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Social and Behavioral Sciences Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Keyword
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- Remote sensing (2)
- Boreal ecosystems (1)
- Change detection (1)
- Cyanobacteria (1)
- Cyanobacterial harmful algal blooms (1)
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- DEM (1)
- Duff (1)
- Fire severity (1)
- FluoroProbe (1)
- Harmful algal bloom (1)
- Hyperspectral remote sensingNASA Glenn HSI2Spectral decompositionUnsupervised classification (1)
- Lake Erie (1)
- Land cover (1)
- LiDAR (1)
- PACE (1)
- Peat (1)
- SAR (1)
- Surface water extent (1)
- Synthetic aperture radar (1)
- Vernal pools (1)
- Vertical structure (1)
- Wetlands (1)
Articles 1 - 5 of 5
Full-Text Articles in Social and Behavioral Sciences
Multi-Source Eo For Dynamic Wetland Mapping And Monitoring In The Great Lakes Basin, Michael Battaglia, Sarah Banks, Amir Behnamian, Laura Bourgeau-Chavez
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 …
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
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 …
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
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, …
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
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 …
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
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 …