Drought is a complex stress which elicits a wide variety of plant responses. As such, genetic
studies of drought are particularly difficult. Elucidation of the genetic basis of components …

Hyperspectral sensors enable the study of the chemical properties of scene materials
remotely for the purpose of identification, detection, and chemical composition analysis of …

Hyperspectral imagery can obtain hundreds of narrow spectral bands of ground objects. The
abundant and detailed spectral information offers a unique diagnostic identification ability for …

Hyperspectral remote sensing technology has advanced significantly in the past two
decades. Current sensors onboard airborne and spaceborne platforms cover large areas of …

A new spectral-spatial classification scheme for hyperspectral images is proposed. The
method combines the results of a pixel wise support vector machine classification and the …

Anomaly detection is an important task for hyperspectral data exploitation. A standard
approach for anomaly detection in the literature is the method developed by Reed and …

Remote sensing data have become very widespread in recent years, and the exploitation of
this technology has gone from developments mainly conducted by government intelligence …

Advances in sensor and computer technology are revolutionizing the way remotely sensed
data is collected, managed and analyzed. In particular, many current and future applications …

In this paper, a new method for supervised hyperspectral data classification is proposed. In
particular, the notion of stochastic minimum spanning forest (MSF) is introduced. For a given …

In most applications, anomaly detection operates in an unsupervised mode by looking for
outliers hoping that they are anomalies. Unfortunately, most anomaly detectors do not come …