Raymond Kokaly
Raymond Kokaly is an expert on the application of remote sensing and spectroscopy for vegetation and mineral characterization. His peer-reviewed publications on the use of spectroscopy include: quantifying biochemical content in leaf spectra, discriminating conifer species, examining post-fire surface cover, and characterizing the impact of oil contamination from the Deepwater Horizon spill.
His research has used multispectral and hyperspectral remote sensing data from AVHRR, Landsat, Hyperion, AVIRIS, HyMap, and MODIS. Raymond created the PRISM software, a framework for archiving and analyzing spectroscopic data collected in the laboratory and the field and from remote sensing platforms. PRISM was applied to map surficial minerals across most of Afghanistan, covering more than 480,000 sq. km. an area about the size of the state of California.
Professional Experience
Research Geophysicist, U.S. Geological Survey, 1996–present
Education and Certifications
University of Colorado at Boulder, M.S. in Aerospace Engineering Sciences, 1993
Science and Products
Hyperspectral surface materials map of quadrangle 3264, Naw Zad-Musa Qala (423) and Dihrawud (424) quadrangles, Afghanistan, showing iron-bearing minerals and other materials
Spectroscopic remote sensing for material identification, vegetation characterization, and mapping
PRISM: Processing routines in IDL for spectroscopic measurements (installation manual and user's guide, version 1.0)
Shoreline surveys of oil-impacted marsh in southern Louisiana, July to August 2010
DESI-Detection of early-season invasives (software-installation manual and user's guide version 1.0)
Detecting Cheatgrass on the Colorado Plateau using Landsat data: A tutorial for the DESI software
Mapping the distribution of materials in hyperspectral data using the USGS Material Identification and Characterization Algorithm (MICA)
Identifying materials by measuring and analyzing their reflectance spectra has been an important method in analytical chemistry for decades. Airborne and space-based imaging spectrometers allow scientists to detect materials and map their distributions across the landscape. With new satellite-borne hyperspectral sensors planned for the future, for example, HYSPIRI (HYPerspectral InfraRed Imager),
A method for quantitative mapping of thick oil spills using imaging spectroscopy
A rapid method for creating qualitative images indicative of thick oil emulsion on the ocean's surface from imaging spectrometer data
Estimated minimum discharge rates of the Deepwater Horizon spill— Interim report to the flow rate technical group from the Mass Balance Team
A Method for Qualitative Mapping of Thick Oil Spills Using Imaging Spectroscopy
Sample collection of ash and burned soils from the October 2007 southern California Wildfires
Science and Products
Hyperspectral surface materials map of quadrangle 3264, Naw Zad-Musa Qala (423) and Dihrawud (424) quadrangles, Afghanistan, showing iron-bearing minerals and other materials
Spectroscopic remote sensing for material identification, vegetation characterization, and mapping
PRISM: Processing routines in IDL for spectroscopic measurements (installation manual and user's guide, version 1.0)
Shoreline surveys of oil-impacted marsh in southern Louisiana, July to August 2010
DESI-Detection of early-season invasives (software-installation manual and user's guide version 1.0)
Detecting Cheatgrass on the Colorado Plateau using Landsat data: A tutorial for the DESI software
Mapping the distribution of materials in hyperspectral data using the USGS Material Identification and Characterization Algorithm (MICA)
Identifying materials by measuring and analyzing their reflectance spectra has been an important method in analytical chemistry for decades. Airborne and space-based imaging spectrometers allow scientists to detect materials and map their distributions across the landscape. With new satellite-borne hyperspectral sensors planned for the future, for example, HYSPIRI (HYPerspectral InfraRed Imager),