NASA Logo

NTRS

NTRS - NASA Technical Reports Server

Back to Results
Virtual Sensors: Using Data Mining Techniques to Efficiently Estimate Remote Sensing SpectraVarious instruments are used to create images of the Earth and other objects in the universe in a diverse set of wavelength bands with the aim of understanding natural phenomena. These instruments are sometimes built in a phased approach, with some measurement capabilities being added in later phases. In other cases, there may not be a planned increase in measurement capability, but technology may mature to the point that it offers new measurement capabilities that were not available before. In still other cases, detailed spectral measurements may be too costly to perform on a large sample. Thus, lower resolution instruments with lower associated cost may be used to take the majority of measurements. Higher resolution instruments, with a higher associated cost may be used to take only a small fraction of the measurements in a given area. Many applied science questions that are relevant to the remote sensing community need to be addressed by analyzing enormous amounts of data that were generated from instruments with disparate measurement capability. This paper addresses this problem by demonstrating methods to produce high accuracy estimates of spectra with an associated measure of uncertainty from data that is perhaps nonlinearly correlated with the spectra. In particular, we demonstrate multi-layer perceptrons (MLPs), Support Vector Machines (SVMs) with Radial Basis Function (RBF) kernels, and SVMs with Mixture Density Mercer Kernels (MDMK). We call this type of an estimator a Virtual Sensor because it predicts, with a measure of uncertainty, unmeasured spectral phenomena.
Document ID
20040081085
Document Type
Preprint (Draft being sent to journal)
Authors
Srivastava, Ashok N. (NASA Ames Research Center Moffett Field, CA, United States)
Oza, Nikunj (NASA Ames Research Center Moffett Field, CA, United States)
Stroeve, Julienne (National Snow and Ice Daya Center United States)
Date Acquired
September 7, 2013
Publication Date
March 12, 2004
Subject Category
Instrumentation and Photography
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.

Available Downloads

NameType 20040081085.pdf STI