Document Type

Thesis - Open Access

Award Date


Degree Name

Master of Science (MS)

Department / School

Electrical Engineering and Computer Science

First Advisor

Morakot Kaewmanee


This research aimed to develop a novel dark hyperspectral absolute calibration (DAHAC) model using stable dark targets of "Global Cluster - 36" (GC-36), one of the clusters from "300 Class Global Classification." The stable dark sites were identified from GC-36 called "Dark EPICS-Global" covering the surface types viz; dark rock, volcanic area, and dark sand. The Dark EPICS-Global shows a temporal variation of 0.02 unit reflectance. This work uses the Landsat-8 (L8) Operational Land Imager (OLI) , Sentinel-2A (S2A) Multispectral Instrument (MSI) , and Earth Observing One (EO-1) Hyperion data for the DAHAC model development, where well-calibrated L8 and S2A are used as the reference sensors while EO-1 Hyperion with 10 nm spectral resolution is used as a hyperspectral library. The dark hyperspectral dataset (DaHD) is generated by combining the normalized hyperspectral profile of L8 and S2A for the DAHAC model development. The DAHAC model developed in this study takes into account the solar zenith and azimuth angles as well as the view zenith and azimuth angles in Cartesian coordinates form. This model is capable of predicting TOA reflectance in all existing spectral bands of any sensor. The DAHAC model was then validated with Landsat-7 (L7) , Landsat-9 (L9) , and Sentinel-2B (S2B) satellites from their launch dates to March 2022. These satellite sensors vary in terms of their spectral resolution, equatorial crossing time, spatial resolution, etc. The comparison between the DAHAC model and satellite measurements shows accuracy within 0.01 unit reflectance across overall spectral bands. The proposed DAHAC model uncertainty level is determined using Monte Carlo Simulation and found to be 0.04 and 0.05 unit reflectance for VNIR and SWIR channels, respectively. The DAHAC model double ratio is used as a tool to perform the inter-comparison between two satellites. The sensor inter-comparison results for L8 and L9 shows a 2% difference and 1% for S2A and S2B across all spectral bands.

Library of Congress Subject Headings

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


South Dakota State University



Rights Statement

In Copyright