Forest Sciences Commons^™

Satellite-Based Forest Structure Metrics As A Predictive Tool For Biodiversity In Hyperdiverse Tropical Forests: A Test Of The Habitat Heterogeneity Hypothesis In The Tropics, David Luther, Marconi Campos-Cerqueira, Aline Medeiros, Aidan Mccarthy, Emilia Roberts, Xiaoxuan Li, Paulo Bobrowiec, Jared Wolfe, Gabriel Augusto Leite, Tomaz Nascimento De Melo, José W. Ribeiro, Thiago Bicudo, Konrad Wessels

Michigan Tech Publications

Tropical forests hold the most species yet face the greatest threats and knowledge gaps. To improve tropical biodiversity knowledge we combined satellite-based LiDAR with in situ bird, mammal, and acoustic soundscape data, via camera and audio recorders, at the Biological Dynamics of Forest Fragments Project in the Amazon rainforest and tested the habitat heterogeneity-diversity hypothesis as a predictor of alpha diversity in tropical forests. GEDI spaceborne LiDAR was used to assess the predictive power of vertical forest structure on acoustic diversity and species diversity in lowland tropical forests. In 4 months, we detected 201 bird and 35 mammal species representing …

Analysis Of Agricultural Remote Sensing Data Driven By Artificial Intelligence On Crop Growth Patterns And Economic Benefits Of Grain, Yang Wang

Turkish Journal of Agriculture and Forestry

To address the shortcomings of conventional agricultural statistical and monitoring methods on a regional scale, this paper proposes the use of artificial intelligence-driven remote sensing data for analysing crop growth patterns and the economic benefits of grain. Winter wheat data from three stations in a single province from 2011 to 2020 was used, with the leaf area index (LAI) used as the key crop growth indicator value. The simulated annealing algorithm was used to assimilate the LAI and remote sensing leaf area index (MODIS-LAI), simulated by the World Food Study (WOFOST) simulation model, to carry out simulation analysis of winter …

Study Of Fire Regimes In Southwestern Australia Using Geospatial Techniques, Ana Do Carmo Carvalho

Theses: Doctorates and Masters

The Northern Jarrah Forest in Southwestern Australia (SWA), part of a global biodiversity hotspot, is home to fire-sensitive tree species such as marri (Corymbia calophylla) and jarrah (Eucalyptus marginata). As climate change intensifies drought and extreme fire events, understanding the drivers of fire severity is increasingly critical. This thesis analyses fire regimes within the Mundaring drinking water catchment to better understand the spatiotemporal complexity of fire severity in relation to fire history and environmental factors.

The thesis commences with a review of three Fire History Databases (FHDs) used in SWA, highlighting significant inconsistencies and data gaps across time and space. …

Mapping Peatland Distribution And Quantifying Peatland Below-Ground Carbon Stocks In Colombia's Eastern Lowlands, A. Uhde, A. M. Hoyt, L. Hess, C. Schmullius, E. Mendoza, J. C. Benavides, S. Trumbore, J. M. Martín-López, Patrick Nicolas Skillings-Neira, R. S. Winton

Michigan Tech Publications

The extent and distribution of tropical peatlands, and their importance as a vulnerable carbon (C) store, remain poorly quantified. Although large peatland complexes in Peru, the Congo basin, and Southeast Asia have been mapped in detail, information on many other tropical areas is uncertain. In the Eastern Colombian lowlands, peatland area estimates range from 700 km2 to nearly 60,000 km2, leading to highly uncertain C stocks. Using new field data, high-resolution Earth observation (EO), and a random forest approach, we mapped peatlands across Colombian territory East of the Andes below 400 m elevation. We estimated peatland extent using two approaches: …

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 …

An Evaluation Of Fuel Model Accuracy And Multi-Scale Mitigation Strategies In The Wildland-Urban Interface Of Southern Humboldt County, Julia I. Cavalli

Cal Poly Humboldt theses and projects

Strategic placement of fuel treatments is critical for mitigating wildfire risk and reducing potential structure losses in wildland-urban interface (WUI) communities. As wildfire activity accelerates across the western United States, the need to identify high-impact fuel treatment locations grows increasingly urgent. Concurrently, housing development in the WUI is expanding, intensifying the exposure of homes and infrastructure to wildfire threats. In response, many communities are looking to mitigate the likelihood and severity of losses during wildfire events. The success of these efforts depends, in part, on robust data to support strategic placement of effective treatments that reduce fuel availability.

This study …

Tree Crown Economics Of Broadleaf Deciduous Forests, Yiting Fan

Graduate Theses, Dissertations, and Problem Reports (ETD)

Tree crown architecture, a critical determinant of forest ecosystem processes such as photosynthesis, evapotranspiration, and spectral reflectance, is shaped by adaptive trade-offs in resource use and environmental responses. However, significant gaps remain in our understanding of how these traits vary across species, environmental gradients, and temporal scales. This dissertation addresses these gaps by employing remote sensing data across three interconnected studies. Together, these studies advance tree crown economic theory, highlighting how crown traits mediate trade-offs between light capture and water-use efficiency and how these traits influence forest responses to global change. Collectively, this dissertation offer insights for improving models that …

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. …

Identification, Mapping And Treatment Of The Invasive Rosa Multiflora Using Unmanned Aerial Systems And Machine Learning Models, Kylie Virginia Shaw

Graduate Theses, Dissertations, and Problem Reports (ETD)

Invasive species are introduced species that cause detrimental impacts to the native ecosystem or cause harm to human health. The work necessary for land managers to survey for and treat invasive species takes up limited time, labor, and financial resources. This study assesses how Unmanned Aerial Systems (UAS) and machine learning models can be used to make the identification, mapping, and treatment of invasive vegetation more efficient and effective. A UAS-mounted multispectral camera captured images of our target species, Rosa multiflora (multiflora rose), throughout its growing season in southwest Pennsylvania. A random forest machine learning model was trained on these …

Bridging The Gap Between Plot-Level And Landscape-Scale Analysis For Wildfire Risk Assessment, Vanessa Leigh Niemczyk

Graduate Student Theses, Dissertations, & Professional Papers

Remote sensing technology has advanced greatly over the past couple of decades proving its ability to aid in wildfire risk assessment and improve our understanding of forest structure and fuel inventory across the landscape. While some aerial and satellite sensors perform better than others, they all have a common weakness, their reduced ability to capture understory fuels with high detail. Terrestrial laser scanning is an emerging solution due to its understory perspective. This research leverages the beneficial aspects of both terrestrial laser scanning and various aerial- or satellite-based remote sensing platforms (aerial laser scanning, digital aerial photogrammetry, and Sentinel-2) to …

Assessing Spatial Distribution And Quantification Of Native Trees In Saskatchewan's Prairie Landscape Using Remote Sensing Techniques, Elham Shafeian, Bryan J. Mood, Kenneth W. Belcher, Colin P. Laroque

Aspen Bibliography

The importance of trees in non-forest landscapes has been the focus of only a few studies. However, these trees provide many important ecosystem services. In this study, we mapped and quantified these trees using Sentinel-2 (S2) and very high-resolution (VHR) Google satellite imagery without any field campaigns. We performed a Random Forest (RF) classification to map the spatial distribution of native trees in different scenarios. The optimal model showed an overall accuracy and kappa of 0.99 and 0.98, respectively. We mapped 40,500 km² of tree cover, including native tree cover (approximately 29,565 km²≈10.5%), excluding plantations, regional and …

Prediction Of Turfgrass Quality Using Multispectral Uav Imagery And Ordinal Forests: Validation Using A Fuzzy Approach, Alexander Hernandez, Shaun Bushman, Paul Johnson, Matthew D. Robbins, Kaden Patten

Plants, Soils, and Climate Faculty Publications

Protocols to evaluate turfgrass quality rely on visual ratings that, depending on the rater’s expertise, can be subjective and susceptible to positive and negative drifts. We developed seasonal (spring, summer and fall) as well as inter-seasonal machine learning predictive models of turfgrass quality using multispectral and thermal imagery collected using unmanned aerial vehicles for two years as a proof-of-concept. We chose ordinal regression to develop the models instead of conventional classification to account for the ranked nature of the turfgrass quality assessments. We implemented a fuzzy correction of the resulting confusion matrices to ameliorate the probable drift of the field-based …

Mapping Urban Tree Canopy Using Publicly Available Satellite Data, Rosemary Mcguinness

Theses and Dissertations

This project addresses the need for accessible, cost-effective tools for quantifying spatial and temporal changes in tree canopy cover in urban areas. Urban tree canopy provides a wide range of ecosystem services, including lowering air temperatures, reducing pollution, and mitigating stormwater runoff. Cities around the world have placed the expansion of their urban forests at the center of their sustainability goals. Consistent and timely data on urban tree canopy is essential for urban greening initiatives to succeed. Existing methods of accessing information about urban tree canopy are highly technical, costly, and labor-intensive, while the freely available source of tree canopy …

Integrating Forest Structural Diversity Measurement Into Ecological Research, Jeff W. Atkins, Parth Bhatt, Luis Carrasco, Emily Francis, James E. Garabedian, Christopher R. Hakkenberg, Brady S. Hardiman, Jinha Jung, Anil Koirala, Elizabeth A. Larue, Sungchan Oh, Gang Shao, Guofan Shao, H. H. Shugart, Anna Spiers, Atticus E.L. Stovall, Thilina D. Surasinghe, Xiaonan Tai, Lu Zhai, Tao Zhang, Keith Krause

Michigan Tech Publications

The measurement of forest structure has evolved steadily due to advances in technology, methodology, and theory. Such advances have greatly increased our capacity to describe key forest structural elements and resulted in a range of measurement approaches from traditional analog tools such as measurement tapes to highly derived and computationally intensive methods such as advanced remote sensing tools (e.g., lidar, radar). This assortment of measurement approaches results in structural metrics unique to each method, with the caveat that metrics may be biased or constrained by the measurement approach taken. While forest structural diversity (FSD) metrics foster novel research opportunities, understanding …

Object-Detection From Multi-View Remote Sensing Images: A Case Study Of Fruit And Flower Detection And Counting On A Central Florida Strawberry Farm, Caiwang Zheng, Tao Liu, Amr Abd-Elrahman, Vance M. Whitaker, Benjamin Wilkinson

Michigan Tech Publications

Object detection in remote sensing images is one of the most critical computer vision tasks for various earth observation applications. Previous studies applied object detection models to orthomosaic images generated from the SfM (Structure-from-Motion) analysis to perform object detection and counting. However, some small objects that are occluded from the vertical view but observable in raw images from the oblique views cannot be detected in the orthomosaic image, leading to an occlusion issue that cannot be resolved with the traditional orthophoto-based approach. Taking strawberry detection as a case study, the objective of this study is to detect small objects directly …

Remote Sensing Characterization Of Ecosystem Structure And Functional Types To Inform On Biodiversity Conservation In The Lowland Chocó Rainforest, Derek Tesser

Dissertations, Theses, and Capstone Projects

This dissertation focuses on the utilization of remote sensing techniques to characterize ecosystem structure and functional types to inform on biodiversity conservation. This work is motivated by a guiding hypothesis that increased degradation of tropical forest biodiversity due to human activity results in in measurable changes in ecosystem processes that can be detected using remote sensing technologies. Throughout this dissertation, testing of aspects of this hypothesis involve comparing areas with varying degrees of human-induced degradation in a biodiverse tropical ecoregion, the lowland Chocó rainforest of Ecuador. Remote sensing data is used to evaluate changes in vegetation structure, thermal regimes, and …

Remote Sensing In Mapping Biodiversity – A Case Study Of Epiphytic Lichen Communities, Ida Palmroos, Veera Norros, Sarita Keski-Saari, Janne Mäyrä, Topi Tanhuanpää, Sonja Kivinen, Juha Pykälä, Peter Kullberg, Timo Kumpula, Petteri Vihervaara

Aspen Bibliography

In boreal forests, European aspen (Populus tremula L.) is a keystone species that hosts a variety of accompanying species including epiphytic lichens. Forest management actions have led to a decrease in aspen abundance and subsequent loss of suitable habitats of epiphytic lichens. In this study, we evaluate the environmental responses of epiphytic lichen species richness and community composition on aspen, focusing on the potential of remote sensing by combined hyperspectral imaging and airborne laser scanning to identify suitable habitats for epiphytic lichens. We measured different substrate and habitat parameters in the field (e.g., aspen diameter and bark pH) …

Mapping Forest Structure In Mississippi Using Lidar Remote Sensing, Nitant Rai

Theses and Dissertations

This study aimed at evaluating the agreement of spaceborne Light Detection and Ranging (lidar) ICESat-2 canopy height with Airborne Laser Scanning (ALS) derived canopy height to inform about the performance of ICESat-2 canopy height metrics and understand its uncertainties and utilities. The agreement was assessed for different forest types, physiographic regions, a range of percent canopy cover, and diverse disturbance histories. Results of this study suggest that best agreements are found using strong beam data collected at night for canopy height retrieval using ICESat-2. The ICESat-2 showed great potential for estimating canopy heights, particularly in evergreen forests with high canopy …

Assessing Turgor Loss Point In Bottomland Hardwood Trees Using Leaf Spectroscopy, Alexandra M. Eisley

LSU Master's Theses

Climate change is expected to radically alter our planet’s forests, with higher frequencies of drought- and flood-induced mortality events posing a challenge for forest managers and biologists. Research into the factors underlying plant tolerance to environmental stressors is therefore gaining popularity for incorporation into projective and earth system modeling using remote sensing measures. Leaf turgor loss point (TLP) is a key trait associated with drought tolerance among plants and is defined as the water potential at which leaf turgor pressure reaches zero, causing wilting. Here, I investigated patterns of TLP across the landscape and its role as an indicator of …

Quantifying Aboveground Biomass In A Tropical Forest Using A Lidar Waveform Weighted Allometric Model, Alejandro Rojas

Theses and Dissertations

Our knowledge of the distribution and amount of terrestrial above ground biomass (AGB) has increased using lidar technology. Recent advancements in satellite lidar has enabled global mapping of forest biomass and structure. However, there are large biases in satellite lidar estimates which impacts our understanding of carbon dynamics, particularly in tropical forests.

Ni-Meister et al. (2022) developed a lidar full waveform weighted height-based allometric model which produced very good results in temperate deciduous/conifer forest in the continental US. The purpose of this study was to evaluate this biomass model in an African tropical forest using the Land Vegetation and Ice …

Using Lidar To Estimate Carbon Sequestration Of Evergreen Trees At Eastern Washington University (Ewu) Campus, Cheney, Washington, Kristy A. Snyder

2022 Symposium

EWU contains a variety of deciduous and evergreen trees across its campus, providing several benefits. However, no comprehensive record exists of the total number, location, species, or ages of these trees. This knowledge can inform facilities of proper care for individual trees and can be used to estimate carbon sequestration on campus. Traditional on-the-ground methods for assessing trees require tree cores or clinometers, making trees susceptible to pests or disease and leading to inaccurate results. Remote sensing using lidar data is a noninvasive, more precise method to measure tree height and subsequently assess tree age. This poster explores using point …

A Review Of Landcover Classification With Very-High Resolution Remotely Sensed Optical Images—Analysis Unit, Model Scalability And Transferability, Rongjun Qin, Tao Liu

Michigan Tech Publications, Part 1

As an important application in remote sensing, landcover classification remains one of the most challenging tasks in very-high-resolution (VHR) image analysis. As the rapidly increasing number of Deep Learning (DL) based landcover methods and training strategies are claimed to be the state-of-the-art, the already fragmented technical landscape of landcover mapping methods has been further complicated. Although there exists a plethora of literature review work attempting to guide researchers in making an informed choice of landcover mapping methods, the articles either focus on the review of applications in a specific area or revolve around general deep learning models, which lack a …

Fine-Scale Mapping Of Natural Ecological Communities Using Machine Learning Approaches, Parth Bhatt, Ann Maclean, Yvette Dickinson, Chandan Kumar

Michigan Tech Publications, Part 1

Remote sensing technology has been used widely in mapping forest and wetland communities, primarily with moderate spatial resolution imagery and traditional classification techniques. The success of these mapping efforts varies widely. The natural communities of the Laurentian Mixed Forest are an important component of Upper Great Lakes ecosystems. Mapping and monitoring these communities using high spatial resolution imagery benefits resource management, conservation and restoration efforts. This study developed a robust classification approach to delineate natural habitat communities utilizing multispectral high-resolution (60 cm) National Agriculture Imagery Program (NAIP) imagery data. For accurate training set delineation, NAIP imagery, soils data and spectral …

Identifying Conifer Tree Vs. Deciduous Shrub And Tree Regeneration Trajectories In A Space-For-Time Boreal Peatland Fire Chronosequence Using Multispectral Lidar, Humaira Enayetullah, Laura Chasmer, Christopher Hopkinson, Dan Thompson, Danielle Cobbaert

Aspen Bibliography

Wildland fires and anthropogenic disturbances can cause changes in vegetation species composition and structure in boreal peatlands. These could potentially alter regeneration trajectories following severe fire or through cumulative impacts of climate-mediated drying, fire, and/or anthropogenic disturbance. We used lidar-derived point cloud metrics, and site-specific locational attributes to assess trajectories of post-disturbance vegetation regeneration in boreal peatlands south of Fort McMurray, Alberta, Canada using a space-for-time-chronosequence. The objectives were to (a) develop methods to identify conifer trees vs. deciduous shrubs and trees using multi-spectral lidar data, (b) quantify the proportional coverage of shrubs and trees to determine environmental conditions driving …

Satellite Evidence Of Canopy-Height Dependence Of Forest Drought Resistance In Southwestern China, Peipei Xu, Wei Fang, Tao Zhou, Hu Li, Xiang Zhao, Spencer Berman, Ting Zhang, Chuixiang Yi

Publications and Research

The frequency and intensity of drought events are increasing with warming climate, which has resulted in worldwide forest mortality. Previous studies have reached a general consensus on the size-dependency of forest resistance to drought, but further understanding at a local scale remains ambiguous with conflicting evidence. In this study, we assessed the impact of canopy height on forest drought resistance in the broadleaf deciduous forest of southwestern China for the 2010 extreme drought event using linear regression and a random forest (RF) model. Drought condition was quantified with standardized precipitation evapotranspiration index (SPEI) and drought resistance was measured with the …

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 …

Improved Boreal Forest Wildfire Fuel Type Mapping In Interior Alaska Using Aviris-Ng Hyperspectral Data, Christopher William Smith, Santosh K. Panda, Uma Suren Bhatt, Franz J. Meyer

Aspen Bibliography

In Alaska the current wildfire fuel map products were generated from low spatial (30 m) and spectral resolution (11 bands) Landsat 8 satellite imagery which resulted in map products that not only lack the granularity but also have insufficient accuracy to be effective in fire and fuel management at a local scale. In this study we used higher spatial and spectral resolution AVIRIS-NG hyperspectral data (acquired as part of the NASA ABoVE project campaign) to generate boreal forest vegetation and fire fuel maps. Based on our field plot data, random forest classified images derived from 304 AVIRIS-NG bands at Viereck …

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 …

Analysis Of Designs Used In Monitoring Crop Growth Based On Remote Sensing Methods, Cristina Teodora Dobrota, Rahela Carpa, Anca Butiuc-Keul

Turkish Journal of Agriculture and Forestry

Choosing appropriate designs and methods for monitoring crop growth is a challenging process of major importance. Remote sensing from space and manned or unmanned airborne operations are used to measure crop reflectance and a wide variety of other agricultural parameters. While some experiments use only a few, specific methods and designs and organize the results in lists of evidence, other experiments use a wider range of techniques to create a more credible and comprehensive assessment of crop yield. Particular situations related to the available resources in terms of data collection and expertise in addition to the intended use of the …

Investigating Surface Temperature From First Principles: Seedling Survival, Microclimate Buffering, And Implications For Forest Regeneration, Robin Rank

Graduate Student Theses, Dissertations, & Professional Papers

Forests are extremely important ecosystems with large impacts on global water, energy, and biogeochemical cycling, and they provide numerous ecosystems services to human populations. Even though these systems consist of long-lived vegetation, forests are constantly experiencing changes to their extent and composition through the interacting forces of disturbance dynamics and climate change. In semi-arid landscapes like the western United States, patterns of recurring wildfire and subsequent seedling recruitment and forest regeneration are important in establishing the distribution of forests on the landscape. In this context, climate, hydrology, and existing vegetation all act together to limit the current and potential range …