The American Society for Photogrammetry and Remote Sensing (ASPRS) Boeing Award Selection Committee recently announced the winners of this year’s Boeing Award for Best Paper in Image Analysis and Interpretation.
The winners are Robert A. Chastain, Jr., Matthew A. Struckhoff, Hong S. He, and David R. Larsen for “Mapping Vegetation Communities Using Statistical Data Fusion in the Ozark National Scenic Riverways, Missouri, USA.” PE&RS 74, (2), 247-264.
Presentation of this award took place in March during the ASPRS 2009 Annual Conference in Baltimore, Maryland. The award is presented by ASPRS through the ASPRS Foundation, with funding provided by Boeing I&SS Mission Systems. The purpose of the award is to stimulate development and recognize achievement in image interpretation and analysis through special acknowledgment of superior publications in the field. The award consists of a presentation plaque provided by Boeing and cash award of $500.
Established in 1965 as the Autometric Award, this grant recognizes development and achievement in the field of photographic interpretation through special acknowledgment of superior publications on the various aspects of image analysis and interpretation.
Founded in 1934, ASPRS is an international professional organization of 6,000 geospatial data professionals. ASPRS is devoted to advancing knowledge and improving understanding of the mapping sciences to promote responsible application of photogrammetry, remote sensing, geographic information systems and supporting technologies.
Founded in 1979, The ASPRS Foundation, Inc. is an independent 501 (c) 3 organization established to provide grants, scholarships, loans and other forms of aid to individuals or organizations pursuing knowledge of imaging and geospatial information science and technology, and their applications across the scientific, governmental, and commercial sectors. The Foundation is the primary funding source for all non-sponsored awards and scholarships recognized by the American Society for Photogrammetry and Remote Sensing.