Remote Sensing Commons^™

Assessment Of Spatial Autocorrelation And Scalability In Fine-Scale Wildfire Random Forest Prediction Models, Madeleine Pascolini-Campbell, Joshua B. Fisher, Kerry Cawse-Nicholson, Christine M. Lee, Natasha Stavros

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Wildfire prediction models that can be applied across diverse regions at fine scales (<  100 m) are critical for wildfire management. Remote sensing offers a path forward by providing heterogeneous and dynamic measurements of fuel load, type, and flammability. Machine learning methods such as random forests provide an empirical framework that are high-accuracy, computationally efficient, interpretable and able to model complex ecological relationships. Here we use high resolution (70 m, every 3–5 days) remote sensing observations of evapotranspiration and evaporative stress index, which represent plant water stress, from Ecosystem Spaceborne Thermal Radiometer on Space Station (ECOSTRESS), as well as topography and weather data, to predict burn severity and occurrence for 8 large wildfires that burned 3715 km² from 2021 and 2022 in New Mexico, USA. These fires ranged from low to high burn intensity, and covered a diverse range of ecoregions (deserts, grasslands, forests), plant species, and topographies. We used a single model to predict the burn severity of all wildfires one week before occurrence. The prediction accuracy was greatest when using all predictors (ECOSTRESS, weather, topography) (R² = 0.77). We assessed the role of spatial autocorrelation in driving model performance by: (1) increasing the sample spacing of our dataset, (2) …

Considerations And Techniques For Producing Urban Tree Canopy Maps Using Freely Available And Accessible Methods, Hugh Reed Ellerman

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

Urban forests are valued as green infrastructure for the variety of benefits they provide across ecological, social, public health, and economic domains. To understand the distribution of trees, maps are required. Many methods of mapping tree cover use expensive and data-intensive datasets such as hyperspectral and LiDAR imagery, making these methods inaccessible to municipal forest managers. Variations in the modelling approaches of existing, freely available methods are not addressed in sufficient enough detail to understand the trade-offs implicit in these variations. Further, characteristics of urban tree canopy mapping (high spatial resolution imagery, heterogeneous urban environments, the importance of the tree …

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 …

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

Murray State Theses and Dissertations

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

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. …

An Automated Machine Learning Approach To The Retrieval Of Daily Soil Moisture In South Korea Using Satellite Images, Meteorological Data, And Digital Elevation Model, Nari Kim, Soo-Jin Lee, Eunha Sohn, Mija Kim, Seonkyeong Seong, Seung Hee Kim, Yangwon Lee

Institute for ECHO Articles and Research

Soil moisture is a critical parameter that significantly impacts the global energy balance, including the hydrologic cycle, land–atmosphere interactions, soil evaporation, and plant growth. Currently, soil moisture is typically measured by installing sensors in the ground or through satellite remote sensing, with data retrieval facilitated by reanalysis models such as the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis 5 (ERA5) and the Global Land Data Assimilation System (GLDAS). However, the suitability of these methods for capturing local-scale variabilities is insufficiently validated, particularly in regions like South Korea, where land surfaces are highly complex and heterogeneous. In contrast, artificial intelligence …

Uncovering The Dynamic Nature Of Fire Refugia Across Landscapes In Oregon's Western Cascades, Alec Scott Dyer

Dissertations and Theses

With increased fire activity, the presence of fire refugia is critical to support forest resiliency and mitigate large-scale vegetation conversion, however, the persistence of fire refugia within burn perimeters over time is uncertain. This study examines the dynamic nature of fire refugia by mapping the decline in forest cover over time, identifying spatiotemporal patch- and landscape-scale patterns and the biophysical drivers of delayed mortality following the 2020 Labor Day Fires occurring in Oregon’s western Cascades. After three years post-fire, delayed mortality accounted for an additional 8.5% of forest loss (total of 24,147 hectares in all five burns) compared to pre-fire …

Managing The Environmental And Socio-Economic Impacts Of Rohingya Refugees In Bangladesh, Mousume Azad

Master's Projects and Capstones

In August 2017, nearly 1 million Rohingya people fled to Bangladesh to save their lives from the genocide inflicted by the military of Myanmar. At present, over 1.3 million Rohingyas are staying at Cox’s Bazar, Bangladesh, in 34 overcrowded refugee camps. This research examined the environmental impacts especially the change in vegetation cover and land surface temperature as well as the socioeconomic alteration of the host country after the refugee influx. The research found a 5488 ha or 9.58% decrease in forest area, accompanied by an 8.25% increase in refugee settlement areas, an increase in average land surface temperature within …

Aboveground Biomass Density Estimation Using Deep Learning: Insight From Neon Ground-Truth Data And Simulated Gedi Waveform, Ashish Mahaur

Dissertations, Master's Theses and Master's Reports

Accurately estimating Aboveground Biomass Density (AGBD) is crucial for managing Earth's carbon cycle and informing climate strategies. NASA's GEDI mission advances global forest mapping, but traditional linear models often yield less reliable AGBD estimates. This study enhances AGBD estimation using deep learning models with NEON ground-truth data and simulated GEDI waveforms. We compared 1D CNNs, LSTMs, and pre-trained CNNs to traditional models. The ResNet152 model outperformed linear regression, achieving an R² of 0.68, demonstrating a 17% improvement. Our experiments also demonstrate the importance of large, diverse datasets, particularly for training deep learning models.

Production, Best Management Practices, And Market Impacts Of Forest Biomass Harvest And Collection In The Mid-Atlantic Region, William E. Smith

Graduate Theses, Dissertations, and Problem Reports (ETD)

Time motion studies were conducted at five mid-Atlantic sites that spanned various operations in West Virginia, Ohio, and Pennsylvania. The harvest systems included integrated harvests where chips were produced in the forest, roundwood systems where only roundwood was produced, and a centralized chipping system. The study collected overall productivity and machine utilization data at the various harvesting operations. The cost per green ton of woody biomass ranged from $18.46 to $39.8 resulting in an average of $30.33 among the five systems. Hauling had the highest average price per green ton at $9.10, while loading had the lowest at $1.73 per …

Carnivore And Ungulate Occurrence In A Fire-Prone Region, Sara J. Moriarty-Graves

Cal Poly Humboldt theses and projects

Increasing fire size and severity in the western United States causes changes to ecosystems, species’ habitat use, and interspecific interactions. Wide-ranging carnivore and ungulate mammalian species and their interactions may be influenced by an increase in fire activity in northern California. Depending on the fire characteristics, ungulates may benefit from burned habitat due to an increase in forage availability, while carnivore species may be differentially impacted, but ultimately driven by bottom-up processes from a shift in prey availability. I used a three-step approach to estimate the single-species occupancy of four large mammal species: mountain lion (Puma concolor), coyote …

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 …

Delineating Field Variation Using Apparent Electrical Conductivity In An Ozark Highlands Agroforestry System, Shane Reid Ylagan

Graduate Theses and Dissertations

Little to no work has been conducted assessing field variability using repeated electromagnetic induction (EMI) apparent electrical conductivity (ECa) surveys in agroforestry (AF) systems within regions similar to the Ozark Highlands. The objectives of this thesis were to identify i) spatiotemporal ECa variability; ii) ECa-derived soil management zones (SMZs); iii) correlations among EMI-ECa and in-situ, sentential-site soil properties; iv) whether fewer, EMI-ECa surveys could be conducted to capture similar ECa variance as mid-monthly EMI-ECa surveys; v) correlations between ECa and forage yield, tree growth, and terrain attributes based on plant (forage and tree) species, and fertility treatments, and ECa-derived SMZs, …

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 …

Multi-Trophic Biodiversity Increases With Increasing Structural Complexity Of Forest Canopy, Ayanna St. Rose

Graduate Theses and Dissertations

Understanding the effects of forest canopy structural complexity on multi-trophic diversity is critical for conserving biodiversity and managing land sustainably. But multi-trophic diversity is often ignored when making decisions about land management due to lack of cost- and time-effective methods to evaluate it. Here, we explored a new method based on widely available remote sensing data to quantify canopy structural complexity and its relationships with multi-trophic biodiversity at landscape scale using 32 forested sites of the National Ecological Observatory Network. We investigated the influence of vertical and horizontal structural complexity of forest canopy on multi-trophic (primary producers, herbivores (beetles), omnivores …

Observations Of Post-Wildfire Landcover Trends In Boreal Alaska Using A Suite Of Remote Sensing Approaches, Eric John Deutsch

Theses - ALL

Wildfires are a common occurrence in the boreal ecosystems of the Pacific Northwest. Studies suggest that anthropogenic climate change has fostered more frequent and higher severity fires in recent decades in these forests, which may result in substantial changes in vegetation structure and ecosystem functioning. However, large-scale studies examining the linkages between changing boreal wildfire regimes and vegetation structure have historically been limited in spatial scope due to the broad area and inaccessibility of many boreal regions, including the Alaskan interior. The development and advancement of satellite remote sensing instruments and geospatial analysis techniques provide researchers with unmatched abilities to …

Effects Of Bark Beetle Outbreaks On Forest Landscape Pattern In The Southern Rocky Mountains, U.S.A., Kyle C. Rodman, Robert A. Andrus, Cori L. Butkiewicz, Teresa B. Chapman, Nathan S. Gill, Brian J. Harvey, Dominik Kulakowski, Niko J. Tutland, Thomas T. Veblen, Sarah J. Hart

Geography

Since the late 1990s, extensive outbreaks of native bark beetles (Curculionidae: Scolytinae) have affected coniferous forests throughout Europe and North America, driving changes in carbon storage, wildlife habitat, nutrient cycling, and water resource provisioning. Remote sensing is a cru-cial tool for quantifying the effects of these disturbances across broad landscapes. In particular, Landsat time series (LTS) are increasingly used to characterize outbreak dynamics, including the presence and severity of bark beetle-caused tree mortality, though broad-scale LTS-based maps are rarely informed by detailed field validation. Here we used spatial and temporal information from LTS products, in combination with extensive field data …

Regional Forest Volume Estimation By Expanding Lidar Samples Using Multi-Sensor Satellite Data, Bo Xie, Chunxiang Cao, Min Xu, Barjeece Bashir, Ramesh P. Singh, Zhibin Huang, Xiaojuan Lin

Mathematics, Physics, and Computer Science Faculty Articles and Research

Accurate information regarding forest volume plays an important role in estimating afforestation, timber harvesting, and forest ecological services. Traditionally, operations on forest growing stock volume using field measurements are labor-intensive and time-consuming. Recently, remote sensing technology has emerged as a time-cost efficient method for forest inventory. In the present study, we have adopted three procedures, including samples expanding, feature selection, and results generation and evaluation. Extrapolating the samples from Light Detection and Ranging (LiDAR) scanning is the most important step in satisfying the requirement of sample size for nonparametric methods operation and result in accuracy improvement. Besides, mean decrease Gini …

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 …

Using Unmanned Aerial Systems (Drones) With A Thermal Sensor To Map And Count Deer Population, Maxwell C. Ott

Williams Honors College, Honors Research Projects

The number of deer in an area is an important statistic for land managers to know, as overabundance has many negative effects. There are many methods that have been used to count deer in the past, such as using manned helicopters and airplanes, walking on foot, and conducting controlled hunts. UAS (unmanned aerial systems) is a growing field that provides many benefits over traditional methods of counting deer, such as lower cost and missions being less time consuming. Using a thermal sensor attached to a UAS makes it simple to spot any deer during a flight. Two main methods of …

Geographic And Climatic Attributions Of Autumn Land Surface Phenology Spatial Patterns In The Temperate Deciduous Broadleaf Forest Of China, Weiguang Lang, Xiaoqiu Chen, Liang Liang, Shilong Ren, Siwei Qian

Geography Faculty Publications

Autumn vegetation phenology plays a critical role in identifying the end of the growing season and its response to climate change. Using the six vegetation indices retrieved from moderate resolution imaging spectroradiometer data, we extracted an end date of the growing season (EOS) in the temperate deciduous broadleaf forest (TDBF) area of China. Then, we validated EOS with the ground-observed leaf fall date (LF) of dominant tree species at 27 sites and selected the best vegetation index. Moreover, we analyzed the spatial pattern of EOS based on the best vegetation index and its dependency on geo-location indicators and seasonal temperature/precipitation. …

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

Graduate Theses, Dissertations, and Problem Reports (ETD)

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 …

Unmanned Aerial-Vehicle-Based Measurement Of Urban Forests, Earle W. Isibue

Graduate Research Theses & Dissertations

Human and natural forces continually act on urban forests to producing changes that leading to trees being removed or replanted. Therefore, to manage the urban forest effectively, periodic inventories are needed to ensure that information about the urban forest is current and comprehensive. This task has traditionally been accomplished by manual ground-based field surveys, or more recently by lidar; however, these methods are expensive, either in terms of time, labor, or cost. This project proposes a novel method of using Unmanned Aerial Vehicles (UAVs) to more accurately measure urban tree height and trunk diameter than is currently possible using conventional …

Spatio-Temporal Reconstruction Of Remote Sensing Observations, Kamrul Khan

Graduate Theses and Dissertations

The USDA Forest Service aims to use satellite imagery for monitoring and predicting changes in forest conditions over time within the country. We specifically focus on a 230, 400 hectares region in north-central Wisconsin between 2003 - 2012. The auxiliary data collected from the satellite imagery of this region are relatively dense in space and time and can be used to efficiently predict how the forest condition changed over that decade. However, these records have a significant proportion of missing values due to weather conditions and system failures. To fill in these missing values, we build spaciotemporal models based on …

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 …

Vulnerability Of Protected Areas To Human Encroachment, Climate Change And Fire In The Fragmented Tropical Forests Of West Africa, Francis Kwabena Dwomoh

Electronic Theses and Dissertations

The Upper Guinean region of West Africa is home to some of the most globally significant tropical biodiversity hotspots, providing ecosystem services that are crucial for the region’s socio-economic and environmental wellbeing. Nonetheless, following decades of human-caused destruction of natural habitats, protected areas currently remain the only significant refugia of original vegetation relics in landscapes that are highly fragmented. Aside from having strong geographic variation in land use, climate, vegetation, and human population, the region has also experienced remarkable biophysical and socio-economic changes in recent decades. All these factors influence the fire regime and the vulnerability of forests within protected …

Implications Of Unmanned Aircraft Systems And Sense Of Place: A Case Study In The Mono Basin, Sara Elizabeth Matthews

Cal Poly Humboldt theses and projects

This paper contributes to an understanding of the social implications of using UAS in natural resource areas; specifically, the ways in which these tools impact human constructed sense of place. This paper draws on in-depth interviews and document analysis to (a) develop an understanding of place meanings held among Mono Basin stakeholders and (b) define the ways in which increased UAS presence may interact with these visions of place.

In short, this research shows that sense of place in this rural area is influential in the way that UAS are received by local stakeholders. The changing nature of place meanings …

Rapid Land Cover Map Updates Using Change Detection And Robust Random Forest Classifiersrapid Land Cover Map Updates Using Change Detection And Robust Random Forest Classifiers, Konrad J. Wassels, Frans Van Den Bergh, David P. Roy, Brian P. Salmon, Karen C. Steenkemp, Bryan Macalister, Derick Swanepoel, Debbie Jewitt

GSCE Faculty Publications

The paper evaluated the Landsat Automated Land Cover Update Mapping (LALCUM) system designed to rapidly update a land cover map to a desired nominal year using a pre-existing reference land cover map. The system uses the Iteratively Reweighted Multivariate Alteration Detection (IRMAD) to identify areas of change and no change. The system then automatically generates large amounts of training samples (n > 1 million) in the no-change areas as input to an optimized Random Forest classifier. Experiments were conducted in the KwaZulu-Natal Province of South Africa using a reference land cover map from 2008, a change mask between 2008 and …

A Model Of The Effects Of Deforestation On Local Climate In The North Cascades, Monica R. H. Jasper

Geography and the Environment: Graduate Student Capstones

Changes in areal extent of land cover types may lead to alterations in the surface energy budget that contribute to anthropogenic climate forcing. This study examines the effects of deforestation in the Cascade Range on local temperature. Temperature sensors were installed in 14 forest stands, taking measurements for one year. Estimated tree age, circumference, and species were recorded to calculate stand density index. Satellite imagery was used to calculate shade fraction from spectral mixture analysis, which is a proxy for canopy structure and density. These data were used to construct seasonal cycles of temperature to model variation with stand density …