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of 9
pro vyhledávání: '"Kurtis J. Nelson"'
Autor:
Birgit Peterson, Kurtis J. Nelson
Publikováno v:
Remote Sensing, Vol 6, Iss 12, Pp 12409-12426 (2014)
Vegetation structure, including forest canopy height, is an important input variable to fire behavior modeling systems for simulating wildfire behavior. As such, forest canopy height is one of a nationwide suite of products generated by the LANDFIRE
Externí odkaz:
https://doaj.org/article/fe26c35b8ebb485c9e46ca7dd8dbd911
Autor:
Yingxin Gu, Bruce K. Wylie, Stephen P. Boyte, Joshua Picotte, Daniel M. Howard, Kelcy Smith, Kurtis J. Nelson
Publikováno v:
Remote Sensing, Vol 8, Iss 11, p 943 (2016)
Regression tree models have been widely used for remote sensing-based ecosystem mapping. Improper use of the sample data (model training and testing data) may cause overfitting and underfitting effects in the model. The goal of this study is to devel
Externí odkaz:
https://doaj.org/article/3417c97c6d5f4fda83a262c5cefa681d
Autor:
Nate Benson, Krishna P. Bhattarai, Joshua J. Picotte, Daniel M. Howard, Brad Quayle, Kurtis J. Nelson, Justin Epting, Jennifer Lecker
Publikováno v:
Fire Ecology. 16
Background The Monitoring Trends in Burn Severity (MTBS) program has been providing the fire science community with large fire perimeter and burn severity data for the past 14 years. As of October 2019, 22 969 fires have been mapped by the MTBS progr
Autor:
Kurtis J. Nelson, Daniel R. Steinwand
Publikováno v:
Photogrammetric Engineering & Remote Sensing. 81:573-586
Annual disturbance maps are produced by the LANDFIRE program across the conterminous United States (CONUS). Existing LANDFIRE disturbance data from 1999 to 2010 are available and current efforts will produce disturbance data through 2012. A tiling an
Autor:
Kurtis J. Nelson, Yingxin Gu, Stephen P. Boyte, Bruce K. Wylie, Joshua J. Picotte, Daniel M. Howard, Kelcy Smith
Publikováno v:
Remote Sensing; Volume 8; Issue 11; Pages: 943
Remote Sensing, Vol 8, Iss 11, p 943 (2016)
Remote Sensing, Vol 8, Iss 11, p 943 (2016)
Regression tree models have been widely used for remote sensing-based ecosystem mapping. Improper use of the sample data (model training and testing data) may cause overfitting and underfitting effects in the model. The goal of this study is to devel
Publikováno v:
Fire Ecology. 9:80-101
The LANDFIRE Program provides comprehensive vegetation and fuel datasets for the entire United States. As with many large-scale ecological datasets, vegetation and landscape conditions must be updated periodically to account for disturbances, growth,
Publikováno v:
Photogrammetric Engineering & Remote Sensing. 79:175-183
Comprehensive canopy structure and fuel data are critical for understanding and modeling wildland fire. The LANDFIRE project produces such data nationwide based on a collection of field observations, Landsat imagery, and other geospatial data. Where
Publikováno v:
Open-File Report.
Autor:
Kurtis J. Nelson, Birgit Peterson
Publikováno v:
Fact Sheet.
The Wildfire Sciences Team at the U.S. Geological Survey’s Earth Resources Observation and Science Center produces vegetation type, vegetation structure, and fuel products for the United States, primarily through the Landscape Fire and Resource Man