Jessica J Walker
Jessica started with the USGS as a Mendenhall Postdoctoral Researcher in 2014.
Jessica's broad research interests center on the analysis of landscape change using remote sensing data. Past projects have included tracking the vegetative trajectories of areas recovering from fire events, both in the semi-arid, high-elevation forests of Arizona and the boreal forests of Alaska. Additional recent work includes examining surface inundation patterns via Landsat and MODIS imagery as part of the PLACE project (Patterns in the Landscape - Analyses of Cause and Effect).
Education and Certifications
2012 - Ph.D. Geospatial and Environmental Analysis, Virginia Tech
2000 - M.A. Geography, University of Arizona, Tucson
1991 - B.A. Applied Math, Williams College
Science and Products
Investigation of Lidar Data Processing and Analysis in the Cloud
Lower technical and financial barriers have led to a proliferation of lidar point-cloud datasets acquired to support diverse USGS projects. The objective of this effort was to implement an open-source, cloud-based solution through USGS Cloud Hosting Solutions (CHS) that would address the needs of the growing USGS lidar community. We proposed to allow users to upload point-cloud datasets...
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...
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
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
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...
National Surface Water Maps using Daily MODIS Satellite Data for the Conterminous United States, 2003-2019
Members from the U.S. Geological Survey (USGS) Patterns in the Landscape - Analyses of Cause and Effect (PLACE) team are releasing monthly surface water maps for the conterminous United States (U.S.) from 2003 through 2019 as 250-meter resolution geoTIFF files. The maps were produced using the Dynamic Surface Water Extent (DSWE) algorithm applied to daily Moderate Resolution Imaging...
DSWEmod surface water map composites generated from daily MODIS images - California
USGS researchers with the Patterns in the Landscape ? Analyses of Cause and Effect (PLACE) project are releasing a collection of high-frequency surface water map composites derived from daily Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. Using Google Earth Engine, the team developed customized image processing steps and adapted the Dynamic Surface Water Extent (DSWE) to...
Data release associated with the journal article "Solar and sensor geometry, not vegetation response, drive satellite NDVI phenology in widespread ecosystems of the western United States"
This dataset supports the following publication: "Solar and sensor geometry, not vegetation response, drive satellite NDVI phenology in widespread ecosystems of the western United States" (DOI:10.1016/j.rse.2020.112013). The data release allows users to replicate, test, or further explore results. The dataset consists of 4 separate items based on the analysis approach used in the...
Implementation of a Surface Water Extent Model using Cloud-Based Remote Sensing - Code and Maps
This data release comprises the raster data files and code necessary to perform all analyses presented in the associated publication. The 16 TIF raster data files are classified surface water maps created using the Dynamic Surface Water Extent (DSWE) model implemented in Google Earth Engine using published technical documents. The 16 tiles cover the country of Cambodia, a flood-prone...
Phenology pattern data indicating recovery trajectories of ponderosa pine forests after high-severity fires
This tabular, machine-readable CSV file contains annual phenometrics at locations in ponderosa pine ecosystems across Arizona and New Mexico that experienced stand-clearing, high-severity fire. The locations represent areas of vegetative recovery towards pre-fire (coniferous/pine) vegetation communities or towards novel grassland, shrubland, or deciduous replacements. Each sampled area...
Datasets for analyzing stream gage discharge and Landsat imagery integration in the greater Central Valley, California from 1984 to 2015
This data release comprises the data files and code necessary to perform all analyses presented in the associated publication. The *.csv data files are aggregations of water extent on the basis of the European Commission's Joint Research Centre (JRC) Monthly Water History database (v1.0) and the Dynamic Surface Water Extent (DSWE) algorithm. The shapefile dataset contains the study area...
Data - Forest harvest patterns on private lands in the Cascade Mountains, Washington, USA
Forests in Washington State generate substantial economic revenue from commercial timber harvesting on private lands. To investigate the rates, causes, and spatial and temporal patterns of forest harvest on private tracts throughout the central Cascade Mountain area, we relied on a new generation of annual land-use/land-cover (LULC) products created from the application of the Continuous...
Filter Total Items: 16
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
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☆
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
Analysis of surface water trends for the conterminous United States using MODIS satellite data, 2003–2019
Satellite imagery is commonly used to map surface water extents over time, but many approaches yield discontinuous records resulting from cloud obstruction or image archive gaps. We applied the Dynamic Surface Water Extent (DSWE) model to downscaled (250-m) daily Moderate Resolution Imaging Spectroradiometer (MODIS) data in Google Earth Engine to generate monthly surface water maps for...
Authors
Roy Petrakis, Christopher E. Soulard, Eric K. Waller, Jessica J. Walker
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
Tamm review: Postfire landscape management in frequent-fire conifer forests of the southwestern United States
The increasing incidence of wildfires across the southwestern United States (US) is altering the contemporary forest management template within historically frequent-fire conifer forests. An increasing fraction of southwestern conifer forests have recently burned, and many of these burned landscapes contain complex mosaics of surviving forest and severely burned patches without surviving...
Authors
Jens T. Stevens, Collin Haffey, Jonathan D. Coop, Paula J. Fornwalt, Larissa Yocom, Craig D. Allen, Anne Bradley, Owen T. Burney, Dennis Carril, Marin E. Chambers, Theresa B. Chapman, Sandra L. Haire, Matthew D. Hurteau, José M. Iniguez, Ellis Margolis, Christopher Marks, Laura A. E. Marshall, Kyle C. Rodman, Camille S. Stevens-Rumann, Andrea E. Thode, Jessica J. Walker
Solar and sensor geometry, not vegetation response, drive satellite NDVI phenology in widespread ecosystems of the western United States
Satellite-derived phenology metrics are valuable tools for understanding broad-scale patterns and changes in vegetated landscapes over time. However, the extraction and interpretation of phenology in ecosystems with subtle growth dynamics can be challenging. US National Park Service monitoring of evergreen pinyon-juniper ecosystems in the western US revealed an unexpected winter-peaking...
Authors
Jodi R. Norris, Jessica J. Walker
Community for data integration 2018 funded project report
The U.S. Geological Survey Community for Data Integration annually funds small projects focusing on data integration for interdisciplinary research, innovative data management, and demonstration of new technologies. This report provides a summary of the 10 projects funded in fiscal year 2018, outlining their goals, activities, and accomplishments.
Authors
Leslie Hsu, Caitlin M. Andrews, John B. Bradford, Daniel D. Buscombe, Katherine J. Chase, Wesley M. Daniel, Jeanne M. Jones, Pam Fuller, Benjamin B. Mirus, Matthew E. Neilson, Hans W. Vraga, Jessica J. Walker, Dennis H. Walworth, Jonathan Warrick, Jake Weltzin, Daniel J. Wieferich, Nathan J. Wood
Implementation of a surface water extent model in Cambodia using cloud-based remote sensing
Mapping surface water over time provides the spatially explicit information essential for hydroclimatic research focused on droughts and flooding. Hazard risk assessments and water management planning also rely on accurate, long-term measurements describing hydrologic fluctuations. Stream gages are a common measurement tool used to better understand flow and inundation dynamics, but gage...
Authors
Christopher E. Soulard, Jessica J. Walker, Roy E. Petrakis
Phenology patterns indicate recovery trajectories of ponderosa pine forests after high-severity fires
Post-fire recovery trajectories in ponderosa pine (Pinus ponderosa Laws.) forests of the US Southwest are increasingly shifting away from pre-burn vegetation communities. This study investigated whether phenological metrics derived from a multi-decade remotely sensed imagery time-series could differentiate among grass, evergreen shrub, deciduous, or conifer-dominated replacement pathways...
Authors
Jessica J. Walker, Christopher E. Soulard
Integrating stream gage data and Landsat imagery to complete time-series of surface water extents in Central Valley, California
Accurate monitoring of surface water location and extent is critical for the management of diverse water resource phenomena. The multi-decadal archive of Landsat satellite imagery is punctuated by missing data due to cloud cover during acquisition times, hindering the assembly of a continuous time series of inundation dynamics. This study investigated whether streamflow volume...
Authors
Jessica J. Walker, Christopher E. Soulard, Roy E. Petrakis
Differential changes in the onset of spring across US National Wildlife Refuges and North American migratory bird flyways
Warming temperatures associated with climate change can have indirect effects on migratory birds that rely on seasonally available food resources and habitats that vary across spatial and temporal scales. We used two heat-based indices of spring onset, the First Leaf Index (FLI) and the First Bloom Index (FBI), as proxies of habitat change for the period 1901 to 2012 at three spatial...
Authors
Eric K. Waller, Theresa M. Crimmins, Jessica J. Walker, Erin E. Posthumus, Jake Weltzin
DSWE_GEE v1.0.0
Code for implementation of the Dynamic Surface Water Extent algorithm in Google Earth Engine. Multiple scripts allow the creation of single-scene or composited Dynamic Surface Water Extent (DSWE) images from Landsat and MODIS data. All code is written for use in the JavaScript API.
Science and Products
Investigation of Lidar Data Processing and Analysis in the Cloud
Lower technical and financial barriers have led to a proliferation of lidar point-cloud datasets acquired to support diverse USGS projects. The objective of this effort was to implement an open-source, cloud-based solution through USGS Cloud Hosting Solutions (CHS) that would address the needs of the growing USGS lidar community. We proposed to allow users to upload point-cloud datasets...
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...
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
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
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...
National Surface Water Maps using Daily MODIS Satellite Data for the Conterminous United States, 2003-2019
Members from the U.S. Geological Survey (USGS) Patterns in the Landscape - Analyses of Cause and Effect (PLACE) team are releasing monthly surface water maps for the conterminous United States (U.S.) from 2003 through 2019 as 250-meter resolution geoTIFF files. The maps were produced using the Dynamic Surface Water Extent (DSWE) algorithm applied to daily Moderate Resolution Imaging...
DSWEmod surface water map composites generated from daily MODIS images - California
USGS researchers with the Patterns in the Landscape ? Analyses of Cause and Effect (PLACE) project are releasing a collection of high-frequency surface water map composites derived from daily Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. Using Google Earth Engine, the team developed customized image processing steps and adapted the Dynamic Surface Water Extent (DSWE) to...
Data release associated with the journal article "Solar and sensor geometry, not vegetation response, drive satellite NDVI phenology in widespread ecosystems of the western United States"
This dataset supports the following publication: "Solar and sensor geometry, not vegetation response, drive satellite NDVI phenology in widespread ecosystems of the western United States" (DOI:10.1016/j.rse.2020.112013). The data release allows users to replicate, test, or further explore results. The dataset consists of 4 separate items based on the analysis approach used in the...
Implementation of a Surface Water Extent Model using Cloud-Based Remote Sensing - Code and Maps
This data release comprises the raster data files and code necessary to perform all analyses presented in the associated publication. The 16 TIF raster data files are classified surface water maps created using the Dynamic Surface Water Extent (DSWE) model implemented in Google Earth Engine using published technical documents. The 16 tiles cover the country of Cambodia, a flood-prone...
Phenology pattern data indicating recovery trajectories of ponderosa pine forests after high-severity fires
This tabular, machine-readable CSV file contains annual phenometrics at locations in ponderosa pine ecosystems across Arizona and New Mexico that experienced stand-clearing, high-severity fire. The locations represent areas of vegetative recovery towards pre-fire (coniferous/pine) vegetation communities or towards novel grassland, shrubland, or deciduous replacements. Each sampled area...
Datasets for analyzing stream gage discharge and Landsat imagery integration in the greater Central Valley, California from 1984 to 2015
This data release comprises the data files and code necessary to perform all analyses presented in the associated publication. The *.csv data files are aggregations of water extent on the basis of the European Commission's Joint Research Centre (JRC) Monthly Water History database (v1.0) and the Dynamic Surface Water Extent (DSWE) algorithm. The shapefile dataset contains the study area...
Data - Forest harvest patterns on private lands in the Cascade Mountains, Washington, USA
Forests in Washington State generate substantial economic revenue from commercial timber harvesting on private lands. To investigate the rates, causes, and spatial and temporal patterns of forest harvest on private tracts throughout the central Cascade Mountain area, we relied on a new generation of annual land-use/land-cover (LULC) products created from the application of the Continuous...
Filter Total Items: 16
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
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☆
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
Analysis of surface water trends for the conterminous United States using MODIS satellite data, 2003–2019
Satellite imagery is commonly used to map surface water extents over time, but many approaches yield discontinuous records resulting from cloud obstruction or image archive gaps. We applied the Dynamic Surface Water Extent (DSWE) model to downscaled (250-m) daily Moderate Resolution Imaging Spectroradiometer (MODIS) data in Google Earth Engine to generate monthly surface water maps for...
Authors
Roy Petrakis, Christopher E. Soulard, Eric K. Waller, Jessica J. Walker
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
Tamm review: Postfire landscape management in frequent-fire conifer forests of the southwestern United States
The increasing incidence of wildfires across the southwestern United States (US) is altering the contemporary forest management template within historically frequent-fire conifer forests. An increasing fraction of southwestern conifer forests have recently burned, and many of these burned landscapes contain complex mosaics of surviving forest and severely burned patches without surviving...
Authors
Jens T. Stevens, Collin Haffey, Jonathan D. Coop, Paula J. Fornwalt, Larissa Yocom, Craig D. Allen, Anne Bradley, Owen T. Burney, Dennis Carril, Marin E. Chambers, Theresa B. Chapman, Sandra L. Haire, Matthew D. Hurteau, José M. Iniguez, Ellis Margolis, Christopher Marks, Laura A. E. Marshall, Kyle C. Rodman, Camille S. Stevens-Rumann, Andrea E. Thode, Jessica J. Walker
Solar and sensor geometry, not vegetation response, drive satellite NDVI phenology in widespread ecosystems of the western United States
Satellite-derived phenology metrics are valuable tools for understanding broad-scale patterns and changes in vegetated landscapes over time. However, the extraction and interpretation of phenology in ecosystems with subtle growth dynamics can be challenging. US National Park Service monitoring of evergreen pinyon-juniper ecosystems in the western US revealed an unexpected winter-peaking...
Authors
Jodi R. Norris, Jessica J. Walker
Community for data integration 2018 funded project report
The U.S. Geological Survey Community for Data Integration annually funds small projects focusing on data integration for interdisciplinary research, innovative data management, and demonstration of new technologies. This report provides a summary of the 10 projects funded in fiscal year 2018, outlining their goals, activities, and accomplishments.
Authors
Leslie Hsu, Caitlin M. Andrews, John B. Bradford, Daniel D. Buscombe, Katherine J. Chase, Wesley M. Daniel, Jeanne M. Jones, Pam Fuller, Benjamin B. Mirus, Matthew E. Neilson, Hans W. Vraga, Jessica J. Walker, Dennis H. Walworth, Jonathan Warrick, Jake Weltzin, Daniel J. Wieferich, Nathan J. Wood
Implementation of a surface water extent model in Cambodia using cloud-based remote sensing
Mapping surface water over time provides the spatially explicit information essential for hydroclimatic research focused on droughts and flooding. Hazard risk assessments and water management planning also rely on accurate, long-term measurements describing hydrologic fluctuations. Stream gages are a common measurement tool used to better understand flow and inundation dynamics, but gage...
Authors
Christopher E. Soulard, Jessica J. Walker, Roy E. Petrakis
Phenology patterns indicate recovery trajectories of ponderosa pine forests after high-severity fires
Post-fire recovery trajectories in ponderosa pine (Pinus ponderosa Laws.) forests of the US Southwest are increasingly shifting away from pre-burn vegetation communities. This study investigated whether phenological metrics derived from a multi-decade remotely sensed imagery time-series could differentiate among grass, evergreen shrub, deciduous, or conifer-dominated replacement pathways...
Authors
Jessica J. Walker, Christopher E. Soulard
Integrating stream gage data and Landsat imagery to complete time-series of surface water extents in Central Valley, California
Accurate monitoring of surface water location and extent is critical for the management of diverse water resource phenomena. The multi-decadal archive of Landsat satellite imagery is punctuated by missing data due to cloud cover during acquisition times, hindering the assembly of a continuous time series of inundation dynamics. This study investigated whether streamflow volume...
Authors
Jessica J. Walker, Christopher E. Soulard, Roy E. Petrakis
Differential changes in the onset of spring across US National Wildlife Refuges and North American migratory bird flyways
Warming temperatures associated with climate change can have indirect effects on migratory birds that rely on seasonally available food resources and habitats that vary across spatial and temporal scales. We used two heat-based indices of spring onset, the First Leaf Index (FLI) and the First Bloom Index (FBI), as proxies of habitat change for the period 1901 to 2012 at three spatial...
Authors
Eric K. Waller, Theresa M. Crimmins, Jessica J. Walker, Erin E. Posthumus, Jake Weltzin
DSWE_GEE v1.0.0
Code for implementation of the Dynamic Surface Water Extent algorithm in Google Earth Engine. Multiple scripts allow the creation of single-scene or composited Dynamic Surface Water Extent (DSWE) images from Landsat and MODIS data. All code is written for use in the JavaScript API.