Geography Commons^™

A Novel Edge-Based Accuracy Assessment Framework For Target Detection From Remotely Sensed Images, Yingfan Zhang, Weiyi Hou, Lyndon Estes, Rui Lu, Shijie Zhu, Aiyin Zhang, Zhou Shi, Su Ye

Geography

Accuracy assessment is critical for evaluating map quality and improving algorithms for target detection in remotely sensed images. Traditional methods for assessing a target-detection task were often performed by estimating the relative pixels of correct and incorrect identifications (e.g., F1 score). However, this approach only considers the pixel-by-pixel agreement and ignores important aspects of positional errors and target object quality. To provide comprehensive diagnostic information, we propose a novel edge-based accuracy assessment framework. This framework firstly applied a newly proposed assessment tool, Dynamic Epsilon-band Accuracy Function (DEAF), which is a linear fitting function from a series of edge accuracies associated …

Scraping The Earth: Testing Ndvi As An Indicator Of Military Ground Maneuver Within The Israeli Invasion Of The Gaza Strip, Thomas A. Bergeron

LSU Master's Theses

The advancement of open-source (OSINT) and geospatial intelligence (GEOINT) has allowed independent researchers to study human conflict in new ways, with tools that were previously reserved only for state intelligence agencies. In order to advance methodologies, researchers must continue to evaluate new tools to study war.  Valued for its accessibility and moderate spatial resolution, the Normalized Difference Vegetation Index (NDVI) is one such tool that has not been widely systematically tested for its use in an open-source GEOINT investigation of modern conflict. This study tests NDVI as an indicator of military maneuver by leveraging a mixed-method approach against open-source kinetic …

Quantifying Terrain Controls On Satellite-Based Snow Water Equivalent Estimation: A Spatially Explicit Machine Learning Approach, Brant Giovannetti

Geography and the Environment: Graduate Student Capstones

Terrain variables are widely incorporated into machine learning Snow Water Equivalent (SWE) models but are rarely evaluated for their independent contribution relative to spectral predictors. Using a four-tier stepwise Random Forest framework with Harmonized Landsat Sentinel-2 imagery and Airborne Snow Observatory LiDAR ground truth, this study isolates the contribution of elevation, slope, northness, and eastness across Peak and Ablation snowpack regimes in the East Taylor River Watershed, Colorado. During peak snowpack, adding terrain improved R² by 0.214, with elevation alone accounting for 42.8% of model importance. During ablation, full-dataset terrain gains were modest, increasing R² by only 0.036. However, when …

Evapotranspiration Everywhere, All The Time: Towards A Unified View From Earth Observation, Joshua B. Fisher, Martha C. Anderson, Diego G. Miralles, Kanishka Mallick, Paul C. Stoy, Youngryel Ryu, Wim G. M. Bastiaanssen

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Scientists want to know everything, everywhere, and all the time. This is particularly true in Earth science, where we seek to understand processes that span from the molecular to the planetary scale in how the world works, how it affects us, and how we impact it—especially the water cycle. Evapotranspiration (ET) was the last component to be measured in closing the water cycle: for decades, closing the water budget meant adding up all the measurable components, then inferring ET as the residual. Early measurements relied on water loss from pans and weighing lysimeters, followed by sensors inserted into plants to …

Distribution Mapping And Modeling Of The Invasive Japanese Knotweed, Jossalyn Rogalski

Masters Theses

This thesis investigates the distribution of invasive Japanese knotweed across Michigan. This plant poses significant challenges to land management due to its rapid growth, environmental impacts, and difficulty of removal once established. Using geographic information systems (GIS), remotely sensed data, and secondary environmental datasets, this research maps current infestations and analyzes key factors influencing the species’ growth and dispersal, such as soil composition, hydrology, land use, and a range of environmental variables, including climatic (annual mean temperature, temperature seasonality, annual precipitation, precipitation seasonality), elevation, vegetation and hydrological indices (NDVI, EVI, NDWI), percent tree cover, and distance to roads. Spatial analysis …

Passive Microwave Remote Sensing Of Flash Drought Impacts On Vegetation, Quinton R. Deppert

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

In 2002, Dr. Mark Svoboda characterized a new form of drought known as flash drought. Flash drought was defined as a rapid decline in vegetation health caused by severe heat and drought. In recent years, attempts to quantify the impacts of flash drought via precipitation, soil moisture, evapotranspiration, and temperature indicators have proliferated. What has rarely been quantified is what the rapid decline in vegetation health amid flash drought looks like through remote sensing. This is because vegetation health indices like the Normalized Difference Vegetation Index (NDVI) are derived from the visible and infrared regions of the electromagnetic spectrum and …

Croatian Seagrass Meadows: Time Change Detection Of Loss Due To Anchoring Damage, Eliza J. Hammari, Gabe Mills, Ruth Kerry, Steve Schill

FHSS Mentored Research Conference

Posidonia oceanica in the Croatian seascape is an important seagrass species for carbon sequestration and habitat stability. One of the largest threats to seagrass is boat anchoring. In this study we used satellite imagery to detect changes in seagrass in anchoring hotspots over a seven-year period.

Tracking The Russian Invasion Of Utah Wheat Fields, Eliza J. Hammari, Ruth Kerry

FHSS Mentored Research Conference

Russian thistle (tumbleweed) is one of the most economically damaging weeds for agricultural fields. Using remote sensing methods, thistle presence in Utah wheat fields was measured and spatial patterns were analyzed to examine how weed infestation corresponds with soil water content and wheat yield harvests.

Changes In Land, Ocean, Atmospheric Parameters Associated With The 2025 Myanmar (Mw 7.7) Earthquake, Feng Jing, Akshansa Chauhan, Ashwani Raju, Ramesh P. Singh

Mathematics, Physics, and Computer Science Faculty Articles and Research

Multiple parameters associated with the land, atmosphere, and ocean were analyzed to study short-term and immediate pre-earthquake changes associated with the 28 March 2025 Myanmar earthquake (Mw 7.7). Anomalous clear-sky outgoing longwave radiation (ClrOLR) and trace gases (CH₄, CO, and O₃) were detected within two months prior to the mainshock. Vertical changes at different pressure levels suggest a possible underground source. High-temporal-resolution observations of the infrared brightness temperature and surface air pressure revealed short-lived fluctuations shortly before the earthquake, which may reflect localized stress adjustments and surface latent heat flux release during the final stage of earthquake preparation. In the …

Using Remote Sensing Technology To Develop A Framework For Improving Hydrologic Models, Marissa Cook

Theses, Dissertations and Capstones

With increased storm intensity due to climate change and urbanization, flash flooding has become an increasingly significant issue globally and regionally. Although the factors influencing urban flash flooding are well-known, there is a growing need for technology to accurately and remotely predict the chance of a flash flood occurring from any given rain event to give people time to prepare. This study aims to use multispectral satellite imagery to provide a framework for improving near real-time flood predictions in an urban area of a high gradient, fourth order stream impacted by flooding. Specifically, we utilize satellite imagery to create the …

Climate Change In Gilgit-Baltistan: Satellite-Based Land Use/Land Cover Change Detection, Socio-Economic Dimensions, And Adaptation Strategies, Ali Muhammad

Graduate Theses/Dissertations

Climate change is increasingly transforming the cryosphere, hydrology, and human landscape of Gilgit-Baltistan, a highly climate-sensitive mountain region in northern Pakistan. This thesis investigates these transformations through satellite-based land use/land cover (LULC) change detection in four representative tehsils of Gilgit-Baltistan—Ali Abad, Gilgit, Nagar, and Sikander Abad—selected to span a gradient of human pressure and cryospheric exposure within the region. Using summer, cloud-free (< 10%) imagery from USGS Landsat 7 (2000) and Landsat 8 (2025), it conducts a multi-temporal comparison of environmental and socio-spatial change. After atmospheric correction and band compositing, the imagery is classified in ArcGIS Pro into six classes—Water, Barren land, Vegetation, Snow, Glacier, and Built-up—using a Support Vector Machine (SVM) classifier, with Maximum Likelihood Classification and Random Forest also tested but found less suitable for the final workflow. The analysis detects a pronounced reduction in mapped glacier-class area alongside a comparatively stable snow class, together with built-up expansion, while examining how temperature, precipitation, tourism, and population dynamics relate to observed LULC transitions. The results reveal a pattern of cryospheric decline and urban growth, with implications for water availability, ecological stability, hazard exposure, and settlement pressure. By integrating geospatial change detection with climatic and socio-economic interpretation, the thesis moves beyond mapping to explain interacting environmental and human drivers of landscape transformation and provides a reproducible remote-sensing baseline for monitoring land-surface change in heterogeneous mountainous terrain. It recommends integrated water-resource management, climate-resilient land-use planning, watershed and glacier monitoring, and sustainable tourism governance, supporting evidence-based decision-making by the Government of Gilgit-Baltistan and organizations working on climate adaptation, disaster risk reduction, and sustainable regional development.

Global, Continental, And Local Scale Paleoenvironmental Reconstruction Methods For Interpreting The History Of Miocene North America And The Great Plains, Willow Hue Nguy

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

The Miocene of North America is characterized by dynamic changes in herbivore communities, habitat composition, and global climate. Long-term cooling and drying trends influenced large changes in floral and faunal communities. The Great Plains, North America shifted from closed-canopy biomes to open-canopy biomes with C3-grasses to biomes with C4-grasses. This shift affected the herbivore communities as browsing-adapted ungulates were replaced by grazing-adapted ungulates. Much focus has centered on the Great Plains, so it is not well understood how the changes in biomes compare to other regions of North America. The models used for vegetation density indicate open-canopy biomes since at …

Advancing Precision Agriculture Through The Application Of Remote Sensing Technologies In Plant Health Assessment, Thomas Wilbur Davis

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Monitoring plant health, including nutritional status assessment, is an important component of crop management decisions. This doctoral document addresses the use of agricultural remote sensing through focused investigations of plant disease detection and nutrient status assessment technologies that advance precision agriculture. The first chapter provides a comprehensive overview of remote sensing technologies in agriculture and examines current capabilities, limitations, and future directions. The final two chapters address studies that evaluated the virus-nitrogen interaction in wheat and compared methods to determine the nitrogen status of midseason field corn.

The first study evaluated the wheat streak mosaic virus (WSMV) × nitrogen interaction …

Remotely-Sensed Urbanization And Local Perceptions Of Change From 1985-2024 In Southern Indiana., Marlea Ferber

Electronic Theses and Dissertations

This study is focused on the land cover change of non-built land cover being transformed into built land cover in two counties in Southern Indiana using mixed methods. Remote sensing was used to identify and quantify land cover change, and interviews were used to understand local perceptions of the physical land cover changes. The study area is situated along the rural-urban continuum with Louisville, Kentucky across the Ohio River. It is important to quantify the amount of land change conversion to built settlement as patterns and rate of urbanization help us to better manage transitions along the rural-urban continuum, but …

Tackling Data Quality Challenges In Remote Sensing: Solutions For Reliable Urban Heat Island Analysis, Wei Xia, Aqil Tariq, Hesham El-Askary, Rana Waqar Aslam, Elgar Barboza, Dmitry E. Kucher, Youssef M. Youssef, Habib Kraiem

Mathematics, Physics, and Computer Science Faculty Articles and Research

Urban heat islands (UHIs) pose critical challenges to public health, energy demand, and environmental sustainability, particularly in rapidly expanding urban regions. This study examines the complex relationship between building configurations and integrated green spaces, as well as their combined impact on thermal regulation. It focuses on addressing data quality issues commonly encountered in remote sensing applications. Using high-resolution multispectral and thermal imagery, we developed an integrated modeling approach that captures the collective influence of built form and green infrastructure on urban microclimates. A key finding is the significant linear inverse relationship between green space coverage and land surface temperature, underscoring …

High Spatial Resolution Crop Type And Land Use Land Cover Classification Without Labels: A Framework Using Multi-Temporal Planetscope Images And Variational Bayesian Gaussian Mixture Model, Minh Tri Le

Mathematics, Physics, and Computer Science Faculty Articles and Research

Previous studies often combined high spatial resolution data (e.g., PlanetScope) with wider spectral range data (e.g., Sentinel-2) and relied on supervised classification methods to produce land use and land cover (LULC) maps. This study proposed a new unsupervised framework to generate crop type and LULC maps at high spatial resolution (< 5 m) using available PlanetScope data solely without requiring ground truths. We used PlanetScope surface reflectance images and their derived spectral indices during growing seasons to create multi-temporal input features, which were fed into an unsupervised Variational Bayesian Gaussian Mixture Model (VBGMM). The VBGMM, unlike the traditional unsupervised classification methods, (1) first estimated optimal parameters that are most suitable based on the input features and then (2) assigned pixels to the cluster with maximum posteriori probability of a mixture of several Gaussian distributions. The crop type and LULC maps were then generated by labeling the derived clusters using the best possible assignment method, referring to the existing crop type or LULC products. We evaluated the produced PlanetScope-based crop type and LULC maps using true labels, corresponding reference maps, and other unsupervised classification methods. The results demonstrated the robustness and effectiveness of the proposed framework in mapping crop types and LULC at 3–5 m pixels across various ecosystems, climate zones, and human-managed landscapes. The spatial patterns of PlanetScope-based maps were (1) highly comparable with all the reference datasets at 10–30 m spatial resolution and (2) better than the traditional GMM and K-means clustering methods. The VBGMM produced classification maps with high confidence, yielding class probabilities above 0.9 for over 90 % of all study areas. The area percentage for all crop type and LULC classes agreed well with their reference maps, with R2 of 0.95 and RMSE of 1.04 %. The confusion matrices using true labels indicated that PlanetScope-based maps achieved a higher overall accuracy of 84 % than the supervised referenced maps of 81 %. Besides, the entropy comparison showed that our framework-based maps were better at capturing fine-scale features such as developed areas within cities that commonly mix with open space and vegetation, deforestation and cropland conversion in South America, smallholder croplands in Africa and Asia, and generating homogeneous crop fields in North America. This study further highlighted the potential for future research to implement our proposed framework to generate timely and extensive annotated datasets, which can be used for operationally training machine learning models to map crop types and LULC, track deforestation, detect wildfires, and delineate flooded areas at larger scales using medium/coarse Earth observations.

Remote Sensing-Based Assessment Of Evapotranspiration Patterns In A Unesco World Heritage Site Under Increasing Water Competition, Maria C. Moyano, Monica Garcia, Luis Juana, Laura Recuero, Lucia Tornos, Joshua B. Fisher, Néstor Fernández, Alicia Palacias-Orueta

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

In water-scarce regions, natural ecosystems and agriculture increasingly compete for limited water resources, intensifying stress during periods of drought. To assess these competing demands, we applied a modified PT-JPL model that incorporates the thermal inertial approach as a substitute for relative humidity (RH) in estimating soil evaporation—a method that significantly outperforms the original PT-JPL formulation in Mediterranean semi-arid irrigated areas. This remote sensing framework enabled us to quantify spatial and temporal variations in water use across both natural and agricultural systems within the UNESCO World Heritage site of Doñana. Our analysis revealed an increasing evapotranspiration (ET) trend in intensified agricultural …

A Novel Approach To Increase Accuracy In Remotely Sensed Evapotranspiration Through Basin Water Balance And Flux Tower Constraints, Kul Khand, Gabriel B. Senay, Mackenzie Friedrichs, Koong Yi, Joshua B. Fisher, Lixin Wang, Kosana Suvočarev, Arman Ahmadi, Housen Chu, Stephen Good, Kanishka Mallick, Justine Missik, Jacob A. Nelson, David E. Reed, Tianxin Wang, Xiangming Xiao

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Remote sensing-derived evapotranspiration (RSET) products capture the spatiotemporal variations of evapotranspiration (ET) from field to basin scales with unprecedented details. However, their accuracy varies across RSET estimation methods and diverse hydroclimate regions. While ET modeling efforts to account for biophysical processes and controlling parameters have made good progress in recent years, a parallel approach of integrating in-situ ET with RSET could reduce biases in RSET products. Basin water balance ET (WBET) and flux tower ET are widely applied to evaluate RSET accuracy, yet such ET measurements are rarely used for RSET bias corrections, especially for large area applications. To address …

Geospatial Intelligence And Multi-Criteria Analysis For Mapping Groundwater Potential Zones And Sustainable Resource Management In Wadi Qena Basin, Eastern Desert, Egypt, El-Taher M. M. Shams, Rashad Sawires, Sahar N. E. Tawfiq, Hanaa R. Youssef, Wenzhao Li, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Groundwater is a rare and valuable resource in arid and hyperarid areas. Over the past few decades, population growth, urbanization, and agricultural activities—particularly in developing countries like Egypt—have greatly increased the demand for water supplies. The purpose of this study is to apply a multi-criteria analytical hierarchy process (AHP) in conjunction with remote sensing and geographic information systems methodologies to identify potential zones for groundwater recharge in Wadi Qena, Eastern Desert of Egypt. This valley is considered as one of the most potential valleys for government-led land reclamation and development initiatives. Using several data sources (e.g., Landsat-8 Enhanced Thematic Mapper …

Monitoring The Qosh Tepa Canal Project: A Geospatial Timeline Of Taliban Water Diversion, Enerel L. Crosslin

Honors Thesis

The World Food Program states that “acute malnutrition in Afghanistan is above emergency thresholds in 25 out of 34 provinces and is expected to worsen”. Aiming to support agriculture, the Taliban began to build the 285 km “Qosh Tepa Canal” to divert 17% of the Amu Darya, which supports the livelihoods of millions of people in downstream Uzbekistan and Turkmenistan. The World Bank estimated that roughly 2.4 million Central Asians could become climate refugees by 2050. Our objectives are to create a timeline of satellite imagery of the canal’s construction. Our research questions are (1) Can we characterize water diversion …

Measuring Agricultural Adaptation Using Remote Sensing: A Study Of Pigeonpea In Malawi, Maria Gorret Nabuwembo

Graduate Theses and Dissertations

Drought, heatwaves, and flooding cause tremendous damage to agricultural production in Malawi, and the continuous production of maize has led to widespread soil degradation. Additionally, climate change is transforming the environment at a scale beyond historical records, posing significant challenges to social, political, and economic systems. To combat these issues, agricultural innovations have been implemented, such as the installation of irrigation systems and development of heat/drought resilient crop varieties. Pigeonpea is one of the prominent drought-tolerant and temperature resilient crops grown as a diversification strategy since it allows farmers to adapt to changes while maintaining subsistence needs. This research investigates …

Assessing Spatial And Temporal Variation In Photoprotective Responses Of Deciduous And Evergreen Tree Canopies With Leaf Spectroscopy, Alexander Piper

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

Environmental conditions frequently prevent carbon fixation by plants, leading to the absorption of excess light that can damage photosynthetic machinery if not dissipated. To do so, plants utilize several photoprotective mechanisms, some detectable remotely using Photochemical Reflectance Index (PRI). Two components of PRI correspond to the facultative engagement of the xanthophyll cycle (ΔPRI) and constitutive changes in xanthophyll pigment pool sizes (PRI0), representing distinct mechanisms regulating shorter and longer-term photoprotection, respectively. Our understanding of interspecific and intraspecific variation in these mechanisms is limited, primarily because PRI components are often not clearly distinguished. This study aimed to assess the variation in …

A Survey Of Sampling Methods For Hyperspectral Remote Sensing: Addressing Bias Induced By Random Sampling, Kevin T. Decker, Brett J. Borghetti

Faculty Publications

Identified as early as 2000, the challenges involved in developing and assessing remote sensing models with small datasets remain, with one key issue persisting: the misuse of random sampling to generate training and testing data. This practice often introduces a high degree of correlation between the sets, leading to an overestimation of model generalizability. Despite the early recognition of this problem, few researchers have investigated its nuances or developed effective sampling techniques to address it. Our survey highlights that mitigation strategies to reduce this bias remain underutilized in practice, distorting the interpretation and comparison of results across the field. In …

Flood Risk Assessment In Humanitarian Contexts: A Remote Sensing And Gis Methodology Applied To Nyarugusu Refugee Camp, Tanzania, Carolyne Vincent Mbirika

Theses

Flooding is a global challenge, with effects mostly experienced in developing countries due to insufficient data for effective flood risk assessment and management. Refugee settlements are particularly vulnerable to flooding due to their remote locations, high population density, and temporary shelters, necessitating flood susceptibility mapping to effectively mitigate risks and minimize damage prior to flooding events. This study assessed flood susceptibility in the Nyarugusu refugee camp, Tanzania, through Multi-criteria Decision Analysis (MCDA) and Analytical Hierarchy Process using remote sensing and Geographic Information Systems (GIS) approaches. The flood susceptibility map that resulted from this process categorizes flood-prone areas into three classes: …

Transfer Learning In Junction With A Light Use Efficiency Model For Estimating Grassland Gross Primary Production, Ruiyang Yu, Yunjun Yao, Qingxin Tang, Xueyi Zhang, Changliang Shao, Joshua B. Fisher, Jiquan Chen, Xiaotong Zhang, Yufu Li, Jia Xu, Lu Liu, Zijing Xie, Jing Ning, Jiahui Fan, Luna Zhang

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

It is significant to simulate grassland gross primary production (GPP) to understand the terrestrial carbon budget over Inner Mongolia (IMG), China. Nevertheless, there is not sufficient in situ GPP data over this region. In this study, we proposed a novel model-based transfer learning (MTL) approach with generative adversarial networks-long short-term memory (GAN-LSTM) and light use efficiency (LUE) models to derive grassland GPP over IMG, China. We first used 25 grassland eddy covariance sites over the conterminous United States to establish the GAN-LSTM model and then fine-tuned it with six sites over IMG to estimate water constraints that were embedded into …

The Urban Surface Of Shanghai Proper, Li Jinan, Tao Kanghua

The Geographical Bulletin

Based on data from aerial photographs the form, material component, and structure of the urban surface of Shanghai Proper are quantitatively mapped, classified, and analyzed. Relationships between the characteristic of the land cover and urban problems are identified. Urban surfaces include natural features such as open water and culture surfaces such as tile roofs, and concrete surfaces. A quantitative analysis of the land cover reveals the historical development of Shanghai and the emergence of an urban basin with the taller buildings at the perimeter, not in the central city. The study also reveals sections of the city where natural hazards …

Generalization Enhancement Strategies To Enable Cross-Year Cropland Mapping With Convolutional Neural Networks Trained Using Historical Samples, Sam Khallaghi, Rahebeh Abedi, Hanan Ali Abou, Hamed Alemohammad, Mary Dziedzorm Asipunu, Ismail Alatise, Nguyen Ha, Boka Luo, Cat Mai, Lei Song, Amos Olertey Wussah, Sitian Xiong

Geography

Mapping agricultural fields using high-resolution satellite imagery and deep learning (DL) models has advanced significantly, even in regions with small, irregularly shaped fields. However, effective DL models often require large, expensive labeled datasets, which are typically limited to specific years or regions. This restricts the ability to create annual maps needed for agricultural monitoring, as changes in farming practices and environmental conditions cause domain shifts between years and locations. To address this, we focused on improving model generalization without relying on yearly labels through a holistic approach that integrates several techniques, including an area-based loss function, Tversky-focal loss (TFL), data …

Spatiotemporal Trends In Anopheles Funestus Breeding Habitats, Grace R. Aduvukha, Elfatih M. Abdel-Rahman, Bester Tawona Mudereri, Onisimo Mutanga, John Odindi, Henri E.Z. Tonnang

All Peer-Reviewed Publications

Effective identification and control of malaria vector larval breeding habitats are crucial for the management and eradication of malaria. Despite its importance, the last decade has seen a decline in data availability and intervention efforts due to reduced attention and prioritization. This study addresses the geographic data scarcity concerning Anopheles funestus larval breeding habitats in a malaria-prone region of western Kenya. Employing a two-step methodological approach, we integrated multi-criteria decision analysis (MCDA) and rule-based fuzzy logic analysis to evaluate the spatiotemporal similarity or divergence of these habitats. The analysis spanned a five-year interval, 2008, 2013, and 2018 with 2013 serving …

Integration Of Geographic Information Systems And Remote Sensing To A Geologic Analysis Of The Llano Uplift,Texas, Michael Clark

The Geographical Bulletin

Developments in Geographic Information Systems (GIS) and Remote Sensing (RS) have provided a practical and economical uses to a variety of disciplines. This paper focuses on the application of this technology to a geologic region using polygon analysis techniques. This application evaluates the feasibility of such methods as compared to conventional geologic field techniques. The Llano Uplift region of central Texas is well defined morphologically and geologically which provides good ground control for aerial photography. A GIS/RS-based analysis scheme is used to extract geologic information from morphological features resulting from surface and subsurface shaping agents. GIS polygon establishment and layer …

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 …