Çѱ¹Çؾç°úÇбâ¼ú¿ø(KIOST)¿¡¼ Á¦14ȸ ÀüÁö±¸ Çؾç¿ø°ÝŽ»ç Çмú´ëȸ(Pan Ocean Remote Sensing Conference 2018)¸¦ ¾Æ·¡¿Í °°ÀÌ °³ÃÖÇÕ´Ï´Ù.
- ¾Æ ·¡ - ¤· ÀϽà ¹× Àå¼Ò: - PORSEC 2018 (Conference): 2018³â 11¿ù 4ÀÏ~11¿ù 7ÀÏ/Á¦ÁÖ±¹Á¦ÄÁº¥¼Ç¼¾ÅÍ 3Ãþ - Tutorial (Pre-Conference): 2018³â 10¿ù 30ÀÏ~11¿ù 3ÀÏ/ Çѱ¹Çؾç°úÇбâ¼ú¿ø Á¦ÁÖ¼¾ÅÍ
¤· ÃÊ·Ï Á¢¼ö: 2018³â 6¿ù 8ÀÏ~ 7¿ù 6ÀÏ ¤· »çÀü ¿Â¶óÀÎ µî·Ï: 2018³â 7¿ù 1ÀÏ~9¿ù 14ÀÏ ¤· Àü½ÃºÎ½º Âü°¡ µî·Ï ¸¶°¨: 2018³â 9¿ù 14ÀÏ
¤· Çмú´ëȸ ȨÆäÀÌÁö: http://porsec2018.kosc.kr ¤· Call-for-abstract: http://porsec2018.kosc.kr/wp-content/uploads/2018/06/PORSEC2018_callforabstract.pdf ¤· PORSEC2018 Brochure: http://porsec2018.kosc.kr/wp-content/uploads/2018/06/PORSEC2018_brochure_s.pdf
¤·¼¼¼Ç - Sea surface roughness from high resolution SAR - Satellite radar altimetry: progress in observing open oceans to coastal zone - Remote sensing of coastal ecosystems and intertidal flats - Air-sea fluxes estimated from remotely sensed data - GOCI-II development and application - Ocean color application - Sustainable development of Fisheries and Aquaculture using the multi-remote sensing technology and GIS - Operational oceanography - Satellite remote sensing application to meteorology, air quality, and climate - Remote Sensing and Understanding of Floating Vegetation Populations in the World Ocean - Advances in ocean observation with SAR - Polarization Sensitivity of Satellite Ocean Color Sensors - Machine learning applications to ocean satellite remote sensing
¤·°ü·Ã ¹®ÀÇ: Çѱ¹Çؾç°úÇбâ¼ú¿ø ÇؾçÀ§¼º¼¾ÅÍ ¹Ú¸í¼÷ ¹Ú»ç (mspark@kiost.ac.kr)
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