Error analysis of spectral reflectance derived from imaging spectrometer data

Abstract

As the field of remote imaging spectrometry grows, interest increases in applications that require the data be "corrected" to surface reflectance. However, the utility of the data for these applications will be limited by the accuracy to which the correction can be performed. Two approaches to atmospheric compensation are reviewed and applied to airbome spectrometer data to study their error characteristics. An end-to-end analysis model is used to extend the study to examine the effects of individual sources of error.Results indicate that random errors of 1 to 2% reflectance units and bias errors of 1 to 4% are achievable in atmospheric window regions, with considerably higher errors in atmospheric absorption bands.

Model-based Exploration of HSI Spaceborne Sensor Requirements with Application Performance as the Metric

“…Previous work has shown these codes to have an approximate error of 1% for 10 nm typical bandwidths [3]. While it is unclear how this error may vary with sensor spectral resolution, reasonable estimates of its magnitude were made based on experience.…”

Critical Metadata for Spectroscopy Field Campaigns

“…Spectroscopy protocols practiced worldwide record metadata relating to the instrument properties, illumination and viewing angles, reference standards and general project information on an ad hoc basis [4][5][6] in a variety of formats including logsheets, and occasionally, databases. It is widely acknowledged that instrument and study design influence the spectral measurements obtained and should be documented to identify their impact in the experiments and allow intercomparison of datasets [7][8][9][10][11]. The impact of these variables across datasets has not yet been fully identified within the remote sensing community nor can it be properly quantified in many instances.…”