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Research Article Open access CC BY 4.0

Area Assessment for Rice Crop in Thiruvarur District Assimilating Sentinel 1A Satellite Data

S. Satheesh, S. Pazhanivelan, R. Kumaraperumal, S. Radhamani, K. P. Ragunath, N. S. Sudarmanian

International Journal of Environment and Climate Change · pp. 1270–1278 · Published 28 Jun 2022

10.9734/ijecc/2022/v12i1030924

Abstract

This study proposes an effective method to map rice area using the Sentinel-1A SAR (Synthetic Aperture Radar) time series data over the Thiruvarur district during samba 2021. Fully automated MAPscape-Rice software was used to pre-process the SAR data and extraction of multi-temporal features. The rice-growing area was estimated based on the extracted multi-temporal features and statistics were derived at district and block level in Thiruvarur district. The study area registered a total rice area of 127027 ha; among the blocks, the Kottur block recorded the largest area of 16615 ha and the lowest area of 6865 ha was recorded in the Thiruvarur block. The estimated rice area was validated with the observed rice area in the Thiruvarur district using accuracy assessment, which indicates an overall accuracy of 92.0 per cent and 0.84 kappa co-efficient.

Rice area Sentinel 1A Synthetic Aperture Radar (SAR) Validation Accuracy assessment

References (12)

  1. 1 Combining agricultural crop models and satellite observations: From field to regional scales [DOI]
  2. 2 Remote sensing of rice crop areas [DOI]
  3. 3 Estimation of cropped area and grain yield of rice using remote sensing data [DOI]
  4. 4 Using NOAA AVHRR and Landsat TM to estimate rice area year-by-year [DOI]
  5. 5 Monitoring Rice Phenology Based on Backscattering Characteristics of Multi-Temporal RADARSAT-2 Datasets [DOI]
  6. 6 Evaluation of the impact of climatic trends and variability in rice–wheat system productivity using Cropping System Model DSSAT over the Indo-Gangetic Plains of India [DOI]
  7. 7 Air temperature variations and rice productivity in Bangladesh: a comparative study of the performance of the YIELD and the CERES-Rice models [DOI]
  8. 8 An operational remote sensing based service for rice production estimation at national scale
  9. 9 In-season early mapping of rice area and flooding dynamics from optical and SAR satellite data [DOI]
  10. 10 ESTIMATION OF COTTON AND MAIZE CROP AREA IN PERAMBALUR DISTRICT OF TAMIL NADU USING MULTI-DATE SENTINEL-1A SAR DATA [DOI]
  11. 11 Improved ground sampling and crop yield estimation using satellite data [DOI]
  12. 12 Mapping rice areas in mindanao using the first images from Sentinel-1A: The PRISM project experience

Cited by 7

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Ramamoorthy Tamilmounika, Dhanaraju Muthumanickam, Sellaperumal Pazhanivelan · Environment Conservation Journal · 2025

Machine learning‐based spatial rice yield estimation by assimilation of SAR and optical remote sensing products

S Satheesh, Sellaperumal Pazhanivelan, D Suresh Kumar · Singapore Journal of Tropical Geography · 2025

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