Paper
12 October 2007 Rice polarization scattering characteristics and paddyfield recognition
Shuanghe Shen, Pingping Zhang, Bingbai Li
Author Affiliations +
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.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Shuanghe Shen, Pingping Zhang, and Bingbai Li "Rice polarization scattering characteristics and paddyfield recognition", Proc. SPIE 6761, Optics for Natural Resources, Agriculture, and Foods II, 67610F (12 October 2007); https://doi.org/10.1117/12.730624
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KEYWORDS
Polarization

Scattering

Data modeling

Radar

Image classification

Remote sensing

Satellites

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