[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.7780/kjrs.2005.21.5.425

Development of Agriculture-related Data Inventories Using IKONOS Images

Kim Seong-Joon (Dept. of Civil and Environmental System Engineering, Konkuk University)
Lim Hyuk-Jin (Dept. of Rural Engineering, Konkuk University)
Hong Seong-Min (Dept. of Rural Engineering, Konkuk University)
Lee Mi-Seon (Dept. of Rural Engineering, Konkuk University)
Park Geun-Ae (Dept. of Rural Engineering, Konkuk University)
Kwon Hyung-Joong (Dept. of Rural Engineering, Konkuk University)

Publication Information

Korean Journal of Remote Sensing / v.21, no.5, 2005 , pp. 425-431 More about this Journal

Abstract

This paper describes the method of using IKONOS imagery in the development of agriculture-related data inventories. Temporally different three images of panchromatic (1m resolution) and multi-spectral bands (4m resolution) were used to obtain the distribution and characteristics of rice, pear, grape, red pepper, garlic, and reservoir surface area with the field surveys. The result of this study suggests the utility of KOMPSAT-II, which increases the use of the crop and water resources data in rural areas by accumulating temporal data inventories.

Keywords

IKONOS; KOMPSAT-II; agriculture; data inventory; texture; pixel value;

Citations & Related Records

Reference

1	Kim, S. J., Hong, S. M., Lee, M. S., and Lim, H. J., 2004. Development of Agriculture-related Data Inventories using IKONOS Images, 2004 International Symposium on Remote Sensing, pp. 618-621
2	Sawaya, K. E., Olmanson, L. G., Reinert, N. J. Brezonik, P. L., and Bauer, M. E., 2003. Extending satellite remote sensing to local scales: land and water resource monitoring using high-resolution imagery, Remote Sensing of Environment, 88(1): 144-156 DOI ScienceOn
3	Pixoneer Inc., 2003. PG-STREAMER 2.2 User's Guide, pp. 279-298
4	Seelan, S. K., Laguette, S., Casady, G. M., Seielstad, and G. A., 2003. Remote Sensing Applications for Precision Agriculture: A learning community approach, Remote Sensing of Environment, 88(1): 157-169 DOI ScienceOn