Development of the Landsat Data Continuity Mission cloud-cover assessment algorithms
IEEE Transactions on Geoscience and Remote Sensing
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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.
| 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 | Institute of Electrical and Electronics Engineers |
| Contributing office(s) | Earth Resources Observation and Science (EROS) Center |
| Description | 15 p. |
| First page | 1140 |
| Last page | 1154 |
| Country | United States |
| Google Analytic Metrics | Metrics page |