Share Email Print

Proceedings Paper

Cloud and shadow detection and removal for Landsat-8 data
Author(s): Xiangsheng Kong; Yonggang Qian; Anding Zhang
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Since 1972, Landsat program has experienced six successful missions that have contributed to nearly 40 years record of Earth Observations for monitoring the land cover and change dynamics. The successful launch of the Landsat Data Continuity Mission (LDCM, now named Landsat 8) on February 11, 2013 continues the mission of collecting images of the Earth with an open (free) data policy. Landsat 8 carries two push broom sensors: the Operational Land Imager (OLI) will collect data for nine shortwave spectral bands over a 185 km swath with a 30 m spatial resolution for all bands except a 15 m panchromatic band. The other instrument, the Thermal Infrared Sensor (TIRS) will collect image data for two thermal bands with a 100 m resolution over a 185 km swath. However, cloud and associated cloud shadows frequently obscure the detection of land surface and restrict the the analysis of change trends over time. This paper presents a new method to detect and remove cloud and cloud shadows using the Landsat 8 first Image data (WRS2: Path/Row =33/32, acquired on March 18, 2013). The method uses six bands for transformation to calculate intensity of cloud and cloud shadows from the nine spectral bands and was further removed. The method takes advantage of spectral information. The validation demonstrates that cloud and cloud shadows contaminated pixels were accurately detected with overall accuracies of 98 and 97%, respectively. However, for thick cloud and cloud shadows, the performance of this method was limited. With further development there is potential for this method using for atmospheric corrections to improve landscape change detection.

Paper Details

Date Published: 26 October 2013
PDF: 10 pages
Proc. SPIE 8921, MIPPR 2013: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 89210N (26 October 2013); doi: 10.1117/12.2031120
Show Author Affiliations
Xiangsheng Kong, Ludong Univ. (China)
Yonggang Qian, Academy of Opto-Electronics (China)
Anding Zhang, Ludong Univ. (China)

Published in SPIE Proceedings Vol. 8921:
MIPPR 2013: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications
Jinwen Tian; Jie Ma, Editor(s)

© SPIE. Terms of Use
Back to Top