Britt W Smith
Britt Smith is a Geographer with the Western Geographic Science Center and is located in Tucson, AZ.
Britt Smith researches land use and land cover change and is part of the Patterns in the Landscape - Analyses of Cause and Effect (PLACE) team. His focus has traditionally be on agricultural landscapes and is excited to branch into urban and other managed landscapes. His work seeks to inform decision makers, resource managers, and stakeholders by leveraging large datasets with cloud computing techniques
Education and Certifications
Ph.D. - 2018 - Natural Resources Management - Texas Tech University
M.S. - 2014 - Natural Resource Ecology and Management - Oklahoma State University
B.S. - 2009 - Environmental Science - University of Missouri - Kansas City
Science and Products
Patterns in the Landscape – Analyses of Cause and Effect
Understanding the rates and causes of land-use/land-cover (LULC) change helps answer questions about what, where, how, and why the Earth’s surface is changing. Land-surface change results from human activities or natural processes like floods, droughts, and wildfires, and many of these change processes are observable in satellite imagery. The growing historical catalog of satellite images allows...
Data on winter surface water dynamics in California’s Central Valley using satellite remote sensing Data on winter surface water dynamics in California’s Central Valley using satellite remote sensing
These data support the following publication: "Assessing causes and consequences of winter surface water dynamics in California’s Central Valley using satellite remote sensing". The file contains information associated with surface water inundation, antecedent soil moisture, and atmospheric river storm characteristics for 2003-2023 in the three HUC-4 hydrologic sub-basins that make up...
MODIS Fire Radiative Power data compiled from active fires in Alaska, 2003-2022 MODIS Fire Radiative Power data compiled from active fires in Alaska, 2003-2022
This data release supports the publication: "Linking Fire Radiative Power to land cover, fire history, and environmental setting in Alaska, 2003 - 2022". The *.csv file contains data associated with fire radiative power (FRP) observations derived from 1-km MODIS data over Alaska from 2003 to 2022. The file allows users to replicate the statistical analysis of FRP values with vegetation...
Classification of crop types in central California from 2005 - 2020 Classification of crop types in central California from 2005 - 2020
This dataset is support materials for the publication "Crop type classification, trends, and patterns of central California agricultural fields from 2005 – 2020". This data release is comprised of two child datasets. The first dataset, 'Labeled_CropType_Points', is a shapefile that consists of randomly selected point locations in which crop types were verified using high resolution...
Wetlands in the state of Arizona Wetlands in the state of Arizona
We created a single map of surface water presence by intersecting water classes from available land cover products (National Wetland Inventory, Gap Analysis Program, National Land Cover Database, and Dynamic Surface Water Extent) across the U.S. state of Arizona. We derived classified samples for four wetland classes from the harmonized map: water, herbaceous wetlands, wooded wetlands...
County-level maps of cropland surface water inundation measured from Landsat and MODIS County-level maps of cropland surface water inundation measured from Landsat and MODIS
This dataset represents a summary of potential cropland inundation for the state of California applying high-frequency surface water map composites derived from two satellite remote sensing platforms (Landsat and Moderate Resolution Imaging Spectroradiometer [MODIS]) with high-quality cropland maps generated by the California Department of Water Resources (DWR). Using Google Earth Engine...
Assessing causes and consequences of winter surface water dynamics in California’s Central Valley using satellite remote sensing Assessing causes and consequences of winter surface water dynamics in California’s Central Valley using satellite remote sensing
California's Central Valley is increasingly vulnerable to winter floods. A comprehensive spatial baseline of flood extents is critical for inundation analyses that can enhance future flood predictions, but cloud cover has prevented the regular observation of surface water extents with optical satellite imagery. In this study, we leveraged the daily resolution of Moderate Resolution...
Authors
Christine M. Albano, Christopher E. Soulard, Blake A. Minor, Jessica J. Walker, Britt Windsor Smith, Eric K. Waller, Michael D. Bartles, Tom Corringham, Anthony T. O'Geen, Melissa M. Rohde, Anne Wein
Linking fire radiative power to land cover, fire history, and environmental setting in Alaska, 2003–2022 Linking fire radiative power to land cover, fire history, and environmental setting in Alaska, 2003–2022
BackgroundFire radiative power (FRP) shows promise as a diagnostic and predictive indicator of fire behavior and post-fire effects in Alaska, USA.AimsTo investigate relationships between FRP, vegetation functional groups, and environmental settings in Alaska (2003–2022) under various fire history conditions.MethodsWe tested for distinctness of MODIS FRP distributions associated with...
Authors
Jessica J. Walker, Rachel A. Loehman, Britt Windsor Smith, Christopher E. Soulard
The feasibility of using national-scale datasets for classifying wetlands in Arizona with machine learning The feasibility of using national-scale datasets for classifying wetlands in Arizona with machine learning
The advent of machine learning techniques has led to a proliferation of landscape classification products. These approaches can fill gaps in wetland inventories across the United States (U.S.) provided that large reference datasets are available to develop accurate models. In this study, we tested the feasibility of expediting the classification process by sourcing requisite training and...
Authors
Christopher E. Soulard, Jessica J. Walker, Britt Windsor Smith, Jason R. Kreitler
Crop type classification, trends, and patterns of central California agricultural fields from 2005 to 2020 Crop type classification, trends, and patterns of central California agricultural fields from 2005 to 2020
California produces many key agricultural products in the United States. Current geospatial agricultural datasets are limited in mapping accuracy, spatial context, or observation period. This study uses machine learning and high-resolution imagery to produce a time series of crop maps to assess crop type trends and patterns across central California from 2005 to 2020. National...
Authors
Britt Windsor Smith, Christopher E. Soulard, Jessica J. Walker
Using Landsat and MODIS satellite collections to examine extent, timing, and potential impacts of surface water inundation in California croplands☆ Using Landsat and MODIS satellite collections to examine extent, timing, and potential impacts of surface water inundation in California croplands☆
The state of California, United States of America produces many crop products that are both utilized domestically and exported throughout the world. With nearly 39,000 km2 of croplands, monitoring unintentional and intentional surface water inundation is important for water resource management and flood hazard readiness. We examine inundation dynamics in California croplands from 2003 to...
Authors
Britt Windsor Smith, Christopher E. Soulard, Jessica J. Walker, Anne Wein
DSWEmod - The production of high-frequency surface water map composites from daily MODIS images DSWEmod - The production of high-frequency surface water map composites from daily MODIS images
Optical satellite imagery is commonly used for monitoring surface water dynamics, but clouds and cloud shadows present challenges in assembling complete water time series. To test whether the daily revisit rate of Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery can reduce cloud obstruction and improve high-frequency surface water mapping, we compared map results...
Authors
Christopher E. Soulard, Eric Waller, Jessica J. Walker, Roy Petrakis, Britt Windsor Smith
Science and Products
Patterns in the Landscape – Analyses of Cause and Effect
Understanding the rates and causes of land-use/land-cover (LULC) change helps answer questions about what, where, how, and why the Earth’s surface is changing. Land-surface change results from human activities or natural processes like floods, droughts, and wildfires, and many of these change processes are observable in satellite imagery. The growing historical catalog of satellite images allows...
Data on winter surface water dynamics in California’s Central Valley using satellite remote sensing Data on winter surface water dynamics in California’s Central Valley using satellite remote sensing
These data support the following publication: "Assessing causes and consequences of winter surface water dynamics in California’s Central Valley using satellite remote sensing". The file contains information associated with surface water inundation, antecedent soil moisture, and atmospheric river storm characteristics for 2003-2023 in the three HUC-4 hydrologic sub-basins that make up...
MODIS Fire Radiative Power data compiled from active fires in Alaska, 2003-2022 MODIS Fire Radiative Power data compiled from active fires in Alaska, 2003-2022
This data release supports the publication: "Linking Fire Radiative Power to land cover, fire history, and environmental setting in Alaska, 2003 - 2022". The *.csv file contains data associated with fire radiative power (FRP) observations derived from 1-km MODIS data over Alaska from 2003 to 2022. The file allows users to replicate the statistical analysis of FRP values with vegetation...
Classification of crop types in central California from 2005 - 2020 Classification of crop types in central California from 2005 - 2020
This dataset is support materials for the publication "Crop type classification, trends, and patterns of central California agricultural fields from 2005 – 2020". This data release is comprised of two child datasets. The first dataset, 'Labeled_CropType_Points', is a shapefile that consists of randomly selected point locations in which crop types were verified using high resolution...
Wetlands in the state of Arizona Wetlands in the state of Arizona
We created a single map of surface water presence by intersecting water classes from available land cover products (National Wetland Inventory, Gap Analysis Program, National Land Cover Database, and Dynamic Surface Water Extent) across the U.S. state of Arizona. We derived classified samples for four wetland classes from the harmonized map: water, herbaceous wetlands, wooded wetlands...
County-level maps of cropland surface water inundation measured from Landsat and MODIS County-level maps of cropland surface water inundation measured from Landsat and MODIS
This dataset represents a summary of potential cropland inundation for the state of California applying high-frequency surface water map composites derived from two satellite remote sensing platforms (Landsat and Moderate Resolution Imaging Spectroradiometer [MODIS]) with high-quality cropland maps generated by the California Department of Water Resources (DWR). Using Google Earth Engine...
Assessing causes and consequences of winter surface water dynamics in California’s Central Valley using satellite remote sensing Assessing causes and consequences of winter surface water dynamics in California’s Central Valley using satellite remote sensing
California's Central Valley is increasingly vulnerable to winter floods. A comprehensive spatial baseline of flood extents is critical for inundation analyses that can enhance future flood predictions, but cloud cover has prevented the regular observation of surface water extents with optical satellite imagery. In this study, we leveraged the daily resolution of Moderate Resolution...
Authors
Christine M. Albano, Christopher E. Soulard, Blake A. Minor, Jessica J. Walker, Britt Windsor Smith, Eric K. Waller, Michael D. Bartles, Tom Corringham, Anthony T. O'Geen, Melissa M. Rohde, Anne Wein
Linking fire radiative power to land cover, fire history, and environmental setting in Alaska, 2003–2022 Linking fire radiative power to land cover, fire history, and environmental setting in Alaska, 2003–2022
BackgroundFire radiative power (FRP) shows promise as a diagnostic and predictive indicator of fire behavior and post-fire effects in Alaska, USA.AimsTo investigate relationships between FRP, vegetation functional groups, and environmental settings in Alaska (2003–2022) under various fire history conditions.MethodsWe tested for distinctness of MODIS FRP distributions associated with...
Authors
Jessica J. Walker, Rachel A. Loehman, Britt Windsor Smith, Christopher E. Soulard
The feasibility of using national-scale datasets for classifying wetlands in Arizona with machine learning The feasibility of using national-scale datasets for classifying wetlands in Arizona with machine learning
The advent of machine learning techniques has led to a proliferation of landscape classification products. These approaches can fill gaps in wetland inventories across the United States (U.S.) provided that large reference datasets are available to develop accurate models. In this study, we tested the feasibility of expediting the classification process by sourcing requisite training and...
Authors
Christopher E. Soulard, Jessica J. Walker, Britt Windsor Smith, Jason R. Kreitler
Crop type classification, trends, and patterns of central California agricultural fields from 2005 to 2020 Crop type classification, trends, and patterns of central California agricultural fields from 2005 to 2020
California produces many key agricultural products in the United States. Current geospatial agricultural datasets are limited in mapping accuracy, spatial context, or observation period. This study uses machine learning and high-resolution imagery to produce a time series of crop maps to assess crop type trends and patterns across central California from 2005 to 2020. National...
Authors
Britt Windsor Smith, Christopher E. Soulard, Jessica J. Walker
Using Landsat and MODIS satellite collections to examine extent, timing, and potential impacts of surface water inundation in California croplands☆ Using Landsat and MODIS satellite collections to examine extent, timing, and potential impacts of surface water inundation in California croplands☆
The state of California, United States of America produces many crop products that are both utilized domestically and exported throughout the world. With nearly 39,000 km2 of croplands, monitoring unintentional and intentional surface water inundation is important for water resource management and flood hazard readiness. We examine inundation dynamics in California croplands from 2003 to...
Authors
Britt Windsor Smith, Christopher E. Soulard, Jessica J. Walker, Anne Wein
DSWEmod - The production of high-frequency surface water map composites from daily MODIS images DSWEmod - The production of high-frequency surface water map composites from daily MODIS images
Optical satellite imagery is commonly used for monitoring surface water dynamics, but clouds and cloud shadows present challenges in assembling complete water time series. To test whether the daily revisit rate of Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery can reduce cloud obstruction and improve high-frequency surface water mapping, we compared map results...
Authors
Christopher E. Soulard, Eric Waller, Jessica J. Walker, Roy Petrakis, Britt Windsor Smith