Assessing Methane Emissions from Rice Fields in Large Irrigation Projects Using Satellite-Derived Land Surface Temperature and Agronomic Flooding: A Spatial Analysis

Sellaperumal Pazhanivelan (), N. S. Sudarmanian, Vellingiri Geethalakshmi, Murugesan Deiveegan, Kaliaperumal Ragunath, A. P. Sivamurugan and P. Shanmugapriya
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Sellaperumal Pazhanivelan: Centre for Water and Geospatial Studies, Tamil Nadu Agricultural University, Coimbatore 641003, India
N. S. Sudarmanian: Department of Remote Sensing and GIS, Tamil Nadu Agricultural University, Coimbatore 641003, India
Vellingiri Geethalakshmi: Centre for Water and Geospatial Studies, Tamil Nadu Agricultural University, Coimbatore 641003, India
Murugesan Deiveegan: International Rice Research Institute, South Asia Regional Centre, Varanasi 221106, India
Kaliaperumal Ragunath: Centre for Water and Geospatial Studies, Tamil Nadu Agricultural University, Coimbatore 641003, India
A. P. Sivamurugan: Centre for Water and Geospatial Studies, Tamil Nadu Agricultural University, Coimbatore 641003, India
P. Shanmugapriya: Centre for Water and Geospatial Studies, Tamil Nadu Agricultural University, Coimbatore 641003, India

Agriculture, 2024, vol. 14, issue 3, 1-23

Abstract: Synthetic aperture radar (SAR) imagery, notably Sentinel-1A’s C-band, VV, and VH polarized SAR, has emerged as a crucial tool for mapping rice fields, especially in regions where cloud cover hinders optical imagery. Employing multi-temporal characteristics, SAR data were regularly collected and parameterized using MAPscape-Rice software, which integrates a fully automated processing chain to convert the data into terrain-geocoded σ° values. This facilitated the generation of rice area maps through a rule-based classifier approach, with classification accuracies ranging from 88.5 to 91.5 and 87.5 percent in 2017, 2018, and 2022, respectively. To estimate methane emissions, IPCC (37.13 kg/ha/season, 42.10 kg/ha/season, 43.19 kg/ha/season) and LST (36.05 kg/ha/season, 41.44 kg/ha/season, 38.07 kg/ha/season) factors were utilized in 2017, 2018 and 2022. Total methane emissions were recorded as 19.813 Gg, 20.661 Gg, and 25.72 Gg using IPCC and 19.155 Gg, 20.373 Gg, and 22.76 Gg using LST factors in 2017, 2018 and 2022. Overall accuracy in methane emission estimation, assessed against field observations, ranged from (IPCC) 85.71, 91.32, and 80.25 percent to (LST) 83.69, 91.43, and 84.69 percent for the years 2017, 2018 and 2022, respectively, confirming the efficacy of remote sensing in greenhouse gas monitoring and its potential for evaluating the impact of large-scale water management strategies on methane emissions and carbon credit-based ecosystem services at regional or national levels.

Keywords: IPCC; LST; methane emission; rice; Sentinel 1A; synthetic aperture radar (SAR) (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2024
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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