Remote Sensing Commons^™

Forest Above-Ground Biomass Estimation Using Nasa Gedi Lidar Waveforms And Global Tree Allometry, Ian Grant

Theses and Dissertations

Above-ground forest biomass plays a crucial role in global carbon cycles, yet accurately estimating biomass at global scales remains challenging. This thesis addresses two key challenges in processing NASA’s Global Ecosystem Dynamics Investigation (GEDI) space-borne lidar data to estimate above-ground biomass density (AGBD): accounting for global variation in forest structure and developing robust physical interpretations of lidar returns. The first component of the thesis analyzes global patterns of tree allometry using the Tallo tree allometry dataset, examining relationships between tree dimensions across biomes, continents, and plant functional types. This analysis reveals consistent allometry across continents for some biomes (e.g., tropical …

Devising Optimized Maize Nitrogen Stress Indices In Complex Field Conditions From Uav Hyperspectral Imagery, Jiating Li, Yufeng Ge, Laila A. Puntel, Derek M. Heeren, Geng Bai, Guillermo R. Balboa, John A. Gamon, Timothy J. Arkebauer, Yeyin Shi

School of Natural Resources: Faculty Publications

Nitrogen Sufficiency Index (NSI) is an important nitrogen (N) stress indicator for precision N management. It is usually calculated using variables such as leaf chlorophyll meter readings (SPAD) and vegetation indices (VIs). However, no consensus has been reached on the most preferred variable. Additionally, conventional NSI (NSI_uni) calculation assumes N being the sole yield-limiting factor, neglecting other factors such as soil water variability. To tackle these issues, this study compared various variables for NSI calculation and evaluated two new N stress indicators in minimizing the impact of confounding water treatment. The following ground- and aerial-derived variables were compared …

Dataset Supporting The Manuscript Fire Spread, Intensity, And Emissions Observations By Multiple Satellites: The Southern California Wildfires Of January 2025, Fangjun Li, Xiaoyang Zhang, Mark Cochrane, Shobha Kondragunta, Shuai An

Global Land Surface Season Data Sets

The data is for the paper "Fire Spread, Intensity, and Emissions Observations by Multiple Satellites: the Southern California Wildfires of January 2025" which has been submitted to the journal AGU Advances.

The downloadable file contains:

• README file that provides an overview of all all supporting files and scripts.
• 12 files folders containing the data and scripts

File type : zip/application
File size :  1.2GB

Satellite And Uas Synergy For Large-Scale Crop Canopy Cover Mapping With Deep Learning, Muhammad Ali Irshad

Electronic Theses and Dissertations

No abstract provided.

Ensemble Machine Learning Approaches For Bathymetry Estimation In Multi-Spectral Images, Kazi A. Islam, Omar Abdul-Hassan, Hongfang Zhang, Victoria Hill, Blake Schaeffer, Richard Zimmerman, Jiang Li

OES Faculty Publications

Traditional bathymetry measures require a large number of human hours, and many bathymetry records are obsolete or missing. Automated measures of bathymetry would reduce costs and increase accessibility for research and applications. In this paper, we optimized a recent machine learning model, named CatBoostOpt, to estimate bathymetry based on high-resolution WorldView-2 (WV-2) multi-spectral optical satellite images. CatBoostOpt was demonstrated across the Florida Big Bend coastline, where the model learned correlations between in situ sound Navigation and Ranging (Sonar) bathymetry measurements and the corresponding multi-spectral reflectance values in WV-2 images to map bathymetry. We evaluated three different feature transformations as inputs …

High Antarctic Coastal Productivity In Polynyas Revealed By Considering Remote Sensing Ice-Adjacency Effects, Hilde Oliver, Jessica S. Turner, Alexandre Castagna, Henry Houskeeper, Heidi Dierssen

OES Faculty Publications

Ocean color-based estimates of Antarctic net primary productivity (NPP) have indicated low nearshore productivity in ice-adjacent waters, contrasting with coupled physical–biogeochemical models. To understand this discrepancy, we assessed satellite records of polynya NPP by comparing field data with two satellite imagery datasets derived using different processing schemes. Our results indicate historical underestimation of chlorophyll a for imagery obtained using default atmospheric correction processing within approximately 100 km of ice-covered coastlines due to adjacency effects. Using radiative transfer modeling, we find that biases in ocean color polynya observations due to adjacency effects correspond to the high albedo of ice and snow. …

Coupling Remote Sensing And Modelling To Monitor The Spatial Distribution And Trends Of Surface Temperature And Ice Thickness On Sub-Arctic Lakes, Gifty Attiah

Theses and Dissertations (Comprehensive)

Lake surface temperature (LST), lake ice thickness (LIT), and lake ice phenology (LIP) play significant roles in the diverse regional processes of freshwater in cold regions. They offer direct indications of regional weather and climate conditions, and their interactions with the atmosphere impact climate processes. Furthermore, lake ice is valuable to northern communities, such as those in the Northwest Territories (NWT). Ice roads, including the longest ice road in the NWT, spanning over 80 lakes, are constructed during winter to haul goods to and from industrial establishments (e.g., mines) and for travel within and between communities. A significant challenge to …

Atmospheric Chemistry Experiment (Ace) Winds, Matthew Wyatt, Peter F. Bernath, Chris Boone, Léo Lavy, Ryan Johnson

Chemistry & Biochemistry Faculty Publications

The Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS) uses limb geometry to measure transmittance spectra of Earth's atmosphere by solar occultation. Line-of-sight wind speeds can be derived via Doppler shifts of molecular lines in infrared spectra. The wind look direction angles relative to geodetic North are derived from geometry. We validate the new ACE version 5.3 (v.5.3) line-of-sight winds with MIGHTI and meteor radar vector wind observations and find a ±15 m/s sunrise/sunset shift above 80 km. We also compare line-of-sight winds from ACE-FTS v.5.2 and v.5.3 with vector winds from the MERRA-2, HWM14, and WACCM-X models. A ±15 m/s …

Analysis Of Aerosols In The Asian Monsoon Anticyclone As Observed By The Atmospheric Chemistry Experiment, M. Lecours, R. Dodangodage, C. D. Boone, P. F. Bernath

Chemistry & Biochemistry Faculty Publications

During the Asian summer monsoon season, pollutants from the lower troposphere are transported through deep convection to the upper troposphere and lower stratosphere. Surface pollutants such as CO are transported upward and trapped in the anticyclone during this unique atmospheric phenomenon. Associated with the anticyclone is a layer of enhanced aerosols located near the tropopause often referred to as the Asian tropopause aerosol layer (ATAL). The chemical and physical properties of aerosols in the ATAL are not yet fully understood as direct observations of the aerosols are limited. The Atmospheric Chemistry Experiment (ACE) is a satellite mission that provides high-resolution …

Making Slums Legible, Visible And Calculable: Geospatial Technologies And The Governance Of Urban Land In Mumbai, Sanjana Krishnan

Theses and Dissertations--Geography

This dissertation examines how geospatial technologies are used to make slums in Mumbai legible, calculable, and hypervisible, and how these practices reshape urban land governance. It situates mapping, remote sensing, and algorithmic systems within their political-economic contexts, showing how technologies intending to see the city often function as instruments of dispossession. The research has three interconnected empirical chapters. The first empirical chapter traces the history of slum mapping in Mumbai, from their absences in early development plans to their selective hypervisibility under the contemporary governance regimes. Using critical cartographic methods, it highlights how novel technologies such as remote sensing, biometric …

Impacts Of Southern Pine Beetle (Dendroctonus Frontalis Zimmerman) On Loblolly Pine (Pinus Taeda L.) Canopy And Water Use In The Homochitto National Forest, Mississippi, Usa, Sasha Goodnow, Yun Yang, Hui Liu, Ashley Schulz

Endeavors: Mississippi State Undergraduate Research Journal

Abiotic and biotic forest disturbances can have many impacts to forest ecosystem services, including to forest water use. Studies on impacts to forest evapotranspiration have been conducted on the mountain pine beetle (Dendroctonus ponderosae) in western North America, but not on the southern pine beetle (Dendroctonus frontalis), which is a native pest of loblolly pine (Pinus taeda) and shortleaf pine (Pinus echinata), in the southeastern United States. Stressed pine trees produce pheromones that attract southern pine beetles and, with enough stressed trees, beetle populations can quickly grow to epidemic levels and attack healthy trees, which results in widespread tree mortality. …

The Role Of Remote Sensing And Gis Techniques In Analysis Of Southern California Wildfires In January 2025, Sara Fitzgibbon

Dissertations, Master's Theses and Master's Reports

California is no stranger to wildfires, with them becoming more frequent and larger in recent years. In early January 2025, Southern California had one of the worst outbreaks of wildfires in its history, with the Pacific Palisades and Eaton Fires being considered among the most destructive in state history. To help prevent this from happening in the future, remote sensing techniques are essential in combating these issues. In this report, geographic information systems (GIS) and remote sensing data utilized to explore fire behavior by various organizations were investigated. By using this data, this study aims to predict and monitor fire …

Global Spectral Clustering Of Temporally Stable Pixels For Epics Identification, Validation, And Hyperspectral Assignment For Satellite Calibration, Juliana Maria Fajardo Rueda

Electronic Theses and Dissertations

No abstract provided.

Remote Sensing - Based Mapping And Analysis Of Winter Cover Crop Adoption For Sustainable Agriculture, Minnehaha County, Belinda Buechler

Electronic Theses and Dissertations

Winter cover crops planted by farmers such as cereal rye, crimson clover, radishes, hairy vetch, and winter wheat are used to conserve and protect the soil during winter. These crops offer numerous benefits such as improving soil health, reducing erosion, fixing nitrogen, increasing carbon sequestration, and weed suppression. Over time, winter cover cropping has been recognized as a sustainable agricultural practice and has gained attention from Federal and State conservation programs, farmers, and non-governmental organizations. Due to their vital benefits, agencies such as the United States Department of Agriculture (USDA), Natural Resources Conversation Services (NRCS) have partnered with cost-share programs …

Shifting Waters: A 41-Year Time-Series Analysis Of Surface Water Change In The Prairie Pothole Region, Madison Dejarlais

Electronic Theses and Dissertations

The Prairie Pothole Region (PRR) is a landscape defined by a dynamic surface water system, with wetlands, lakes, and rivers playing critical roles in supporting biodiversity, regulating floods, and maintaining hydrological balance. This study conducts a time-series analysis of surface water change in the PPR from 1984 to 2024, using remote sensing tools including Google Earth Engine, ArcGIS Pro, and ENVI. 41 annual surface water presence rasters were compiled into a cumulative dataset, allowing for both year-to-year comparisons and broader trend analysis. Results indicate that the presence of surface water in the PPR has not followed a simple linear trend. …

Restored Wetlands Show Rapid Vegetation Recovery And Substantial Surface-Water Expansion, Thilina D. Surasinghe, Yin-Hsuen Chen, Kunwar K. Singh

Center for Geospatial Science, Education & Analytics Faculty Publications

Ecological restoration is essential for improving the ecological integrity of degraded ecosystems to enhance ecosystem services and biodiversity. In this study, we assessed the effectiveness of wetland restoration on retired cranberry farms by analyzing vegetation recovery and surface-water dynamics using the enhanced vegetation index (EVI) and normalized difference water index (NDWI) derived from Sentinel-2 satellite imagery. To quantify temporal dynamics of both vegetation recovery and surface-water cover, we identified the spectral distinctions among restored wetland plant communities. Our results indicated the emergence of distinct plant communities upon restoration. Restored wetlands in general showed significant and progressive vegetation recovery and expanding …

Evaluating Spatiotemporal Vegetation Index Variation To Detect Salt Marsh Dieback On The Georgia Coast, Emmanuella Bosompemaa Obeng

College of Graduate Studies: Theses & Dissertations

Salt marshes, essential for coastal protection and carbon sequestration, are increasingly vulnerable to dieback events, threatening ecosystem resilience and vital services. Detecting these shifts early is essential for timely intervention. However, few studies have applied Early Warning Signals (EWS) to coastal marsh systems. Most EWS research has focused on lakes, forests, or climate tipping points, with limited application to salt marsh dieback in the southeastern U.S. Site-specific, long-term spatial analyses are also lacking, as prior work often examines short time frames or single disturbance events. This study investigates the spatiotemporal patterns of salt marsh dieback on the Georgia coast from …

Annual Diversity Of Honey Bee Pollen Sources In Two Pumpkin Growing Landscapes, Machakos County, Kenya, Marystella W. Nang’Oni, Muo Kasina, Rebecca Karanja, Mary M. Guantai, Rahab N. Kinyanjui, Evanson R. Omuse, Michael H.G. Lattorff, Elfatih M. Abdel-Rahman, Marian Adan, Samira A. Mohamed, Thomas Dubois

All Peer-Reviewed Publications

Multi-floral foraging sources for honey bee (Apis mellifera L.) have been threatened by landscape changes and unsustainable farming practices. In East Africa, the biodiversity of forage resources that could support honey bees, especially in agricultural lands, remains least explored. This study investigated pollen diversity for honey bees in Yatta and Masinga Sub-counties in Machakos County, Kenya. Honey bee hives were installed on eight pumpkin (Cucurbita maxima Duchesne ex Lam) farms (one hive per farm) in two varying landscape vegetation classes (low and medium) based on normalized difference vegetation index (NDVI). Pollen traps were installed at the hive entrance and pollen …

Earth Observations Reveal Impacts Of Climate Variability On Maize Cropping Systems In Sub-Saharan Africa, Adomas Liepa, Michael Thiel, Hannes Taubenböck, Doris Klein, Ingolf Steffan-Dewenter, Marcell K. Peters, Sarah Schönbrodt-Stitt, Insa Otte, Tobias Landmann, Zeyaur R. Khan, Michael Ochieng Obondo, Frank Chidawanyika, Emily A. Martin, Tobias Ullmann

All Peer-Reviewed Publications

In Kenya, climate variability and change threaten smallholder, rainfed farms, with crop failures, yield reductions, and pest infestations. Efficient agroecological strategies, such as Push-Pull intercropping, offer documented benefits including pest control, improved soil fertility, and water conservation compared to traditional maize monocropping. To date, no studies exist comparing traditional maize monocropping and Push-Pull intercropping using earth observation tools over several growing seasons in East Africa. Our research addresses this by harmonizing Landsat 7, 8, 9 with Sentinel-2 remote sensing time series from 2016 to 2023. Phenological metrics of 15 growing seasons are extracted based on a threshold method using the …

Wildlife Distribution Mapping And Analysis In Gorongosa National Park, Mozambique, Using Site And Satellite Imagery Data, Pinho Joaquim Munhequeira Mr

Murray State Theses and Dissertations

One of Mozambique's most important conservation sites, Gorongosa National Park has seen critical ecological changes over the past several decades resulting from climate variability, habitat loss, and political instability. This research integrates Geographic Information Systems (GIS) and remote sensing to examine the relationship between vegetation dynamics and wildlife population, and distribution. The main goals of this study are to evaluate the spatial distribution of particular wildlife species: buffalo (Syncerus caffer), elephant (Loxodonta africana), hippopotamus (Hippopotamus amphibius), and zebra (Equus quagga), and determine the impact of vegetation density and land cover on their …

Multi-Source Remote Sensing–Based Soil Moisture Prediction Using Machine Learning, Niraj Neupane

Electronic Theses and Dissertations

Soil moisture (SM) plays a central role in climatic and environmental processes, influencing shear strength of soil, agricultural productivity, land–atmosphere interactions, and hydrologic functioning. However, accurately estimating SM across diverse climatic regions remains challenging due to spatial heterogeneity, limited in situ measurements, and inconsistencies in sensor resolution. Machine learning (ML) and remote sensing offer promising avenues for improving SM prediction, yet many existing approaches struggle with generalization across climatic gradients and often fail to capture temporal variability. This study integrates multi-source satellite and climate datasets, including SMAP L4_SM, MODIS land surface temperature, Daymet meteorological variables, and in situ observations from …

Slum Area Detection In Dhaka City, Bangladesh, Using Satellite Remote Sensing And Deep Learning, Soubhoon Sadeq Shinjini

Electronic Theses and Dissertations

Dhaka City, a rapidly growing megacity and high-density developing area in Bangladesh, faces numerous urbanization challenges. Among these, informal settlements or slum areas pose serious concerns for authorities and policymakers striving to improve living conditions for slum dwellers. Dhaka City’s slums are characterized by high-density, one- or two-story structures made of low-cost materials, often located adjacent to natural water bodies and lacking basic public infrastructure (Ahmed 2014; Iqbal 2014; Jahan 2012). The need for accurate and up-to-date data on these settlements is crucial for researchers and policymakers, particularly for implementing slum upgradation and resettlement programs. However, traditional field surveys for …

Atmospheric Chemistry Experiment (Ace) V.5.3 Winds: Validation And Model Comparisons, Matthew Wyatt, Peter F. Bernath, Chris Boone, Leo Lavy, Ryan Johnson

Physics Faculty Publications

The Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS) uses limb geometry to measure transmittance spectra of Earth's atmosphere by solar occultation. Line-of-sight wind speeds can be derived via Doppler shifts of molecular lines in infrared spectra. The wind look direction angles relative to geodetic north are derived from geometry. We validate the new ACE version 5.3 (v.5.3) line-of-sight winds with MIGHTI and meteor radar vector wind observations and find a -15 m s^-¹ (+15 m s^-¹) sunrise (sunset) shift above 80 km. We also compare line-of-sight winds from ACE-FTS v.5.2 and v.5.3 with vector winds from …

Land Target Detection Algorithm In Remote Sensing Images Based On Deep Learning, Wenyi Hu, Xiaomeng Jiang, Jiawei Tian, Shitong Ye, Shan Liu

Electrical & Computer Engineering Faculty Publications

Remote sensing technology plays a crucial role across various sectors, such as meteorological monitoring, city planning, and natural resource exploration. A critical aspect of remote sensing image analysis is land target detection, which involves identifying and classifying land-based objects within satellite or aerial imagery. However, despite advancements in both traditional detection methods and deep-learning-based approaches, detecting land targets remains challenging, especially when dealing with small and rotated objects that are difficult to distinguish. To address these challenges, this study introduces an enhanced model, YOLOv5s-CACSD, which builds upon the YOLOv5s framework. Our model integrates the channel attention (CA) mechanism, CARAFE, and …

Social Susceptibility-Driven Longitudinal Tornado Reconnaissance Methodology: 2021 Midwest Quad-State Tornado Outbreak, John W. Van De Lindt, Wanting "Lisa" Wang, Blythe Johnston, P. Shane Crawford, Guirong Yan, Thang Dao, Trung Do, Katie Skakel, Mojtaba Harati, Tu Nguyen, Robinson Umeike, Silvana Croope

Civil & Environmental Engineering Faculty Publications

With the impact of climate change, the intensity and frequency of tornado events have been increasing. Enhancing tornado reconnaissance methods can comprehensively capture building damage and recovery data following tornado events and outbreaks, thereby strengthening community resilience against the threat of future tornado events. Advancements in tornado data reconnaissance research have embraced remote sensing techniques to assess building damage after tornado events, supplanting traditional reconnaissance methods relying on handheld cameras with GIS mapping. Community resilience research offers a groundbreaking perspective, stressing the importance of assessing buildings throughout their recovery cycle-from damage and functionality to recovery-and considering their socioeconomic stability in …

Performance Of Acoustic Telemetry And Space Use Of Pallid Sturgeon In The Lower Platte River, Nebraska, Christopher F. Pullano

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

Pallid Sturgeon (Scaphirhynchus albus) are centenarian, potamodromous, rheophiles that historically occupied the Missouri River and Mississippi River basins. Listed on the U.S. Endangered Species Act in 1990, population declines are attributed to habitat fragmentation and degradation, as well as overharvest, and hybridization. A knowledge gap exists regarding the extent to which tributaries facilitate key life stages for Pallid Sturgeon. This study evaluated the capacity of acoustic telemetry to monitor the movements of Pallid Sturgeon in a shallow, braided tributary to the Missouri River. The specific objectives were to (1) evaluate the environmental variables influencing the performance of acoustic …

Modeling Snow Surface Properties From Lidar And Imaging Spectroscopy, Brenton A. Wilder

Boise State University Theses and Dissertations

Seasonal snow surface plays an important role in altering terrestrial hydrology and global climate patterns. Snow reflects a majority of incoming shortwave radiation thereby reducing the net shortwave radiation received into snowpack throughout the season. This property is commonly referred to as snow albedo and impacts water cycles and air temperatures by modulating the timing and magnitude of melt. This reflectivity of snow is difficult to measure accurately in mountain environments and at a large enough scale to be meaningful for water resource managers and climate scientists. The work presented herein aims to improve methodologies to measure snow reflectivity from …

Redefining Approaches For Measuring Landscape Subsidence And Permafrost Degradation In Arctic Tundra Environments, Tabatha Lynn Fuson

Open Access Theses & Dissertations

As climate change accelerates in the Arctic, the degradation of permafrost is leading to significant landscape transformation in tundra landscapes. This dissertation investigates the multifaceted responses of permafrost systems to warming, focusing on the dynamics of surface elevation changes and active layer thickness (ALT) across the North Slope of Alaska. In this study, I explore the capacity of repeat Terrestrial Laser Scanning (TLS) technology for modeling tundra features and detecting surface subsidence, specifically how different climate and landscape conditions during scanning impact TLS model precision. We also compare TLS model precision estimates to TLS model accuracy by comparing elevation values …

Time Series Decomposition Of Land Surface Temperature For Long-Term Trend Forecasting And Impact On Nesting Sea Turtle Habitats In The Arabian Gulf, Sachi Perera, Rommel H. Maneja, Mohamed Allali, Cyril Rakovski, Erik Linstead, Daniele Struppa, Ali Qasem, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Improving land surface temperature (LST) modeling is vital for mitigating climate change effects on various ecosystems and marine habitats such as important sea turtle habitats. Over the past decade, extreme temperatures have likely significantly affected nesting sea turtle habitats in the Arabian Gulf, with predominantly female hatchlings creating an imbalance in the sex ratio. Such shifts have profound implications for these habitats’ long-term survival and conservation management. This study leverages statistical machine learning models to measure ongoing temporal variations in LST. We break down the LST time series into trend, seasonal, and noise components using classical decomposition methods like X11, …

Impact Of Weather Systems On Uav Parameters Using Computational Fluid Dynamics, Saif Aljuhaishi, Yaseen K. Al-Timimi, Basim I. Wahab

Karbala International Journal of Modern Science

Since drones cannot fly in any kind of weather, they are not safe for time-sensitive activities. The study examines how the passage of weather systems in Iraq leads to the ban on drone flights, and how these weather conditions impact the aerodynamic forces of the drone. Hourly climate data for the study area were obtained from ECMWF ERA5 and CAMS in NetCDF format for four climate stations (Erbil, Baghdad, Rutbah, and Basrah). A ScanEagle drone was chosen for this study. The Python programming language was used to perform mathematical operations to calculate the ban on drone flights. ArcGIS 10.8 was …