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Land cover estimation with ALOS satellite image using a neural-network

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Abstract

On May 12, 2008, a large earthquake occurred in Sichuan, China. We analyzed the damage caused by this disaster using satellite images from ALOS, a Japanese satellite. The land cover classification is operated by images captured on AVNIR-2. Frequently, the AVNIR-2 images cannot be monitored because of the cloud cover and solar irradiation. The area near the center of the earthquake area is covered with clouds. The goal of this article is to classify the land cover using PALSAR images. PALSAR can observe over a 350-km-wide area independently of the weather. The PALSAR is a single-band sensor, and the inputs consist of many pixels by using the nearest pixel values, and the supervisor signal is the classes estimated by AVNIR-2.

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References

  1. Tsuchida Y, Omatu S, Yoshioka M (2009) The land cover classification with PALSAR and AVNIR-2 image. IEEJ C convention, Osaka, Japan, GS11-7

  2. RESTEC (2007) ALOS Products and Services, Japan

  3. CAS (2008) Concise atlas of the Wenchuan earthquake area. 2008/1, Starmap, China

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Correspondence to Yuta Tsuchida.

Additional information

This work was presented in part at the 15th International Symposium on Artificial Life and Robotics, Oita, Japan, February 4–6, 2010

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Tsuchida, Y., Omatu, S. & Yoshioka, M. Land cover estimation with ALOS satellite image using a neural-network. Artif Life Robotics 15, 37–40 (2010). https://doi.org/10.1007/s10015-010-0763-1

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  • DOI: https://doi.org/10.1007/s10015-010-0763-1

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