Jesslyn Brown is a research geographer with the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center in Sioux Falls, South Dakota, USA. Jess's main interests involve improving our understanding of changes in terrestrial vegetation related to climate and other driving forces and advancing the use of remote sensing imagery in applications.
Jesslyn Brown is a research geographer with the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center in Sioux Falls, South Dakota, USA, where she has worked for 30 years. Since finishing her graduate program at the University of Nebraska—Lincoln in 1990, she has worked in applied geographic research utilizing remote sensing approaches. Jess’s main interests involve improving our understanding of changes in terrestrial vegetation related to climate and other driving forces and advancing the use of remotely sensed imagery for applications including drought early warning, tracking vegetation phenology (i.e., seasonal dynamics), and mapping land cover and land use. Jess was a member of the Global Land Cover Characteristics team that created the first map of global land cover at a 1-km resolution in the 1990s. From 2001 to 2017, she led multiple projects mainly focused on developing new monitoring tools to improve agricultural drought monitoring capabilities in the U.S. in a strong collaboration with the University of Nebraska-Lincoln’s National Drought Mitigation Center. During that time, she also led efforts to investigate recent land use change specifically focused on irrigated agriculture across the country. In 2017, she began a new role leading the Land Change Monitoring Assessment and Projection (LCMAP) science team. LCMAP is a relatively new USGS initiative developing an end-to-end capability to use the deep Landsat record to continuously track and characterize changes in land cover state and condition and translate the information into assessments of current and historical processes of cover and change.
Science and Products
Using seasonal climate scenarios in the ForageAhead annual forage production model for early drought impact assessment
Trends in tree cover change over three decades related to interannual climate variability and wildfire in California
Temporal greenness trends in stable natural land cover and relationships with climatic variability across the conterminous United States
Conterminous United States land-cover change (1985-2016): New insights from annual time series
Implementation of the CCDC algorithm to produce the LCMAP Collection 1.0 annual land surface change product
Hotter drought escalates tree cover declines in blue oak woodlands of California
Exploring the regional dynamics of U.S. irrigated agriculture from 2002 to 2017
Exploring VIIRS continuity with MODIS in an expedited capability for monitoring drought-related vegetation conditions
Investigating the effects of land use and land cover on the relationship between moisture and reflectance using Landsat Time Series
Land change monitoring, assessment, and projection
Lessons learned implementing an operational continuous U.S. national land change monitoring capability: The LCMAP approach
Mapping 30m irrigation extent across the United States by using a semi-automatic training approach on Google Earth Engine
Non-USGS Publications**
**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.
Eyes on Earth Episode 29 – Tracking Landscape Change with LCMAP
Eyes on Earth is a podcast on remote sensing, Earth observation, land change and science, brought to you by the USGS Earth Resources Observation and Science (EROS) Center. In this episode, we learn about an exciting new initiative to track landscape change in the U.S.
LCMAP and NLCD: Complementary Data for Understanding the Geography of the United States
USGS Land Change Monitoring, Assessment, and Projection releases ‘unprecedented’ reference dataset for United States
Eyes on Earth Episode 12 – Plant Health via Satellite (NDVI)
Eyes on Earth is a podcast on remote sensing, Earth observation, land change and science, brought to you by the USGS Earth Resources Observation and Science (EROS) Center. In this episode, we learn about an important tool for remote sensing scientists – the Normalized Difference Vegetation Index (NDVI).
MODIS Irrigated Agriculture
Moderate Resolution Imaging Spectroradiometer (MODIS) Irrigated Agriculture Dataset for the United States (MIrAD-US)
LCMAP Change Stories: Hurricanes in the Everglades
LCMAP Change Stories: Alabama Tornadoes
LCMAP Workshop 2018
Drought Monitoring Datasets Available as OGC Web Map Services (WMS)
Monitoring Vegetation Drought Stress
Conterminous United States Remote Sensing Phenology Metrics Database
Using Targeted Training Data to Develop Site Potential for the Upper Colorado River Basin from 2000 - 2018
Data files supporting the paper titled "Complementing data from ground-based sensors with satellite-derived products to measure ecological changes in relation to climate lessons from temperate wetland-upland landscapes"
Science and Products
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Using seasonal climate scenarios in the ForageAhead annual forage production model for early drought impact assessment
High interannual variability of forage production in semiarid grasslands leads to uncertainties when livestock producers make decisions, such as buying additional feed, relocating animals, or using flexible stocking. Within-season predictions of annual forage production (i.e., yearly production) can provide specific boundaries for producers to make these decisions with more information and possiblAuthorsMarkéta Poděbradská, Bruce K. Wylie, Michael J. Hayes, Deborah J. Bathke, Yared A. Bayissa, Stephen P. Boyte, Jesslyn F. Brown, Brian D. WardlowTrends in tree cover change over three decades related to interannual climate variability and wildfire in California
The U.S. State of California has experienced frequent drought events, hotter temperatures and other disruptions to the climate system whose effects on ecosystems have been widely reported in recent decades. Studies primarily confined to specific vegetation communities or species, individual drought incidents, or analysis over a relatively short intervals, has limited our understanding of the broadAuthorsFrancis K Dwomoh, Roger F. Auch, Jesslyn F. Brown, Heather J. TollerudTemporal greenness trends in stable natural land cover and relationships with climatic variability across the conterminous United States
Assessment of temporal trends in vegetation greenness and related influences aids understanding of recent change in terrestrial ecosystems and feedbacks from weather, climate, and environment. We analyzed 1-km normalized difference vegetation index (NDVI) timeseries data (1989–2016) derived from the Advanced Very High Resolution Radiometer (AVHRR) and developed growing season time-integrated NDVIAuthorsLei Ji, Jesslyn F. BrownConterminous United States land-cover change (1985-2016): New insights from annual time series
Sample-based estimates augmented by complete coverage land-cover maps were used to estimate area and describe patterns of annual land-cover change across the conterminous United States (CONUS) between 1985 and 2016. Most of the CONUS land cover remained stable in terms of net class change over this time, but a substantial gross change dynamic was captured by the annual and cumulative time intervalAuthorsRoger F. Auch, Danika Fay Wellington, Janis L. Taylor, Stephen V. Stehman, Heather J. Tollerud, Jesslyn F. Brown, Thomas Loveland, Bruce Pengra, Josephine Horton, Zhe Zhu, Alemayehu Midekisa, Kristi Sayler, George Z. Xian, Christopher Barnes, Ryan R. RekerImplementation of the CCDC algorithm to produce the LCMAP Collection 1.0 annual land surface change product
The increasing availability of high-quality remote sensing data and advanced technologies have spurred land cover mapping to characterize land change from local to global scales. However, most land change datasets either span multiple decades at a local scale or cover limited time over a larger geographic extent. Here, we present a new land cover and land surface change dataset created by the LandAuthorsGeorge Z. Xian, Kelcy Smith, Danika F. Wellington, Josephine Horton, Qiang Zhou, Congcong Li, Roger F. Auch, Jesslyn F. Brown, Zhe Zhu, Ryan R. RekerHotter drought escalates tree cover declines in blue oak woodlands of California
California has, in recent years, become a hotspot of interannual climatic variability, recording devastating climate-related disturbances with severe effects on tree resources. Understanding the patterns of tree cover change associated with these events is vital for developing strategies to sustain critical habitats of endemic and threatened vegetation communities. We assessed patterns of tree covAuthorsFrancis K Dwomoh, Jesslyn F. Brown, Heather J. Tollerud, Roger F. AuchExploring the regional dynamics of U.S. irrigated agriculture from 2002 to 2017
The United States has a geographically mature and stable land use and land cover system including land used as irrigated cropland; however, changes in irrigation land use frequently occur related to various drivers. We applied a consistent methodology at a 250 m spatial resolution across the lower 48 states to map and estimate irrigation dynamics for four map eras (2002, 2007, 2012, and 2017) andAuthorsDinesh Shrestha, Jesslyn F. Brown, Trenton D Benedict, Daniel HowardExploring VIIRS continuity with MODIS in an expedited capability for monitoring drought-related vegetation conditions
Vegetation has been effectively monitored using remote sensing time-series vegetation index (VI) data for several decades. Drought monitoring has been a common application with algorithms tuned to capturing anomalous temporal and spatial vegetation patterns. Drought stress models, such as the Vegetation Drought Response Index (VegDRI), often use VIs like the Normalized Difference Vegetation IndexAuthorsTrenton D Benedict, Jesslyn F. Brown, Stephen P. Boyte, Daniel Howard, Brian Fuchs, Brian D. Wardlow, Tsegaye Tadesse, Kirk EvensonInvestigating the effects of land use and land cover on the relationship between moisture and reflectance using Landsat Time Series
To better understand the Earth system, it is important to investigate the interactions between precipitation, land use/land cover (LULC), and the land surface, especially vegetation. An improved understanding of these land-atmosphere interactions can aid understanding of the climate system and modeling of time series satellite data. Here, we investigate the effect of precipitation and LULC on theAuthorsHeather J. Tollerud, Jesslyn F. Brown, Thomas LovelandLand change monitoring, assessment, and projection
There is a pressing need to monitor and understand the rapid land change happening around the world. The U.S. Geological Survey is developing a new capability, called Land Change Monitoring, Assessment, and Projection (LCMAP), to innovate the understanding of land change. This capability is the Earth Resources Observation and Science Center's foundation for an integrated U.S. Geological Survey-widAuthorsJennifer Rover, Jesslyn F. Brown, Roger F. Auch, Kristi Sayler, Terry L. Sohl, Heather J. Tollerud, George Z. XianLessons learned implementing an operational continuous U.S. national land change monitoring capability: The LCMAP approach
Growing demands for temporally specific information on land surface change are fueling a new generation of maps and statistics that can contribute to understanding geographic and temporal patterns of change across large regions, provide input into a wide range of environmental modeling studies, clarify the drivers of change, and provide more timely information for land managers. To meet these needAuthorsJesslyn F. Brown, Heather J. Tollerud, Christopher Barber, Qiang Zhou, John L. Dwyer, James Vogelmann, Thomas Loveland, Curtis Woodcock, Stephen V. Stehman, Zhe Zhu, Bruce Pengra, Kelcy Smith, Josephine Horton, George Z. Xian, Roger F. Auch, Terry L. Sohl, Kristi Sayler, Alisa L. Gallant, Daniel Zelenak, Ryan R. Reker, Jennifer R. RoverMapping 30m irrigation extent across the United States by using a semi-automatic training approach on Google Earth Engine
Accurate and timely information on the distribution of irrigated croplands is crucial to research on agriculture, water availability, land use, and climate change. While agricultural land use has been well characterized, less attention has been paid specifically to croplands that are irrigated, in part due to the difficulty in mapping and distinguishing irrigation in satellite imagery. In this stuAuthorsYanhua Xie, Tyler J. Lark, Jesslyn F. Brown, Holly GibbsNon-USGS Publications**
**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.
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Eyes on Earth Episode 29 – Tracking Landscape Change with LCMAP
Eyes on Earth is a podcast on remote sensing, Earth observation, land change and science, brought to you by the USGS Earth Resources Observation and Science (EROS) Center. In this episode, we learn about an exciting new initiative to track landscape change in the U.S.
LCMAP and NLCD: Complementary Data for Understanding the Geography of the United States
Land Change Monitoring, Assessment, and Projection (LCMAP) Collection 1 science products provide unprecedented monitoring of past changes occurring in land cover and condition across the conterminous U.S. over more than 30 years at an annual timestep.USGS Land Change Monitoring, Assessment, and Projection releases ‘unprecedented’ reference dataset for United States
The USGS Land Change Monitoring, Assessment and Projection (LCMAP) team has released its reference dataset for the Conterminous U.S. (CONUS), an 25,000-point trove of land cover data that represents the culmination of nearly five years of intensive human labor.Eyes on Earth Episode 12 – Plant Health via Satellite (NDVI)
Eyes on Earth is a podcast on remote sensing, Earth observation, land change and science, brought to you by the USGS Earth Resources Observation and Science (EROS) Center. In this episode, we learn about an important tool for remote sensing scientists – the Normalized Difference Vegetation Index (NDVI).
MODIS Irrigated Agriculture
Moderate Resolution Imaging Spectroradiometer (MODIS) Irrigated Agriculture Dataset for the United States (MIrAD-US)Moderate Resolution Imaging Spectroradiometer (MODIS) Irrigated Agriculture Dataset for the United States (MIrAD-US)
The Moderate Resolution Imaging Spectroradiometer (MODIS) Irrigated Agriculture Dataset for the United States (MIrAD-US) suite of irrigation products was developed by the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center. The goal of MIrAD is to provide a comprehensive and consistently processed geospatial dataset for irrigated agriculture across the conterminous...LCMAP Change Stories: Hurricanes in the Everglades
When Atlantic hurricanes make landfall in south Florida, the coastal marshes and mangrove forests of the Everglades often act as a buffer that protects residents from rising sea levels, high winds and storm surge.LCMAP Change Stories: Alabama Tornadoes
The USGS Land Change Monitoring, Assessment, and Projection initiative aims to identify where the landscape is changing and why.LCMAP Workshop 2018
The Land Change Monitoring, Assessment, and Projection (LCMAP) team presented pilot data and offered visitors an opportunity to work with LCMAP data at the Earth Resources Observation and Science Center in November 2018.Drought Monitoring Datasets Available as OGC Web Map Services (WMS)
Web Services The Drought Monitoring datasets are available as OGC Web Map Services (WMS). You can access the services using the below links.Monitoring Vegetation Drought Stress
Drought strikes somewhere in the United States every year, turning green landscapes brown as precipitation falls below normal levels and water supplies dwindle. Drought is typically a temporary climatic abnormality, but it is also an insidious natural hazard. It might last for weeks, months, or years and may have many negative effects. Drought can threaten crops, livestock, and livelihoods, stress... - Data
Conterminous United States Remote Sensing Phenology Metrics Database
Phenological dynamics of terrestrial ecosystems reflect the response of the Earth's vegetation canopy to changes in climate and hydrology and are thus important to monitor operationally. Researchers at the U.S. Geological Survey (USGS), Earth Resources Observation and Science (EROS) Center have developed methods for documenting the seasonal dynamics of vegetation in an operational fashion from satUsing Targeted Training Data to Develop Site Potential for the Upper Colorado River Basin from 2000 - 2018
Defining site potential for an area establishes its possible long-term vegetation growth productivity in a relatively undisturbed state, providing a realistic reference point for ecosystem performance. Modeling and mapping site potential helps to measure and identify naturally occurring variations on the landscape as opposed to variations caused by land management activities or disturbances (RiggeData files supporting the paper titled "Complementing data from ground-based sensors with satellite-derived products to measure ecological changes in relation to climate lessons from temperate wetland-upland landscapes"
The files on this page contain the data used for the research described in in the paper, "Challenges in complementing data from ground-based sensors with satellite-derived products to measure ecological changes in relation to climate lessons from temperate wetland-upland landscapes" (Gallant, A.L., Sadinski, W., Brown, J.F., Senay, G.B., Roth, M.F. 2018. Sensors). Supplementary Datafile 1 contai - Multimedia
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