Several decades ago, USGS EROS employees were pioneers in land cover mapping—turning satellite imagery into a record of what covers the land, from farmland to forest to urban areas. National and global datasets with a variety of uses resulted from these efforts.
Jesslyn Brown
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
Multi-resolution Land Cover Characterization Consortium
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)
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"
Participated in these Eyes on Earth podcast episodes.
Several decades ago, USGS EROS employees were pioneers in land cover mapping—turning satellite imagery into a record of what covers the land, from farmland to forest to urban areas. National and global datasets with a variety of uses resulted from these efforts.
The U.S. Geological Survey took a bold step toward documenting change across the landscape with the launch of the first Landsat satellite in 1972. Since then, it’s collected nearly five decades of imagery. But it takes more than just imagery to understand change. It takes time, effort—and serious computing horsepower.
The U.S. Geological Survey took a bold step toward documenting change across the landscape with the launch of the first Landsat satellite in 1972. Since then, it’s collected nearly five decades of imagery. But it takes more than just imagery to understand change. It takes time, effort—and serious computing horsepower.
A farmer at the foot of a corn stalk can tell how well the plant is faring. That same farmer might survey his entire field for crop health. But assessing the health of crops or forests at regional, national, and international scales requires remote sensing, most often via satellite.
A farmer at the foot of a corn stalk can tell how well the plant is faring. That same farmer might survey his entire field for crop health. But assessing the health of crops or forests at regional, national, and international scales requires remote sensing, most often via satellite.
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 United States national land change monitoring capability: The Land Change Monitoring, Assessment, and Projection (LCMAP) approach
Mapping irrigated cropland extent across the conterminous United States at 30 m resolution 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.
Science and Products
Multi-resolution Land Cover Characterization Consortium
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)
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"
Participated in these Eyes on Earth podcast episodes.
Several decades ago, USGS EROS employees were pioneers in land cover mapping—turning satellite imagery into a record of what covers the land, from farmland to forest to urban areas. National and global datasets with a variety of uses resulted from these efforts.
Several decades ago, USGS EROS employees were pioneers in land cover mapping—turning satellite imagery into a record of what covers the land, from farmland to forest to urban areas. National and global datasets with a variety of uses resulted from these efforts.
The U.S. Geological Survey took a bold step toward documenting change across the landscape with the launch of the first Landsat satellite in 1972. Since then, it’s collected nearly five decades of imagery. But it takes more than just imagery to understand change. It takes time, effort—and serious computing horsepower.
The U.S. Geological Survey took a bold step toward documenting change across the landscape with the launch of the first Landsat satellite in 1972. Since then, it’s collected nearly five decades of imagery. But it takes more than just imagery to understand change. It takes time, effort—and serious computing horsepower.
A farmer at the foot of a corn stalk can tell how well the plant is faring. That same farmer might survey his entire field for crop health. But assessing the health of crops or forests at regional, national, and international scales requires remote sensing, most often via satellite.
A farmer at the foot of a corn stalk can tell how well the plant is faring. That same farmer might survey his entire field for crop health. But assessing the health of crops or forests at regional, national, and international scales requires remote sensing, most often via satellite.
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 United States national land change monitoring capability: The Land Change Monitoring, Assessment, and Projection (LCMAP) approach
Mapping irrigated cropland extent across the conterminous United States at 30 m resolution 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.