Abstract

Abstract. A research study was conducted during Rabi 2016 (Samba season) to estimate rice area using SAR data in Tiruvarur district of Tamil Nadu. Multi temporal Sentinel 1A satellite data with VV and VH polarization at 20 m spatial resolution was acquired between September 2016 and January 2017 at 12 days interval and processed using rule-based Parameterized classification in MAPscape-RICE software. Continuous monitoring for crop parameters and validation exercise was done for accuracy assessment. Spectral dB curve of rice was generated and the dB values ranged from −12.76 to −9.95 for VV and from −19.25 to −15.15 for VH polarization with an average primary variation of 1.3 and 2.5 dB respectively. Start of Season (SOS) map was derived from satellite data showing rice emergence dates for the cropping season. A total rice area of 106773 ha was estimated in Tiruvarur district using VV polarization with an overall accuracy of 79.5% and 0.59 kappa index, while in VH polarization, the rice area was estimated to be 91007 ha with 82.1% over all accuracy and 0.64 kappa index. The lesser accuracy in VV polarization was due to underestimate of direct seeded rice area and in VH polarization, it was due to underestimate in Transplanted rice area. The VV and VH rice area maps were then integrated to derive a VV-VH rice area map in MAPscape-RICE software and it recorded a total rice area of 124551 ha with an accuracy of 91.5% and 0.83-kappa index.

Highlights

  • Agricultural resources are among the most important renewable, dynamic natural resources

  • The district occupies an area of 2161 km2

  • The multi-temporal stack of terrain-geocoded σ° images of Sentinel 1A acquired from September, 2016 to January, 2017 was given as input to a rule-based rice detection algorithm in MAPscape-RICE software, which was an proprietary software with the capability of performing sequential Synthetic Aperture Radar (SAR) data processing

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Summary

Introduction

Agricultural resources are among the most important renewable, dynamic natural resources. Remote sensing data provide timely, accurate and objective estimation of crop identification, crop monitoring, acreage and yield estimation. Since the 1980’s, optical remote sensing has been widely used to identify various crops, optical images are not often available in the key growth period of crops, owing to the cloudy and rainy weather. It has a negative effect on the accuracy and timeliness of crop area monitoring. As a new technology with an advantage of all weather, all-time, high resolution and wide coverage, Synthetic Aperture Radar (SAR) has been widely applied in agricultural condition monitoring which provides a strong complement and support for crop identification in data and technology aspect. The potential of cross polarization in combination with the single polarization was attempted for rice area

METHODOLOGY
RESULTS
12 Dec 2016
Rice area
Full Text
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