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
Intercomparison, interpretation, and assessment of spring phenology in North America estimated from remote sensing for 1982-2006
NIDIS Remote Sensing Workshop, showcase of products and technologies—vegetation health (crops, rangeland, forest) products
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
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 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
Integrating growing season satellite metrics with climate data to map and monitor drought
Issues in characterizing phenology from satellite observations
Integrating satellite and climate data for U.S. drought mapping and monitoring: First steps
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.
Participated in these Eyes on Earth podcast episodes.
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Intercomparison, interpretation, and assessment of spring phenology in North America estimated from remote sensing for 1982-2006
Shifts in the timing of spring phenology are a central feature of global change research. Long-term observations of plant phenology have been used to track vegetation responses to climate variability but are often limited to particular species and locations and may not represent synoptic patterns. Satellite remote sensing is instead used for continental to global monitoring. Although numerous methAuthorsM.A. White, K. M. de Beurs, K. Didan, D.W. Inouye, A.D. Richardson, O.P. Jensen, J. O'Keefe, G. Zhang, R.R. Nemani, Leeuwen van, Jesslyn F. Brown, A. de Wit, M. Schaepman, X. Lin, M. Dettinger, A.S. Bailey, J. Kimball, M.D. Schwartz, D. D. Baldocchi, J.T. Lee, W.K. LauenrothNIDIS Remote Sensing Workshop, showcase of products and technologies—vegetation health (crops, rangeland, forest) products
No abstract available.AuthorsChristina AlvordAssessment of 2006 and 2007 drought patterns in the vegetation drought response index across Nebraska
The Vegetation Drought Response Index (VegDRI) is a hybrid geospatial drought indicator and monitoring tool that provides timely drought severity information with relatively higher spatial resolution (1-km2) than the traditional drought monitoring maps. The VegDRI model integrates climate-based drought index data, satellite-based vegetation index information, and several biophysical parameters. DuAuthorsJesslyn F. Brown, Brian D. Wardlow, Md Shahriar Pervez, Tsegaye TadesseThe Vegetation Drought Response Index (VegDRI): A new integrated approach for monitoring drought stress in vegetation
The development of new tools that provide timely, detailed-spatial-resolution drought information is essential for improving drought preparedness and response. This paper presents a new method for monitoring drought-induced vegetation stress called the Vegetation Drought Response Index (VegDRI). VegDRI integrates traditional climate-based drought indicators and satellite-derived vegetation index mAuthorsJesslyn F. Brown, B.D. Wardlow, T. Tadesse, M.J. Hayes, B. C. ReedEvaluation of MODIS NDVI and NDWI for vegetation drought monitoring using Oklahoma Mesonet soil moisture data
The evaluation of the relationship between satellite-derived vegetation indices (normalized difference vegetation index and normalized difference water index) and soil moisture improves our understanding of how these indices respond to soil moisture fluctuations. Soil moisture deficits are ultimately tied to drought stress on plants. The diverse terrain and climate of Oklahoma, the extensive soilAuthorsYingxin Gu, E. Hunt, B. Wardlow, J.B. Basara, Jesslyn F. Brown, J. P. VerdinA five-year analysis of MODIS NDVI and NDWI for grassland drought assessment over the central Great Plains of the United States
A five-year (2001–2005) history of moderate resolution imaging spectroradiometer (MODIS) normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) data was analyzed for grassland drought assessment within the central United States, specifically for the Flint Hills of Kansas and Oklahoma. Initial results show strong relationships among NDVI, NDWI, and drought conditAuthorsYingxin Gu, Jesslyn F. Brown, J. P. Verdin, B. WardlowA new approach for predicting drought-related vegetation stress: Integrating satellite, climate, and biophysical data over the U.S. central plains
Droughts are normal climate episodes, yet they are among the most expensive natural disasters in the world. Knowledge about the timing, severity, and pattern of droughts on the landscape can be incorporated into effective planning and decision-making. In this study, we present a data mining approach to modeling vegetation stress due to drought and mapping its spatial extent during the growing seasAuthorsTsegaye Tadesse, Jesslyn F. Brown, M.J. HayesTrend analysis of time-series phenology derived from satellite data
Remote sensing information has been used in studies of the seasonal dynamics (phenology) of the land surface for the past 15 years. While our understanding of remote sensing phenology is still in development, it is regarded as a key to understanding land surface processes over large areas. Repeat observations from satellite-borne multispectral sensors provide a mechanism to move from plant-specifiAuthorsB. C. Reed, Jesslyn F. BrownIntegrating growing season satellite metrics with climate data to map and monitor drought
No abstract available.AuthorsJesslyn F. Brown, Tsegaye TadesseIssues in characterizing phenology from satellite observations
Over the past decade, many investigators have published techniques for deriving phenological parameters, especially the start of the growing season (SOS), from time-series satellite imagery. The principal satellite sensor for these studies is the advanced very high resolution radiometer (AVHRR). This study investigates the characteristics of four of the primary methods for identifying SOS; maximumAuthorsB. C. Reed, J.F. BrownIntegrating satellite and climate data for U.S. drought mapping and monitoring: First steps
Although droughts are normal, recurring climate phenomena, they challenge our current ability to plan, predict, monitor, and provide relief to drought stricken areas. Because of the spatial and temporal variability of droughts, we need to improve the tools available to map and monitor them on many scales from local to national. A team of researchers from the US Geological Survey’s EROS Data CenterAuthorsJesslyn F. Brown, Tsegaye Tadesse, Bradley C. ReedNon-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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Participated in these Eyes on Earth podcast episodes.
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