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 the understanding of changes in terrestrial vegetation, drought early warning, and transitions in land cover and land use by 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 over 30 years. Her work in applied geographic research has contributed to improving understanding of terrestrial vegetation patterns 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. In the 1990s, 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. From 2001 to 2017, she led multiple projects mainly focused on developing new monitoring tools, including VegDRI and QuickDRI, 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 leading the Land Change Monitoring Assessment and Projection (LCMAP) science team. LCMAP was a USGS initiative to develop 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. In 2023, the LCMAP project was integrated with the National Land Cover Database team. Under Jess’s leadership, this team developed and produced a new annual land cover database for the conterminous U.S. covering 39 years from 1985 to 2023 utilizing the long Landsat record, deep learning methods, and cloud computing.
Science and Products
Remote Sensing Phenology
The Effects of Drought on Vegetation Phenology and Wildlife
Participated in these Eyes on Earth podcast episodes.
Phenological classification of the United States: A geographic framework for extending multi-sensor time-series data Phenological classification of the United States: A geographic framework for extending multi-sensor time-series data
Mapping irrigated lands at 250-m scale by merging MODIS data and National Agricultural Statistics Mapping irrigated lands at 250-m scale by merging MODIS data and National Agricultural Statistics
Mapping irrigated lands across the United States using MODIS satellite imagery Mapping irrigated lands across the United States using MODIS satellite imagery
Intercomparison, interpretation, and assessment of spring phenology in North America estimated from remote sensing for 1982-2006 Intercomparison, interpretation, and assessment of spring phenology in North America estimated from remote sensing for 1982-2006
Assessment of 2006 and 2007 drought patterns in the vegetation drought response index across Nebraska Assessment of 2006 and 2007 drought patterns in the vegetation drought response index across Nebraska
The Vegetation Drought Response Index (VegDRI): A new integrated approach for monitoring drought stress in vegetation The Vegetation Drought Response Index (VegDRI): A new integrated approach for monitoring drought stress in vegetation
Evaluation of MODIS NDVI and NDWI for vegetation drought monitoring using Oklahoma Mesonet soil moisture data Evaluation of MODIS NDVI and NDWI for vegetation drought monitoring using Oklahoma Mesonet soil moisture data
A five-year analysis of MODIS NDVI and NDWI for grassland drought assessment over the central Great Plains of the United States A five-year analysis of MODIS NDVI and NDWI for grassland drought assessment over the central Great Plains of the United States
Range condition as input to water quality monitoring in the northern Plains Range condition as input to water quality monitoring in the northern Plains
A new approach for predicting drought-related vegetation stress: Integrating satellite, climate, and biophysical data over the U.S. central plains A new approach for predicting drought-related vegetation stress: Integrating satellite, climate, and biophysical data over the U.S. central plains
Trend analysis of time-series phenology derived from satellite data Trend analysis of time-series phenology derived from satellite data
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
Remote Sensing Phenology
The Effects of Drought on Vegetation Phenology and Wildlife
Participated in these Eyes on Earth podcast episodes.
Phenological classification of the United States: A geographic framework for extending multi-sensor time-series data Phenological classification of the United States: A geographic framework for extending multi-sensor time-series data
Mapping irrigated lands at 250-m scale by merging MODIS data and National Agricultural Statistics Mapping irrigated lands at 250-m scale by merging MODIS data and National Agricultural Statistics
Mapping irrigated lands across the United States using MODIS satellite imagery Mapping irrigated lands across the United States using MODIS satellite imagery
Intercomparison, interpretation, and assessment of spring phenology in North America estimated from remote sensing for 1982-2006 Intercomparison, interpretation, and assessment of spring phenology in North America estimated from remote sensing for 1982-2006
Assessment of 2006 and 2007 drought patterns in the vegetation drought response index across Nebraska Assessment of 2006 and 2007 drought patterns in the vegetation drought response index across Nebraska
The Vegetation Drought Response Index (VegDRI): A new integrated approach for monitoring drought stress in vegetation The Vegetation Drought Response Index (VegDRI): A new integrated approach for monitoring drought stress in vegetation
Evaluation of MODIS NDVI and NDWI for vegetation drought monitoring using Oklahoma Mesonet soil moisture data Evaluation of MODIS NDVI and NDWI for vegetation drought monitoring using Oklahoma Mesonet soil moisture data
A five-year analysis of MODIS NDVI and NDWI for grassland drought assessment over the central Great Plains of the United States A five-year analysis of MODIS NDVI and NDWI for grassland drought assessment over the central Great Plains of the United States
Range condition as input to water quality monitoring in the northern Plains Range condition as input to water quality monitoring in the northern Plains
A new approach for predicting drought-related vegetation stress: Integrating satellite, climate, and biophysical data over the U.S. central plains A new approach for predicting drought-related vegetation stress: Integrating satellite, climate, and biophysical data over the U.S. central plains
Trend analysis of time-series phenology derived from satellite data Trend analysis of time-series phenology derived from satellite data
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.