The spectral signatures of the materials contained in hyperspectral images, also called
endmembers (EMs), can be significantly affected by variations in atmospheric, illumination …

Geologists have used remote sensing data since the advent of the technology for regional
mapping, structural interpretation and to aid in prospecting for ores and hydrocarbons. This …

Hyperspectral data (Table 1) is acquired as continuous narrowbands (eg, each band with 1
to 10 nanometer or nm bandwidths) over a range of electromagnetic spectrum (eg, 400 …

Abstract In 2007, the NASA Hyperspectral InfraRed Imager (HyspIRI) mission was
recommended in Earth Science and Applications from Space: National Imperatives for the …

Image classification is a complex process that may be affected by many factors. This paper
examines current practices, problems, and prospects of image classification. The emphasis …

The composite nature of remotely sensed spectral information often masks diagnostic
spectral features and hampers the detailed identification and mapping of targeted …

Since the publishing of the first edition of Classification Methods for Remotely Sensed Data
in 2001, the field of pattern recognition has expanded in many new directions that make use …

Variable illumination and environmental, atmospheric, and temporal conditions cause the
measured spectral signature for a material to vary within hyperspectral imagery. By ignoring …

Remotely sensed data have become the primary source for biomass estimation. A summary
of previous research on remote sensing‐based biomass estimation approaches and a …

Monitoring land changes is an important activity in landscape planning and resource
management. In this study, we analyze urban land changes in Atlanta metropolitan area …