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Social and Behavioral Sciences Commons

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Geographic Information Sciences

Michigan Technological University

Michigan Tech Publications

2020

Remote sensing

Articles 1 - 2 of 2

Full-Text Articles in Social and Behavioral Sciences

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 …


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 …