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Michigan Technological University

Michigan Tech Publications

Geography

Articles 1 - 18 of 18

Full-Text Articles in Social and Behavioral Sciences

Mapping Historical Archaeology And Industrial Heritage: The Historical Spatial Data Infrastructure, Daniel Trepal, Don Lafreniere, Timothy Stone Oct 2021

Mapping Historical Archaeology And Industrial Heritage: The Historical Spatial Data Infrastructure, Daniel Trepal, Don Lafreniere, Timothy Stone

Michigan Tech Publications

While a vibrant and growing research literature exists on the value of GIS to archaeology in general, the application of geospatial digital data to the subfield of historical archaeology is less well developed, especially in North America. This is particularly true for the era of industrialization, where the archaeological record is accompanied by a comparatively rich historical record. Historical and industrial archaeology are fundamentally bound up in the interplay between material and historical data, and it is in enhancing the dialogue between these two evidentiary bodies that interdisciplinary geospatial approaches are most fruitful to these subdisciplines. Drawing on recent discussions …

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Using Uncrewed Aerial Vehicles For Identifying The Extent Of Invasive Phragmites Australis In Treatment Areas Enrolled In An Adaptive Management Program, Colin Brooks, Charlotte Weinstein, Andrew Poley, Amanda Grimm, Nicholas Marion, Laura Bourgeau-Chavez, Dana Hansen, Kurt Kowalski May 2021

Using Uncrewed Aerial Vehicles For Identifying The Extent Of Invasive Phragmites Australis In Treatment Areas Enrolled In An Adaptive Management Program, Colin Brooks, Charlotte Weinstein, Andrew Poley, Amanda Grimm, Nicholas Marion, Laura Bourgeau-Chavez, Dana Hansen, Kurt Kowalski

Michigan Tech Publications

Higher spatial and temporal resolutions of remote sensing data are likely to be useful for ecological monitoring efforts. There are many different treatment approaches for the introduced European genotype of Phragmites australis, and adaptive management principles are being integrated in at least some long-term monitoring efforts. In this paper, we investigated how natural color and a smaller set of near-infrared (NIR) images collected with low-cost uncrewed aerial vehicles (UAVs) could help quantify the aboveground effects of management efforts at 20 sites enrolled in the Phragmites Adaptive Management Framework (PAMF) spanning the coastal Laurentian Great Lakes region. We used object-based image …

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Multi-Source Eo For Dynamic Wetland Mapping And Monitoring In The Great Lakes Basin, Michael Battaglia, Sarah Banks, Amir Behnamian, Laura Bourgeau-Chavez Feb 2021

Multi-Source Eo For Dynamic Wetland Mapping And Monitoring In The Great Lakes Basin, Michael Battaglia, Sarah Banks, Amir Behnamian, Laura Bourgeau-Chavez

Michigan Tech Publications

Wetland managers, citizens and government leaders are observing rapid changes in coastal wetlands and associated habitats around the Great Lakes Basin due to human activity and climate variability. SAR and optical satellite sensors offer cost effective management tools that can be used to monitor wetlands over time, covering large areas like the Great Lakes and providing information to those making management and policy decisions. In this paper we describe ongoing efforts to monitor dynamic changes in wetland vegetation, surface water extent, and water level change. Included are assessments of simulated Radarsat Constellation Mission data to determine feasibility of continued monitoring …

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Quantifying Surface Severity Of The 2014 And 2015 Fires In The Great Slave Lake Area Of Canada, Nancy H. F. French, Jeremy Graham, Ellen Whitman, Laura Bourgeau-Chavez Oct 2020

Quantifying Surface Severity Of The 2014 And 2015 Fires In The Great Slave Lake Area Of Canada, Nancy H. F. French, Jeremy Graham, Ellen Whitman, Laura Bourgeau-Chavez

Michigan Tech Publications

The focus of this paper was the development of surface organic layer severity maps for the 2014 and 2015 fires in the Great Slave Lake area of the Northwest Territories and Alberta, Canada, using multiple linear regression models generated from pairing field data with Landsat 8 data. Field severity data were collected at 90 sites across the region, together with other site metrics, in order to develop a mapping approach for surface severity, an important metric for assessing carbon loss from fire. The approach utilised a combination of remote sensing indices to build a predictive model of severity that was …

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Paul Robeson, Carnival, And The 2018 National Eisteddfod, Mark Rhodes May 2020

Paul Robeson, Carnival, And The 2018 National Eisteddfod, Mark Rhodes

Michigan Tech Publications

No abstract provided.

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American Influences At The National Eisteddfod, Mark Rhodes Apr 2020

American Influences At The National Eisteddfod, Mark Rhodes

Michigan Tech Publications

No abstract provided.

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Mapping Kenyan Grassland Heights Across Large Spatial Scales With Combined Optical And Radar Satellite Imagery, Olivia S. B. Spagnuolo, Julie C. Jarvey, Michael Battaglia, Zachary Laubach, Mary Ellen Miller, Kay E. Holekamp, Laura Bourgeau-Chavez Mar 2020

Mapping Kenyan Grassland Heights Across Large Spatial Scales With Combined Optical And Radar Satellite Imagery, Olivia S. B. Spagnuolo, Julie C. Jarvey, Michael Battaglia, Zachary Laubach, Mary Ellen Miller, Kay E. Holekamp, Laura Bourgeau-Chavez

Michigan Tech Publications

Grassland monitoring can be challenging because it is time-consuming and expensive to measure grass condition at large spatial scales. Remote sensing offers a time- and cost-effective method for mapping and monitoring grassland condition at both large spatial extents and fine temporal resolutions. Combinations of remotely sensed optical and radar imagery are particularly promising because together they can measure differences in moisture, structure, and reflectance among land cover types. We combined multi-date radar (PALSAR-2 and Sentinel-1) and optical (Sentinel-2) imagery with field data and visual interpretation of aerial imagery to classify land cover in the Masai Mara National Reserve, Kenya using …

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Assessing Boreal Peat Fire Severity And Vulnerability Of Peatlands To Early Season Wildland Fire, Laura Bourgeau-Chavez, Sarah L. Grelik, Michael Billmire, Liza K. Jenkins, Eric S. Kasischke, Merritt R. Turetsky Feb 2020

Assessing Boreal Peat Fire Severity And Vulnerability Of Peatlands To Early Season Wildland Fire, Laura Bourgeau-Chavez, Sarah L. Grelik, Michael Billmire, Liza K. Jenkins, Eric S. Kasischke, Merritt R. Turetsky

Michigan Tech Publications

Globally peatlands store large amounts of carbon belowground with 80% distributed in boreal regions of the northern hemisphere. Climate warming and drying of the boreal region has been documented as affecting fire regimes, with increased fire frequency, severity and extent. While much research is dedicated to assessing changes in boreal uplands, few research efforts are focused on the vulnerability of boreal peatlands to wildfire. In this case study, an integration of field data collection, land cover mapping of peatland types and Landsat-based fire severity mapping was conducted for four early season (May to mid-June) wildfires where peatlands are abundant in …

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Regional Scale Dryland Vegetation Classification With An Integrated Lidar-Hyperspectral Approach, Hamid Dashti, Andrew Poley, Nancy Glenn, Nayani Ilangakoon, Lucas Spaete, Dar Roberts, Et. Al. Sep 2019

Regional Scale Dryland Vegetation Classification With An Integrated Lidar-Hyperspectral Approach, Hamid Dashti, Andrew Poley, Nancy Glenn, Nayani Ilangakoon, Lucas Spaete, Dar Roberts, Et. Al.

Michigan Tech Publications

The sparse canopy cover and large contribution of bright background soil, along with the heterogeneous vegetation types in close proximity, are common challenges for mapping dryland vegetation with remote sensing. Consequently, the results of a single classification algorithm or one type of sensor to characterize dryland vegetation typically show low accuracy and lack robustness. In our study, we improved classification accuracy in a semi-arid ecosystem based on the use of vegetation optical (hyperspectral) and structural (lidar) information combined with the environmental characteristics of the landscape. To accomplish this goal, we used both spectral angle mapper (SAM) and multiple endmember spectral …

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Understanding Cumulative Hazards In A Rustbelt City: Integrating Gis, Archaeology, And Spatial History, Daniel Trepal, Don Lafreniere Jul 2019

Understanding Cumulative Hazards In A Rustbelt City: Integrating Gis, Archaeology, And Spatial History, Daniel Trepal, Don Lafreniere

Michigan Tech Publications

We combine the Historical Spatial Data Infrastructure (HSDI) concept developed within spatial history with elements of archaeological predictive modeling to demonstrate a novel GIS-based landscape model for identifying the persistence of historically-generated industrial hazards in postindustrial cities. This historical big data approach draws on over a century of both historical and modern spatial big data to project the presence of specific persistent historical hazards across a city. This research improves on previous attempts to understand the origins and persistence of historical pollution hazards, and our final model augments traditional archaeological approaches to site prospection and analysis. This study also demonstrates …

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Evaluating Visible Derivative Spectroscopy By Varimax-Rotated, Principal Component Analysis Of Aerial Hyperspectral Images From The Western Basin Of Lake Erie, Joseph D. Ortiz, Dulci M. Avouris, Stephan J. Schiller, Jeffrey C. Luvall, John D. Lekki, Roger P. Tokars, Robert C. Anderson, Robert Shuchman, Michael Sayers, Richard Becker Jun 2019

Evaluating Visible Derivative Spectroscopy By Varimax-Rotated, Principal Component Analysis Of Aerial Hyperspectral Images From The Western Basin Of Lake Erie, Joseph D. Ortiz, Dulci M. Avouris, Stephan J. Schiller, Jeffrey C. Luvall, John D. Lekki, Roger P. Tokars, Robert C. Anderson, Robert Shuchman, Michael Sayers, Richard Becker

Michigan Tech Publications

The Kent State University (KSU) spectral decomposition method provides information about the spectral signals present in multispectral and hyperspectral images. Pre-processing steps that enhance signal to noise ratio (SNR) by 7.37–19.04 times, enables extraction of the environmental signals captured by the National Aeronautics and Space Administration (NASA) Glenn Research Center's, second generation, Hyperspectral imager (HSI2) into multiple, independent components. We have accomplished this by pre-processing of Level 1 HSI2 data to remove stripes from the scene, followed by a combination of spectral and spatial smoothing to further increase the SNR and remove non-Lambertian features, such as waves. On average, …

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Real Time Habs Mapping Using Nasa Glenn Hyperspectral Imager, Reid W. Sawtell, Robert Anderson, Roger Tokars, John D. Lekki, Robert Shuchman, Karl Bosse, Michael Sayers Jun 2019

Real Time Habs Mapping Using Nasa Glenn Hyperspectral Imager, Reid W. Sawtell, Robert Anderson, Roger Tokars, John D. Lekki, Robert Shuchman, Karl Bosse, Michael Sayers

Michigan Tech Publications

The hyperspectral imaging system (HSI) developed by the NASA Glenn Research Center was used from 2015 to 2017 to collect high spatial resolution data over Lake Erie and the Ohio River. Paired with a vicarious correction approach implemented by the Michigan Tech Research Institute, radiance data collected by the HSI system can be converted to high quality reflectance data which can be used to generate near-real time (within 24 h) products for the monitoring of harmful algal blooms using existing algorithms. The vicarious correction method relies on imaging a spectrally constant target to normalize HSI data for atmospheric and instrument …

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Spatial And Temporal Variability Of Inherent And Apparent Optical Properties In Western Lake Erie: Implications For Water Quality Remote Sensing, Michael Sayers, Karl Bosse, Robert Shuchman, Steven A. Ruberg, Gary L. Fahnenstiel, George Leshkevich, Et Al. Jun 2019

Spatial And Temporal Variability Of Inherent And Apparent Optical Properties In Western Lake Erie: Implications For Water Quality Remote Sensing, Michael Sayers, Karl Bosse, Robert Shuchman, Steven A. Ruberg, Gary L. Fahnenstiel, George Leshkevich, Et Al.

Michigan Tech Publications

Lake Erie has experienced dramatic changes in water quality over the past several decades requiring extensive monitoring to assess effectiveness of adaptive management strategies. Remote sensing offers a unique potential to provide synoptic monitoring at daily time scales complementing in-situ sampling activities occurring in Lake Erie. Bio-optical remote sensing algorithms require knowledge about the inherent optical properties (IOPs) of the water for parameterization to produce robust water quality products. This study reports new IOP and apparent optical property (AOP) datasets for western Lake Erie that encapsulate the May–October period for 2015 and 2016 at weekly sampling intervals. Previously reported IOP …

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Satellite Monitoring Of Harmful Algal Blooms In The Western Basin Of Lake Erie: A 20-Year Time-Series, Michael Sayers, Amanda Grimm, Robert Shuchman, Karl Bosse, Gary L. Fahnenstiel, Steven A. Ruberg, George A. Leshkevich Jun 2019

Satellite Monitoring Of Harmful Algal Blooms In The Western Basin Of Lake Erie: A 20-Year Time-Series, Michael Sayers, Amanda Grimm, Robert Shuchman, Karl Bosse, Gary L. Fahnenstiel, Steven A. Ruberg, George A. Leshkevich

Michigan Tech Publications

Blooms of harmful cyanobacteria (cyanoHABs) have occurred on an annual basis in western Lake Erie for more than a decade. Previously, we developed and validated an algorithm to map the extent of the submerged and surface scum components of cyanoHABs using MODIS ocean-color satellite data. The algorithm maps submerged cyanoHABs by identifying high chlorophyll concentrations (>18 mg/m3) combined with water temperature >20 °C, while cyanoHABs surface scums are mapped using near-infrared reflectance values. Here, we adapted this algorithm for the SeaWiFS sensor to map the annual areal extents of cyanoHABs in the Western Basin of Lake Erie for the …

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Determining Remote Sensing Spatial Resolution Requirements For The Monitoring Of Harmful Algal Blooms In The Great Lakes, John Lekki, Eric Deutsch, Michael Sayers, Karl Bosse, Robert Anderson, Roger Tokars, Reid W. Sawtell Jun 2019

Determining Remote Sensing Spatial Resolution Requirements For The Monitoring Of Harmful Algal Blooms In The Great Lakes, John Lekki, Eric Deutsch, Michael Sayers, Karl Bosse, Robert Anderson, Roger Tokars, Reid W. Sawtell

Michigan Tech Publications

Harmful algal blooms (HABs) have become a major health and environmental concern in the Great Lakes. In 2014, severe HABs prompted the State of Ohio to request NASA Glenn Research Center (GRC) to assist with monitoring algal blooms in Lake Erie. The most notable species of HAB is Microcystis aeruginosa, a hepatotoxin producing cyanobacteria that is responsible for liver complications for humans and other fauna that come in contact with these blooms. NASA GRC conducts semiweekly flights in order to gather up-to-date imagery regarding the blooms' spatial extents and concentrations. Airborne hyperspectral imagery is collected using two hyperspectral imagers, HSI-2 …

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Spatial-Temporal Variability Of In Situ Cyanobacteria Vertical Structure In Western Lake Erie: Implications For Remote Sensing Observations, Karl Bosse, Michael Sayers, Robert Shuchman, Gary L. Fahnenstiel, Steven A. Ruberg, David L. Fanslow, Dack G. Stuart, Thomas H. Johengen, Ashley M. Burtner Feb 2019

Spatial-Temporal Variability Of In Situ Cyanobacteria Vertical Structure In Western Lake Erie: Implications For Remote Sensing Observations, Karl Bosse, Michael Sayers, Robert Shuchman, Gary L. Fahnenstiel, Steven A. Ruberg, David L. Fanslow, Dack G. Stuart, Thomas H. Johengen, Ashley M. Burtner

Michigan Tech Publications

Remote sensing has provided expanded temporal and spatial range to the study of harmful algal blooms (cyanoHABs) in western Lake Erie, allowing for a greater understanding of bloom dynamics than is possible through in situ sampling. However, satellites are limited in their ability to specifically target cyanobacteria and can only observe the water within the first optical depth. This limits the ability of remote sensing to make conclusions about full water column cyanoHAB biomass if cyanobacteria are vertically stratified. FluoroProbe data were collected at nine stations across western Lake Erie in 2015 and 2016 and analyzed to characterize spatio-temporal variability …

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Semi-Automated Surface Water Detection With Synthetic Aperture Radar Data: A Wetland Case Study, Amir Behnamian, Sarah Banks, Lori White, Brian Brisco, Koreen Millard, Jon Pasher, Zhaohua Chen, Jason Duffe, Laura Bourgeau-Chavez, Michael Battaglia Nov 2017

Semi-Automated Surface Water Detection With Synthetic Aperture Radar Data: A Wetland Case Study, Amir Behnamian, Sarah Banks, Lori White, Brian Brisco, Koreen Millard, Jon Pasher, Zhaohua Chen, Jason Duffe, Laura Bourgeau-Chavez, Michael Battaglia

Michigan Tech Publications

In this study, a new method is proposed for semi-automated surface water detection using synthetic aperture radar data via a combination of radiometric thresholding and image segmentation based on the simple linear iterative clustering superpixel algorithm. Consistent intensity thresholds are selected by assessing the statistical distribution of backscatter values applied to the mean of each superpixel. Higher-order texture measures, such as variance, are used to improve accuracy by removing false positives via an additional thresholding process used to identify the boundaries of water bodies. Results applied to quad-polarized RADARSAT-2 data show that the threshold value for the variance texture measure …

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Identification Of Woodland Vernal Pools With Seasonal Change Palsar Data For Habitat Conservation, Laura Bourgeau-Chavez, Yu Man Lee, Michael Battaglia, Sarah L. Endres, Zachary Laubach, Kirk Scarbrough Jun 2016

Identification Of Woodland Vernal Pools With Seasonal Change Palsar Data For Habitat Conservation, Laura Bourgeau-Chavez, Yu Man Lee, Michael Battaglia, Sarah L. Endres, Zachary Laubach, Kirk Scarbrough

Michigan Tech Publications

Woodland vernal pools are important, small, cryptic, ephemeral wetland ecosystems that are vulnerable to a changing climate and anthropogenic influences. To conserve woodland vernal pools for the state of Michigan USA, vernal pool detection and mapping methods were sought that would be efficient, cost-effective, repeatable and accurate. Satellite-based L-band radar data from the high (10 m) resolution Japanese ALOS PALSAR sensor were evaluated for suitability in vernal pool detection beneath forest canopies. In a two phase study, potential vernal pool (PVP) detection was first assessed with unsupervised PALSAR (LHH) two season change detection (spring when flooded—summer when dry) and validated …

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