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) …

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 …

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 …

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 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. …

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 …

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 …

Patterns And Drivers Of Recent Disturbances Across The Temperate Forest Biome, Andreas Sommerfeld, Cornelius Senf, Brian Buma, Anthony W. D’Amato, Tiphaine Després, Ignacio Díaz-Hormazábal, Shawn Fraver, Lee E. Frelich, Álvaro G. Gutiérrez, Sarah J. Hart, Brian J. Harvey, Hong S. He, Tomáš Hlásny, Andrés Holz, Thomas Kitzberger, Dominik Kulakowski, David Lindenmayer, Akira S. Mori, Jörg Müller, Juan Paritsis, George L.W. Perry, Scott L. Stephens, Miroslav Svoboda, Monica G. Turner, Thomas T. Veblen, Rupert Seidl

Geography

Increasing evidence indicates that forest disturbances are changing in response to global change, yet local variability in disturbance remains high. We quantified this considerable variability and analyzed whether recent disturbance episodes around the globe were consistently driven by climate, and if human influence modulates patterns of forest disturbance. We combined remote sensing data on recent (2001–2014) disturbances with in-depth local information for 50 protected landscapes and their surroundings across the temperate biome. Disturbance patterns are highly variable, and shaped by variation in disturbance agents and traits of prevailing tree species. However, high disturbance activity is consistently linked to warmer and …

Evaluation Of Modis Land Surface Temperature Data To Estimate Near-Surface Air Temperature In Northeast China, Yuan Z. Yang, Wen H. Cai, Jian Yang

Forestry and Natural Resources Faculty Publications

Air temperature (T_air) near the ground surface is a fundamental descriptor of terrestrial environment conditions and one of the most widely used climatic variables in global change studies. The main objective of this study was to explore the possibility of retrieving high-resolution T_air from the Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) products, covering complex terrain in Northeast China. The All Subsets Regression (ASR) method was adopted to select the predictors and build optimal multiple linear regression models for estimating maximum (T_max), minimum (T_min), and mean (T_mean) air temperatures. …

Accuracy Assessment Of Pictometry® Height Measurements Stratified By Cardinal Direction And Image Magnification Factor, Daniel Unger, David Kulhavy, I-Kuai Hung, Yanli Zhang

Faculty Publications

The aim of this project was to ascertain if Pictometry^® estimated height could be used in lieu of field-based height estimation. Height of a light pole measured with a telescopic height pole was compared to Pictometry^® hyperspatial 4-inch (10.2 centimeters) multispectral imagery estimated light pole height on the campus of Stephen F. Austin State University, Nacogdoches, Texas. Average percent agreement between light pole height and Pictometry^® estimated light pole height summarized by Pictometry^® image magnification factors at 100%, 125%, 150%, 200%, and 300% magnification were within 98% of light pole height with percent disagreement ranging from …

Incorporating Applied Undergraduate Research In Senior To Graduate Level Remote Sensing Courses, Richard Henley, Daniel Unger, David Kulhavy, I-Kuai Hung

Faculty Publications

An Arthur Temple College of Forestry and Agriculture (ATCOFA) senior spatial science undergraduate student engaged in a multi-course undergraduate research project to expand his expertise in remote sensing and assess the applied instruction methodology employed within ATCOFA. The project consisted of performing a change detection land-use/land-cover classification for Nacogdoches and Angelina counties in Texas using satellite imagery. The dates for the imagery were spaced approximately ten years apart and consisted of four different acquisitions between 1984 and 2013. The classification procedure followed and expanded upon a series of concrete theoretical remote sensing principles, transforming the four remotely sensed raster images …

Review Of Broad-Scale Drought Monitoring Of Forests: Toward An Integrated Data Mining Approach, Steven P. Norman, Frank H. Koch, William W. Hargrove

USDA Forest Service / UNL Faculty Publications

Efforts to monitor the broad-scale impacts of drought on forests often come up short. Drought is a direct stressor of forests as well as a driver of secondary disturbance agents, making a full accounting of drought impacts challenging. General impacts can be inferred from moisture deficits quantified using precipitation and temperature measurements. However, derived meteorological indices may not meaningfully capture drought impacts because drought responses can differ substantially among species, sites and regions. Meteorology-based approaches also require the characterization of current moisture conditions relative to some specified time and place, but defining baseline conditions over large, ecologically diverse regions can …

Linking Remote Sensing And Various Site Factors For Predicting The Spatial Distribution Of Eastern Hemlock Occurrence And Relative Basal Area In Maine, Usa, Kathleen Dunckel, Aaron Weiskittel, Greg Fiske, Steven A. Sader, Erika Latty, Amy Arnett

Publications

Introduced invasive pests are perhaps the most important and persistent catalyst for changes in forest composition. Infestation and outbreak of the hemlock woolly adelgid (Adelges tsugae; HWA) along the eastern coast of the USA, has led to widespread loss of hemlock (Tsuga canadensis (L.) Carr.), and a shift in tree species composition toward hardwood stands. Developing an understanding of the geographic distribution of individual species can inform conservation practices that seek to maintain functional capabilities of ecosystems. Modeling is necessary for understanding changes in forest composition, and subsequent changes in biodiversity, and one that can be implemented at the species …

Remote Sensing Estimates Of Stand-Replacement Fires In Russia, 2002–2011, Alexander Krylov, Jessica L. Mccarty, Peter Potapov, Tatiana Loboda, Alexandra Tyukavina, Svetlana Turubanova, Matthew Hansen

Michigan Tech Research Institute Publications

The presented study quantifies the proportion of stand-replacement fires in Russian forests through the integrated analysis of Landsat and Moderate Resolution Imaging Spectroradiometer (MODIS) data products. We employed 30 m Landsat Enhanced Thematic Mapper Plus derived tree canopy cover and decadal (2001–2012) forest cover loss (Hansen et al 2013 High-resolution global maps of 21st-century forest cover change Science 342 850–53) to identify forest extent and disturbance. These data were overlaid with 1 km MODIS active fire (earthdata.nasa.gov/data/near-real-time-data/firms) and 500 m regional burned area data (Loboda et al 2007 Regionally adaptable dNBR-based algorithm for burned area mapping from …

Measuring Tree Height Using Pictometry Hyperspatial Imagery, Daniel Unger, David Kulhavy, Matthew A. Wade, I-Kuai Hung

Faculty Publications

Trees within Nacogdoches, Texas were measured for height using Pictometry hyperspatial imagery at 4 inch spatial resolution. Trees measured included baldcypress located on LaNana Creek as part of a hybrid analysis study. Baldcypress, Taxodiumdistichum, was planted along La Nana Creek, Nacogdoches, Texas, for erosion control and as a test bank for growth of the species genotypes. Each tree was located with GPS and entered into the GIS data base in the Arthur Temple College of Forestry and Agriculture, Stephen F. Austin State University. Actual tree height, measured using a height pole in 0.1 inch increments, was compared to …

Quantitative Analysis Of Woodpecker Habitat Using High-Resolution Airborne Lidar Estimates Of Forest Structure And Composition, James E. Garabedian, Robert Mcgaughey, Stephen E. Reutebuch, Bernard R. Parresol, John C. Kilgo, Christopher E. Moorman, M. Nils Peterson

USDA Forest Service / UNL Faculty Publications

Light detection and ranging (LiDAR) technology has the potential to radically alter theway researchers and managers collect data onwildlife–habitat relationships. To date, the technology has fostered several novel approaches to characterizing avian habitat, but has been limited by the lack of detailed LiDAR-habitat attributes relevant to species across a continuum of spatial grain sizes and habitat requirements. We demonstrate a novel three-step approach for using LiDAR data to evaluate habitat based on multiple habitat attributes and accounting for their influence at multiple grain sizes using federally endangered red-cockaded woodpecker (RCW; Picoides borealis) foraging habitat data fromthe Savannah River Site (SRS) …

Low Mortality In Tall Tropical Trees, R. Q. Thomas, J. R. Kellner, D. B. Clark, D. R. Peart

Dartmouth Scholarship

The dynamics of the tallest trees in tropical forests are of special interest due to their carbon content, canopy dominance, and the large canopy gaps created when they die. Known ecological mechanisms that may influence tall tree survival lead to conflicting predictions. Hydraulic stress and exposure to high winds and desiccation should increase death rates, yet the tallest trees have the greatest access to light and escape damage caused by falling boles and branches. The uncertainty in tall tree mortality rates has been difficult to address due to their low density, which makes mortality rates challenging to estimate accurately. Here, …

A Synoptic Review Of U.S. Rangelands A Technical Document Supporting The Forest Service 2010 Rpa Assessment, Matthew Clark Reeves, John E. Mitchell

USDA Forest Service / UNL Faculty Publications

The Renewable Resources Planning Act of 1974 requires the USDA Forest Service to conduct assessments of resource conditions. This report fulfills that need and focuses on quantifying extent, productivity, and health of U.S. rangelands. Since 1982, the area of U.S. rangelands has decreased at an average rate of 350,000 acres per year owed mostly to conversion to agricultural and residential land uses. Nationally, rangeland productivity has been steady over the last decade, but the Rocky Mountain Assessment Region appears to have moderately increased productivity since 2000. The forage situation is positive and, from a national perspective, U.S. rangelands can probably …

Use Of Remote Sensing To Support Forest And Wetlands Policies In The Usa, Audrey L. Mayer, Ricardo D. Lopez

College of Forest Resources and Environmental Science Publications

The use of remote sensing for environmental policy development is now quite common and well-documented, as images from remote sensing platforms are often used to focus attention on emerging environmental issues and spur debate on potential policy solutions. However, its use in policy implementation and evaluation has not been examined in much detail. Here we examine the use of remote sensing to support the implementation and enforcement of policies regarding the conservation of forests and wetlands in the USA. Specifically, we focus on the “Roadless Rule” and “Travel Management Rules” as enforced by the US Department of Agriculture Forest Service …

Geolite, An Arcgis Extension To Assist In Lidar Data Processing, Yanli Zhang, Jason Grogan, I-Kuai Hung, Ramanathan Sugumaran

Faculty Publications

No abstract provided.

Advanced Digital Image Processing Techniques For Natural Resource Assessment At Stephen F. Austin State University, Daniel Unger

Faculty Presentations

Graduate course work concentrating on land cover classification and digital image processing within the Arthur Temple College of Forestry and Agriculture at Stephen F. Austin State University is presented.

Accuracy Assessment Of Land Cover Maps Derived From Multiple Data Sources, Daniel Unger, Hillary Tribby, Hans Michael Williams, I-Kuai Hung

Faculty Publications

Maximum Likelihood (ML) and Artificial Neural Network (ANN) supervised classification methods were used to demarcate land cover types within IKONOS and Landsat ETM+ imagery. Three additional data sources were integrated into the classification process: Canopy Height Model (CHM), Digital Terrain Model (DTM) and Thermal data. Both the CHM and DTM were derived from multiple return small footprint LIDAR. Forty maps were created and assessed for overall map accuracy, user's accuracy, producer's accuracy, kappa statistic and Z statistic using classification schemes from U.S.G.S. 1976 levels 1 and 2 and T.G.l.C. 1999 levels 2 and 4. Results for overall accuracy of land …