TITLE:
Radiometric Characteristics of the Landsat Collection 1 Dataset
AUTHORS:
Shuang Li, Weile Wang, Sangram Ganguly, Ramakrishna R. Nemani
KEYWORDS:
Landsat Collection 1, Cross-Calibration, Landsat-4 (L4) Thematic Mapper (TM), Landsat-5 (L5) Thematic Mapper (TM), Landsat-7 (L7) Enhanced Thematic Mapper Plus (ETM+), Landsat-8 (L8) Operational Land Imager (OLI)
JOURNAL NAME:
Advances in Remote Sensing,
Vol.7 No.3,
September
13,
2018
ABSTRACT: This
study evaluates the long-term radiometric performance of the USGS new released Landsat
Collection 1 archive, including the absolute calibration of each Landsat sensor
as well as the relative cross-calibration among the four most popular Landsat
sensors. A total of 920 Landsat Collection 1 scenes were evaluated against the
corresponding Pre-Collection images over a Pseudo-Invariant Site, Railroad
Valley Playa Nevada, United States (RVPN). The radiometric performance of the
six Landsat solar reflective bands, in terms of both Digital Numbers (DNs) and
at-sensor Top of Atmosphere (TOA) reflectance, on the sensor cross-calibration
was examined. Results show that absolute radiometric calibration at DNs level
was applied to the Landsat-4 and -5 TM (L4 TM and L5 TM) by –1.119% to 0.126%. For L4 TM and L5 TM, the
cross-calibration decreased the radiometric measurement level by rescaling
at-sensor radiance to DN values. The radiometric changes, –0.77% for L4 TM,
0.95% for L5 TM, –0.26% for L7 ETM+, and –0.01% for L8 OLI, were detected
during the cross-calibration stage of converting DNs into TOA reflectance. This
study has also indicated that the long-term radiometric performance for the Landsat
Collection 1 archive is promising. Supports of these conclusions were
demonstrated through the time-series analysis based on the Landsat Collection 1
image stack. Nevertheless, the radiometric changes across the four Landsat
sensors raised concerns of the previous Landsat Pre-Collection based results.
We suggest that Landsat users should pay attention to differences in results
from Pre-Collection and Collection 1 time-series data sets.