Development of the Landsat Data Continuity Mission Cloud Cover Assessment Algorithms

IEEE Transactions on Geoscience and Remote Sensing
By: , and 

Links

Abstract

The upcoming launch of the Operational Land Imager (OLI) will start the next era of the Landsat program. However, the Automated Cloud-Cover Assessment (CCA) (ACCA) algorithm used on Landsat 7 requires a thermal band and is thus not suited for OLI. There will be a thermal instrument on the Landsat Data Continuity Mission (LDCM)-the Thermal Infrared Sensor-which may not be available during all OLI collections. This illustrates a need for CCA for LDCM in the absence of thermal data. To research possibilities for full-resolution OLI cloud assessment, a global data set of 207 Landsat 7 scenes with manually generated cloud masks was created. It was used to evaluate the ACCA algorithm, showing that the algorithm correctly classified 79.9% of a standard test subset of 3.95 109 pixels. The data set was also used to develop and validate two successor algorithms for use with OLI data-one derived from an off-the-shelf machine learning package and one based on ACCA but enhanced by a simple neural network. These comprehensive CCA algorithms were shown to correctly classify pixels as cloudy or clear 88.5% and 89.7% of the time, respectively.

Additional publication details

Publication type Article
Publication Subtype Journal Article
Title Development of the Landsat Data Continuity Mission Cloud Cover Assessment Algorithms
Series title IEEE Transactions on Geoscience and Remote Sensing
DOI 10.1109/TGRS.2011.2164087
Volume 50
Issue 4
Year Published 2012
Language English
Publisher location Reston, VA
Contributing office(s) Earth Resources Observation and Science (EROS) Center
Larger Work Type Article
Larger Work Subtype Journal Article
Larger Work Title IEEE Transactions on Geoscience and Remote Sensing
First page 1140
Last page 1154
Country United States