Document Type

Thesis - Open Access

Award Date


Degree Name

Master of Science (MS)

Department / School

Electrical Engineering and Computer Science

First Advisor

Larry Leigh

Second Advisor

Morakot Kaewmanee


Hyperion EO-1 Hyperspectral APICS model Hyperspectral BRDF Landsat 8 Libya 4 PICS Sentinel 2A, 2B


The objective of this paper is to find an empirical hyperspectral absolute calibration model using Libya 4 pseudo-invariant calibration site (PICS). The approach involves using the Landsat 8 (L8) Operational Land Imager (OLI) as the reference radiometer and using Earth Observing One (EO-1) Hyperion, with a spectral resolution of 10 nm as a hyperspectral source. This model utilizes data from a region of interest (ROI) in an “optimal region” of 3% temporal, spatial, and spectral stability within the Libya 4 PICS. It uses an improved, simple, empirical, hyperspectral Bidirectional Reflectance Distribution function (BRDF) model accounting for four angles: solar zenith and azimuth, and view zenith and azimuth angles. This model can perform absolute calibration in 1 nm spectral resolution by predicting TOA reflectance in all existing spectral bands of the sensors. The resultant model was validated with image data acquired from satellite sensors such as Landsat 7, Sentinel 2A, and Sentinel 2B, Terra MODIS, Aqua MODIS, from their launch date to 2020. These satellite sensors differ in terms of the width of their spectral band-pass, overpass time, off-nadir viewing capabilities, spatial resolution, and temporal revisit time, etc. The result demonstrates the efficacy of the proposed model has an accuracy of the order of 3% with a precision of about 3% for the nadir viewing sensors (with view zenith angle up to 5°) used in the study. For the off-nadir viewing satellites with view zenith angle up to 20°, it can have an estimated accuracy of 6% and precision of 4%.

Library of Congress Subject Headings

Hyperspectral imaging.
Landsat satellites -- Calibration.
Artificial satellites in remote sensing -- Calibration.
Imaging systems -- Image quality.
Remote sensing -- Data processing.

Number of Pages



South Dakota State University



Rights Statement

In Copyright