severity of the fire, the higher the probability of DF occurrence. Due to high fatalities associated with these events, several statistical models have been developed for use as emergency decision support tools. These previous models used linear modeling approaches that produced subpar results. Our study therefore investigated the application of nonlinear machine learning modeling as an alternative. Existing models …

Deriving Landscape-Scale Vegetation Cover And Aboveground Biomass In A Semi-Arid Ecosystem Using Imaging Spectroscopy, Andrew Poley

Boise State University Theses and Dissertations

Environmental disturbances in semi-arid ecosystems have highlighted the need to monitor current and future vegetation conditions across the landscape. Imaging spectroscopy provide the necessary information to derive vegetation characteristics at high-spatial resolutions across large geographic areas. The work of this thesis is divided into two sections focused on using imaging spectroscopy to estimate and classify vegetation cover, and approximate aboveground biomass in a semi-arid ecosystem.

The first half of this thesis assesses the ability of imaging spectroscopy to derive vegetation classes and their respective cover across large environmental gradients and ecotones often associated with semi-arid ecosystems. Optimal endmember selection and …

Estimation Of The Instantaneous Downward Surface Shortwave Radiation Using Modis Data In Lhasa For All-Sky Conditions, Xu Lu

Sustainability and Social Justice

Measuring the solar irradiance with high accuracy is the basis of PV power forecasting. Although the downward surface shortwave radiation (DSSR) data derived from satellite images are widely used in the PV industry, the instantaneity and accuracy of these data are not suitable for PV power forecasting in a short-time period. In this study, an algorithm to calculate instantaneous DSSR for all-sky conditions was developed by combining clear-sky radiative transfer model and 3D radiative transfer model using MODIS products (MOD03-07, 09). The algorithm was evaluated by ground measurements from a station in Lhasa and a reference dataset from FLASHFlux. The …

Developing The Framework For A Risk Map For Mite Vectored Viruses In Wheat Resulting From Pre-Harvest Hail Damage, Anthony L. Nguy-Robertson, Arthur Zygielbaum, Anthony J. Mcmechan, Gary L. Hein, Stephen N. Wegulo, Abby R. Stilwell, Travis M. Smith

Department of Plant Pathology: Faculty Publications

There is a strong economic incentive to reduce mite-vectored virus outbreaks. Most outbreaks in the central High Plains of the United States occur in the presence of volunteer wheat that emerges before harvest as a result of hail storms. This study provides a conceptual framework for developing a risk map for wheat diseases caused by mite-vectored viruses based on pre-harvest hail events. Traditional methods that use NDVI were found to be unsuitable due to low chlorophyll content in wheat at harvest. Site-level hyperspectral reflectance from mechanically hailed wheat showed increased canopy albedo. Therefore, any increase in NIR combined with large …

A Comparison Of Habitat And Geomorphic Changes On East Ship Versus Sand Islands Mississippi, 2007-2014, Carlton Peter Anderson

Master's Theses

ABSTRACT

A COMPARISON OF HABITAT AND GEOMORPHIC CHANGES ON EAST SHIP VERSUS SAND ISLANDS MISSISSIPPI, 2007-2014

by Carlton Peter Anderson

May 2015

The islands of the Mississippi-Alabama (MS-AL) barrier island chain along the micro-tidal northern Gulf of Mexico are highly dynamic coastal features subject to rapid changes in habitat, geomorphology, and elevation by natural and anthropogenic disturbances, such as hurricanes, subsidence, sea-level rise, and dredging activities. The purpose of this study was to compare elevation, total volume, habitat-type coverage, and short-term change between “naturally” formed East Ship Island and “man-made” Sand Island (Disposal-Area 10). This study used a combination of …

Estimation Of Daily Air Temperature Based On Modis Land Surface Temperature Products Over The Corn Belt In The Us, Linglin Zeng, Brian D. Wardlow, Tsegaye Tadesse, Jie Shan, Michael Hayes, Deren Li, Daxiang Xiang

Center for Advanced Land Management Information Technologies: Publications

Air temperature (Ta) is a key input in a wide range of agroclimatic applications. Moderate Resolution Imaging Spectroradiometer (MODIS) Ts (Land Surface Temperature (LST)) products are widely used to estimate daily Ta. However, only daytime LST (Ts-day) or nighttime LST (Ts-night) data have been used to estimate Tmax/Tmin (daily maximum or minimum air temperature), respectively. The relationship between Tmax and Ts-night, and the one between Tmin and Ts-day has not been studied. In this study, both the ability of Ts-night data to estimate Tmax and the ability of Ts-day data to estimate Tmin were tested and studied in the Corn …

Merging Remote Sensing Data And National Agricultural Statistics To Model Change In Irrigated Agriculture, Jesslyn F. Brown, Md Shahriar Pervez

United States Geological Survey: Staff Publications

Over 22 million hectares (ha) of U.S. croplands are irrigated. Irrigation is an intensified agricultural land use that increases crop yields and the practice affects water and energy cycles at, above, and below the land surface. Until recently, there has been a scarcity of geospatially detailed information about irrigation that is comprehensive, consistent, and timely to support studies tying agricultural land use change to aquifer water use and other factors. This study shows evidence for a recent overall net expansion of 522 thousand ha across the U.S. (2.33%) and 519 thousand ha (8.7%) in irrigated cropped area across the High …

Extending Airborne Electromagnetic Surveys For Regional Active Layer And Permafrost Mapping With Remote Sensing And Ancillary Data, Yukon Flats Ecoregion, Central Alaska, Neal J. Pastick, M. Torre Jorgenson, Bruce K. Wylie, Burke J. Minsley, Lei Ji, Michelle A. Walvoord, Bruce D. Smith, Jared D. Abraham, Joshua R. Rose

United States Geological Survey: Staff Publications

Machine-learning regression tree models were used to extrapolate airborne electromagnetic resistivity data collected along flight lines in the Yukon Flats Ecoregion, central Alaska, for regional mapping of permafrost. This method of extrapolation (r = 0.86) used subsurface resistivity, Landsat Thematic Mapper (TM) at-sensor reflectance, thermal, TM-derived spectral indices, digital elevation models and other relevant spatial data to estimate near-surface (0–2.6-m depth) resistivity at 30-m resolution. A piecewise regression model (r = 0.82) and a presence/absence decision tree classification (accuracy of 87%) were used to estimate active-layer thickness (ALT) (< 101 cm) and the probability of near-surface (up to 123-cm depth) permafrost occurrence from field data, modelled near-surface (0–2.6m) resistivity, and other relevant remote sensing and map data. At site scale, the predicted ALTs were similar to those previously observed for different vegetation types. At the landscape scale, the predicted ALTs tended to be thinner on higher-elevation loess deposits than on low-lying alluvial and sand sheet deposits of the Yukon Flats. The ALT and permafrost maps provide a baseline for future permafrost monitoring, serve as inputs for modelling hydrological and carbon cycles at local to regional scales, and offer insight into the ALT response to fire and thaw processes. Published 2013. This article is a U.S. Government work and is in the public domain in the USA.

Chlorophyll-Based Approach For Remote Estimation Of Crop Gross Primary Production: From In Situ Measurements To Satellite Imagery, Yi Peng

School of Natural Resources: Dissertations, Theses, and Student Research

The synoptic and accurate quantification of crop gross primary production (GPP) is essential for studying carbon budgets in croplands and monitoring crop status. The objective of this dissertation is to develop a quantitative technique to estimate crop GPP using remotely sensed data collected from close range to satellite altitudes. In this study, a model based on a recently developed paradigm, which relates crop GPP to a product of total crop chlorophyll content and incident radiation affecting vegetation photosynthesis, was justified for the remote estimation of GPP in crops. The model was tested with ground-observed incoming photosynthetically active radiation (PAR_{in …}

Assessing Seasonal Features Of Tropical Forests Using Remote Sensing, Roberto Bonifaz-Alfonzo

Department of Geography: Dissertations, Theses, and Student Research

Tropical forests are key components of the biogeochemical cycles, complex in structure, diversity and dynamics, also, tropical regions have been deforested and modified by human activities particularly for agriculture. Understanding the inter-annual and intra-annual variation dynamics of tropical regions could give valuable information on temporal characteristics of ecosystems behavior which is important for mapping and monitoring. This dissertation assesses seasonal and inter-annual changes in the tropical land cover that may be related to changes in the natural environment and/or human activities. Research was focused on the Mayan forest located in southern Mexico and Northwest Guatemala, one of the northern-most important …

Nir-Red Reflectance-Based Algorithms For Chlorophyll-A Estimation In Mesotrophic Inland And Coastal Waters: Lake Kinneret Case Study, Yosef Z. Yacobi, Wesley Moses, Semion Kaganovsky, Benayahu Sulimani, Bryan Leavitt, Anatoly A. Gitelson

School of Natural Resources: Faculty Publications

A variety of models have been developed for estimating chlorophyll-a (Chl-a) concentration in turbid and productive waters. All are based on optical information in a few spectral bands in the red and near-infra-red regions of the electromagnetic spectrum. The wavelength locations in the models used were meticulously tuned to provide the highest sensitivity to the presence of Chl-a and minimal sensitivity to other constituents in water. But the caveat in these models is the need for recurrent parameterization and calibration due to changes in the biophysical characteristics of water based on the location and/or time of the year. In this …