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Proceedings Paper

Rice polarization scattering characteristics and paddyfield recognition
Author(s): Shuanghe Shen; Pingping Zhang; Bingbai Li
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Paper Abstract

Paddy rice is a staple food in China and it's growth monitoring, acreage extraction and yield estimate are of far reaching importance. It is difficult to apply conventional remote sensing technique for obtaining precise information on paddy planting and growth, for rice bowls are mostly distributed over rainy regions in China. The radar image is unlimited by cloud, rain and fog, and could proceed all weather operation and obtain more stable data, therefore it could be used for paddy monitoring. Making use of Envisat's ASAR data and NOAA data in 2004, paddy's backward-scattering characteristics with different polarizations were studied in this paper. To combine multi-temporal radar data with one view ETM image, paddyfield of experimental area in Hongze of Jiangsu Province was classified. Results show that 1) characteristics of paddy's hh and vv polarizations vary from stage to stage and vv polarization is more sensitive. The polarization ratio hh / vv of paddy during metaphase is apparently higher than other objects'. 2) paddy's polarization ratio hh / vv and growth vigor closely relate to each other , thereof two empirical time-domain models of backward- scattering were established, wherewith to estimate number of days after transplanting and growing season. 3) hh and ratio hh / vv are both well correlated with NDVI. 4) hh polarization data could be used for information extraction of towns and water bodies, and the hh / vv image in metaphase for partition of paddy from other objects. The recognition accuracy being ninety percent over, multi-temporal and -polarization radarsat data are of predominance and potential for paddy growth and/or acreage monitoring.

Paper Details

Date Published: 12 October 2007
PDF: 8 pages
Proc. SPIE 6761, Optics for Natural Resources, Agriculture, and Foods II, 67610F (12 October 2007); doi: 10.1117/12.730624
Show Author Affiliations
Shuanghe Shen, Nanjing Univ. of Information Science and Technology (China)
Pingping Zhang, Hubei Meteorological Bureau (China)
Bingbai Li, Jiangsu Academy of Agricultural Sciences (China)


Published in SPIE Proceedings Vol. 6761:
Optics for Natural Resources, Agriculture, and Foods II
Yud-Ren Chen; George E. Meyer; Shu-I Tu, Editor(s)

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