Life Sciences Commons^™

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, Part 2

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, Part 2

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 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 …

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

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

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 …

Comparison Of Low-Cost Commercial Unpiloted Digital Aerial Photogrammetry To Airborne Laser Scanning Across Multiple Forest Types In California, James Edward Lamping

Cal Poly Humboldt theses and projects

Science-based forest management requires quantitative information about forest attributes traditionally collected via sampled field plots in a forest inventory program. Remote sensing tools, such as active three-dimensional (3D) Light Detection and Ranging (lidar), are increasingly utilized to supplement and even replace field-based forest inventories. However, lidar remains cost prohibitive for smaller areas and repeat measurement, often limiting its use to single acquisitions of large contiguous areas. Recent advancements in unpiloted aerial systems (UAS), digital aerial photogrammetry (DAP) and high precision global positioning systems (HPGPS) have the potential to provide low-cost time and place flexible 3D data to support forest inventory …

Regional Impacts Of Invasive Species And Climate Change On Black Ash Wetlands, Joseph Shannon

Dissertations, Master's Theses and Master's Reports

For more than a decade intensive research on the ecohydrology of black ash wetland ecosystems has been performed to understand these systems before they are drastically altered by the invasive species, emerald ash borer (EAB). In that time there has been little research aimed at the scale and persistence of the alterations. Three distinct but related research articles will be presented to demonstrate a method for moderate resolution mapping of black ash across its entire range, understand the relative impacts of EAB and climate change on probable future wetland conditions, and develop an experimental and modeling approach to quantify and …

Extreme Fire As A Management Tool To Combat Regime Shifts In The Range Of The Endangered American Burying Beetle, Alison K. Ludwig, Daniel R. Uden, Dirac Twidwell

Department of Agronomy and Horticulture: Dissertations, Theses, and Student Research

This study is focused on the population of federally-endangered American burying beetles in south-central Nebraska. It is focused on changes in land cover over time and at several levels of spatial scale, and how management efforts are impacting both the beetle and a changing landscape. Our findings are applicable to a large portion of the Great Plains, which is undergoing the same shift from grassland to woodland, and to areas where the beetle is still found.

Remote Sensing Monitoring Of Vegetation Dynamic Changes After Fire In The Greater Hinggan Mountain Area: The Algorithm And Application For Eliminating Phenological Impacts, Zhibin Huang, Chunxiang Cao, Wei Chen, Min Xu, Yongfeng Dang, Ramesh P. Singh, Barjeece Bashir, Bo Xie, Xiaojuan Lin

Mathematics, Physics, and Computer Science Faculty Articles and Research

Fires are frequent in boreal forests affecting forest areas. The detection of forest disturbances and the monitoring of forest restoration are critical for forest management. Vegetation phenology information in remote sensing images may interfere with the monitoring of vegetation restoration, but little research has been done on this issue. Remote sensing and the geographic information system (GIS) have emerged as important tools in providing valuable information about vegetation phenology. Based on the MODIS and Landsat time-series images acquired from 2000 to 2018, this study uses the spatio-temporal data fusion method to construct reflectance images of vegetation with a relatively consistent …

Remote Sensing Approaches To Predict Forest Characteristics In Northwest Montana, Ryan P. Rock

Graduate Student Theses, Dissertations, & Professional Papers

Remote sensing can be utilized by land management organizations to save money and time. Mapping vegetation using either aerial photographs or satellite imagery and the applications for forest management are of particular interest to the Montana Department of Natural Resources. In 2018, the organization began a pilot program to test the incorporation of raster analysis of remotely sensed data into their inventory program and had limited success. This analysis identified two areas of improvement: the selection method of inventory plots and the imagery used for classification and metrics. This study found that selecting inventory plots using a generalized random tessellation …

Remote Sensing Of Ploidy Level In Quaking Aspen (Populus Tremuloides Michx.), Benjamin Blonder, Bente J. Graae, Burke Greer, Marja Haagsma, Kenny Helsen, Rozália E. Kapás, Henry Pai, Jolanta Rieksta, Dillon Sapena, Christopher J. Still, Richard Strimbeck

Aspen Bibliography

1. Ploidy level in plants may influence ecological functioning, demography and response to climate change. However, measuring ploidy level typically requires intensive cell or molecular methods.
2. We map ploidy level variation in quaking aspen, a dominant North American tree species that can be diploid or triploid and that grows in spatially extensive clones. We identify the predictors and spatial scale of ploidy level variation using a combination of genetic and ground‐based and airborne remote sensing methods.
3. We show that ground‐based leaf spectra and airborne canopy spectra can both classify aspen by ploidy level with a precision‐recall harmonic mean of 0.75–0.95 and …

Characterizing Boreal Peatland Plant Composition And Species Diversity With Hyperspectral Remote Sensing, Mara Y. Mcpartland, Michael J. Falkowski, Jason R. Reinhardy, Evan Kane, Randall K Kolka, Merritt R. Turetsky, Et Al.

Michigan Tech Publications

Peatlands, which account for approximately 15% of land surface across the arctic and boreal regions of the globe, are experiencing a range of ecological impacts as a result of climate change. Factors that include altered hydrology resulting from drought and permafrost thaw, rising temperatures, and elevated levels of atmospheric carbon dioxide have been shown to cause plant community compositional changes. Shifts in plant composition affect the productivity, species diversity, and carbon cycling of peatlands. We used hyperspectral remote sensing to characterize the response of boreal peatland plant composition and species diversity to warming, hydrologic change, and elevated CO₂. …

Crown-Level Mapping Of Tree Species And Health From Remote Sensing Of Rural And Urban Forests, Fang Fang

Graduate Theses, Dissertations, and Problem Reports

Tree species composition and health are key attributes for rural and urban forest biodiversity, and ecosystem services preservation. Remote sensing has facilitated extraordinary advances in estimating and mapping tree species composition and health. Yet previous sensors and algorithms were largely unable to resolve individual tree crowns and discriminate tree species or health classes at this essential spatial scale due to the low image spectral and spatial resolution. However, current available very high spatial resolution (VHR) remote sensing data can begin to resolve individual tree crowns and measure their spectral and structural qualities with unprecedented precision. Moreover, various machine learning algorithms …

Interactions Between Fire Severity And Forest Biota In The Central Sierra Nevada: Formation And Impact Of Small-Scale Fire Refugia And The Effect Of Fire On Forest Structure Predictive Of Fisher (Pekania Pennanti) Den Habitat, Erika M. Blomdahl

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Fire is a natural and essential component of forests in western North America. Fire maintains biodiversity through the creation of different habitat types, and regular fire rotations reduce the accumulation of woody fuels and thick understory plant densities that give rise to catastrophic fire. The practice of fire exclusion has altered western forests and increased the risk of widespread change under rising temperatures projected for the 21^st century. To manage for the reintroduction of fire it is critical that we understand the interactions between fire and forest biota in recently fire-suppressed forests.

In Chapter 2, I studied the formation …

Modeling The Response Of Black Walnut -Dominant Mixed Hardwoods To Seasonal Climate Effects With Uav-Based Hyperspectral Sensor And Aerial Photogrammetry, Tyler G. Bradford

MSU Graduate Theses

The development of compact sensors in recent years has inspired the use of UAS-based hyperspectral and aerial imaging techniques for small-scale remote sensing applications. With increasing concerns about climate change, spectrally-derived vegetation indices (VIs) have proven useful for quantifying stress-induced vegetation response. The goal of this study was to develop predictive models and assess methodology for modeling the biological response of a black walnut -dominant mixed hardwood stand to seasonal climate events using UAV-based hyperspectral remote-sensing. The derived VIs were evaluated against the means of four seasonal measures of climate calculated for a two-week period prior to the flight date. …

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 …

Forest Disturbance Detection And Aboveground Biomass Modeling Using Moderate-Resolution, Time-Series Satellite Imagery, John B. Kilbride

Electronic Theses and Dissertations

Human-induced and natural disturbances are an important feature of forest ecosystems. Disturbances influence forest structure and composition and can impact crucial ecosystem services. However, deriving spatially explicit estimates of past forest disturbance across a large region can prove challenging. Researchers have recognized that remote sensing is an important tool for monitoring forest ecosystems and mapping land use and land cover change. One of the most important sources of remotely sensed imagery is the United States Geologic Survey’s Landsat program which has continuously acquired earth observations since 1972. This repository of imagery has the spatial, spectral, and temporal resolution necessary to …

Spatio-Temporal Variations Of Soil Active Layer Thickness In Chinese Boreal Forests From 2000 To 2015, Xiongxiong Bai, Jian Yang, Bo Tao, Wei Ren

Forestry and Natural Resources Faculty Publications

The soil active layer in boreal forests is sensitive to climate warming. Climate-induced changes in the active layer may greatly affect the global carbon budget and planetary climatic system by releasing large quantities of greenhouse gases that currently are stored in permafrost. Ground surface temperature is an immediate driver of active layer thickness (ALT) dynamics. In this study, we mapped ALT distribution in Chinese boreal larch forests from 2000 to 2015 by integrating remote sensing data with the Stefan equation. We then examined the changes of the ALT in response to changes in ground surface temperature and identified drivers of …

Developing A Coastal Gis Model Of Sri Lanka To Pinpoint Areas At Risk Of Tsunamis, John E. Dellysse, Buddhika D. Madurapperuma

IdeaFest: Interdisciplinary Journal of Creative Works and Research from Cal Poly Humboldt

No abstract provided.

Predicting Potential Fire Severity Using Vegetation, Topography And Surface Moisture Availability In A Eurasian Boreal Forest Landscape, Lei Fang, Jian Yang, Megan White, Zhihua Liu

Forestry and Natural Resources Faculty Publications

Severity of wildfires is a critical component of the fire regime and plays an important role in determining forest ecosystem response to fire disturbance. Predicting spatial distribution of potential fire severity can be valuable in guiding fire and fuel management planning. Spatial controls on fire severity patterns have attracted growing interest, but few studies have attempted to predict potential fire severity in fire-prone Eurasian boreal forests. Furthermore, the influences of fire weather variation on spatial heterogeneity of fire severity remain poorly understood at fine scales. We assessed the relative importance and influence of pre-fire vegetation, topography, and surface moisture availability …