JOURNAL BROWSE
Search
Advanced SearchSearch Tips
Estimation of Rice Growth Using RADARSTA-2 SAR Images at Seosan Region
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
Estimation of Rice Growth Using RADARSTA-2 SAR Images at Seosan Region
Kim, Yihyun; Hong, Sukyoung; Lee, Kyoungdo; Jang, Soyeong;
  PDF(new window)
 Abstract
Radar remote sensing is appropriate for monitoring rice because the areas where this crop is cultivated are often cloudy and rainy. Especially, Synthetic Aperture Radar (SAR) can acquire remote sensing information with a high temporal resolution in tropical and subtropical regions due to its all-weather capability. This paper analyzes the relationships between backscattering coefficients of rice measured by RADARSAT-2 SAR and growth parameters during a rice growth period. We examined the temporal variations of backscattering coefficients with full polarization. Backscattering coefficients for all polarizations increased until Day Of Year (DOY 222) and then decreased along with Leaf Area Index (LAI), fresh weight, and Vegetation Water Content (VWC). Vertical transmit and Vertical receive polarization (VV)-polarization backscattering coefficients were higher than Horizontal transmit and Horizontal receive polarization (HH)-polarization backscattering coefficients in early rice growth stage and HH-polarization backscattering coefficients were higher than VV-polarization backscattering coefficients after effective tillering stage (DOY 186). Correlation analysis between backscattering coefficients and rice growth parameters revealed that HH-polarization was highly correlated with LAI, fresh weight, and VWC. Based on the observed relationships between backscattering coefficients and variables of cultivation, prediction equations were developed using the HH-polarization backscattering coefficients.
 Keywords
Synthetic aperture radar;Rice;Backscattering coefficients;Growth parameters;
 Language
Korean
 Cited by
1.
RADARSAT-2 SAR를 이용한 서산 및 평양 지역의 벼 생육 모니터링 적용성 평가 -RapidEye와의 비교를 통해-,나상일;홍석영;김이현;이경도;

한국농공학회논문집, 2014. vol.56. 5, pp.55-65 crossref(new window)
1.
Evaluation of the Applicability of Rice Growth Monitoring on Seosan and Pyongyang Region using RADARSAT-2 SAR -By Comparing RapidEye-, Journal of The Korean Society of Agricultural Engineers, 2014, 56, 5, 55  crossref(new windwow)
 References
1.
Bouvet, A., T. Le Toan, and N. Lamdao. 2009. Monitoring of the rice cropping system in the Mekong Delta using ENVISAT/ASAR dual polarization data. IEEE Trans. Geosci. Remote Sens. 47:517-526. crossref(new window)

2.
Bouvet, A. and T. Le Toan. 2011. Use of ENVISAT/ASAR wide-swath data for timely rice fields mapping in the Mekong River Delta. Remote Sens. Environ. 115(4):1090-1101. crossref(new window)

3.
Chakraborty, M., K.R. Manjunath, S. Panigrahy, N. Kundu, and J.S. Parihar. 2005. Rice crop parameter retrieval using multi-temporal, multi-incidence angle Radarsat SAR data. ISPRS J Photogramm Remote Sens. 59(5): 310-322. crossref(new window)

4.
Chen, J., H. Lin, and Z. Pei. 2007. Application of ENVISAT ASAR data in mapping rice crop growth in Southern China. IEEE Geosci. Remote Sens. Lett. 4:431-435. crossref(new window)

5.
Gao, B.C. and A.F.H. Goetz. 1995. Retrieval of equivalent water thickness and information related to biochemical components of vegetation canopies from AVIRIS data. Remote Sens. Environ. 52:155-162. crossref(new window)

6.
Hong, S.Y., S.H. Hong, and S.K. Rim. 2000. Relationship between Radarsat backscattering coefficient and rice growth. Korean J. Remote Sens. 16(2):109-116.

7.
Jackson, T.J. and T.J. Schmugge. 1991. Vegetation effects on the passive microwave emission of soils. Remote Sens. Environ. 36:203-212. crossref(new window)

8.
Kim, Y.H., S.Y. Hong, and H.Y. Lee. 2009. Estimation of paddy rice growth parameters using L, C, X-bands polarimetric scatterometer. Korean J. Remote Sens. 25:31-44.

9.
Kim, Y.H., T.J. Jackson, R. Bindlish, H.Y. Lee, and S.Y. Hong. 2012. Radar vegetation index for estimating the vegetation water content of rice and soybean. IEEE Geosci. Remote Sens. Lett. 9(4):564-568. crossref(new window)

10.
Kurosu, T., M. Fujita, and K. Chiba. 1997. The identification of rice fields using multi-temporal ERS-1 C-band SAR data. Int. J. Remote Sens. 18(2):953-965.

11.
Le Toan, T., H. Laur, E. Mougin, and A. Lopes. 1989. Multitemporal and dual-polarization observations of agricultural vegetation covers by X-band SAR images. IEEE Trans. Geosci. Remote Sens. 27(6):709-718. crossref(new window)

12.
Le Toan, T., F. Ribbes, L.F. Wang, N. Floury, K.H. Ding, J.A. Kong, M. Fujita, and T. Kurosu. 1997. Rice crop mapping and monitoring using ERS-1 data based on experiment and modeling results. IEEE Trans. Geosci. Remote Sens. 35:41-56. crossref(new window)

13.
Yilmaz, M.T., E.R. Hunt, L.D. Goins, S.L. Ustin, V.C. Vandrbilt, and T.J. Jackson. 2008. Vegetation water content during SMEX04 from ground data and Landsat 5 Thematic Mapper imagery. Remote Sens. Environ. 112:350-362. crossref(new window)