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Full-Text Articles in Spatial Science
Exploring Spatial Patterns Of Virginia Tornadoes Using Kernel Density And Space-Time Cube Analysis (1960-2019), Michael J. Allen, Thomas R. Allen, Christopher Davis, George Mcleod, Wolfgang Kainz (Ed.), Dean Kyne (Ed.)
Exploring Spatial Patterns Of Virginia Tornadoes Using Kernel Density And Space-Time Cube Analysis (1960-2019), Michael J. Allen, Thomas R. Allen, Christopher Davis, George Mcleod, Wolfgang Kainz (Ed.), Dean Kyne (Ed.)
Political Science & Geography Faculty Publications
This study evaluates the spatial-temporal patterns in Virginia tornadoes using the National Weather Service Storm Prediction Center’s Severe Weather GIS (SVRGIS) database. In addition to descriptive statistics, the analysis employs Kernel Density Estimation for spatial pattern analysis and space-time cubes to visualize the spatiotemporal frequency of tornadoes and potential trends. Most of the 726 tornadoes between 1960–2019 occurred in Eastern Virginia, along the Piedmont and Coastal Plain. Consistent with other literature, both the number of tornadoes and the tornado days have increased in Virginia. While 80% of the tornadoes occurred during the warm season, tornadoes did occur during each month …
Field-Scale Soil Moisture Bridges The Spatial-Scale Gap Between Drought Monitoring And Agricultural Yields, Noemi Vergopolan, Sitian Xiong, Lyndon Estes, Niko Wanders, Nathaniel W. Chaney, Eric F. Wood, Megan Konar, Kelly Caylor, Hylke E. Beck, Nicolas Gatti, Tom Evans, Justin Sheffield
Field-Scale Soil Moisture Bridges The Spatial-Scale Gap Between Drought Monitoring And Agricultural Yields, Noemi Vergopolan, Sitian Xiong, Lyndon Estes, Niko Wanders, Nathaniel W. Chaney, Eric F. Wood, Megan Konar, Kelly Caylor, Hylke E. Beck, Nicolas Gatti, Tom Evans, Justin Sheffield
Geography
Soil moisture is highly variable in space and time, and deficits (i.e., droughts) play an important role in modulating crop yields. Limited hydroclimate and yield data, however, hamper drought impact monitoring and assessment at the farm field scale. This study demonstrates the potential of using field-scale soil moisture simulations to support highresolution agricultural yield prediction and drought monitoring at the smallholder farm field scale. We present a multiscale modeling approach that combines HydroBlocks a physically based hyper-resolution land surface model (LSM) with machine learning. We used HydroBlocks to simulate root zone soil moisture and soil temperature in Zambia at 3 …