Polarimetric Backscattering Coefficients of Flooded Rice Fields at L- and C-Bands: Measurements, Modeling, and Data Analysis

Oh, Yisok; Hong, Su Young; Kim, Yun-Jin; Hong, Jin-Young; Kim, Yi-Hyun

doi:10.1109/tgrs.2009.2014053

Cited by 49 publications

(8 citation statements)

References 7 publications

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“…We found that Sentinel-1 images with a high temporal resolution were well suited to monitor and capture the different stages of rice based on evidence from previous literature and observations made in this study. The penetration capability of C-band is particularly advantageous to retrieve information not only from the canopy but also from the underlying soil and water surface before the saturation effect due to full canopy closure (McNairn and Brisco, 2004;Oh et al, 2009) which enables more factors to be considered when interpreting the backscatter signatures at the early rice growth stages. Additionally, the proposed method of relating backscatter to the crop calendar is able to identify differences in backscatter during the entire cropping season in areas with diverse crop calendars.…”

Section: Temporal Backscatter Signatures Of Tp and Wds Ricementioning

confidence: 99%

“…The wider adoption of DS (either dry or wet seeding) can have implications for many remote sensing-based rice detection techniques. Most rice detection algorithms that use either SAR data (Choudhury and Chakraborty, 2006;Oh et al, 2009;Nelson et al, 2014) or a combination of vegetation and water indices in optical data (Xiao et al, 2002(Xiao et al, , 2006Nguyen et al, 2012;Boschetti et al, 2014) depend on a strong water signal during the early season, which is typical of transplanted rice. Direct seeding has a shorter period of flooding and a lower water level in the early season (Bouman et al, 2007;Bouvet and Le Toan, 2011;Kumar and Ladha, 2011) that can result in a weaker water V.N.…”

Section: Limitations Potential Applications and Recommendationsmentioning

confidence: 99%

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Discriminating transplanted and direct seeded rice using Sentinel-1 intensity data

Fikriyah

Darvishzadeh

Khan

et al. 2019

International Journal of Applied Earth Observation and Geoinfor

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A B S T R A C TImproved rice crop and water management practices that make the sustainable use of resources more efficient are important interventions towards a more food secure future. A remote sensing-based detection of different rice crop management practices, such as crop establishment method (transplanting or direct seeding), can provide timely and cost-effective information on which practices are used as well as their spread and change over time as different management practices are adopted. Establishment method cannot be easily observed since it is a rapid event, but it can be inferred from resulting observable differences in land surface characteristics (i.e. field condition) and crop development (i.e. delayed or prolonged stages) that take place over a longer time. To examine this, we used temporal information from Synthetic Aperture Radar (SAR) backscatter to detect differences in field condition and rice growth, then related those to crop establishment practices in Nueva Ecija (Philippines). Specifically, multi-temporal, dual-polarised, C-band backscatter data at 20m spatial resolution was acquired from Sentinel-1A every 12 days over the study area during the dry season, from November 2016 to May 2017. Farmer surveys and field observations were conducted in four selected municipalities across the study area in 2017, providing information on field boundaries and crop management practices for 61 fields. Mean backscatter values were generated per rice field per SAR acquisition date. We matched the SAR acquisition dates with the reported dates for land management activities and with the estimated dates for when the crop growth stages occurred. The Mann-Whitney U test was used to identify significant differences in backscatter between the two practices during the land management activities and crop growth stages. Significant differences in cross-polarised, co-polarised and band ratio backscatter values were observed in the early growing season, specifically during land preparation, crop establishment, rice tillering and stem elongation. These findings indicate the possibility to discriminate crop establishment methods by SAR at those stages, suggesting that there is more opportunity for discrimination than has been presented in previous studies. Further testing in a wider range of environments, seasons, and management practices should be done to determine how reliably rice establishment methods can be detected. The increased use of dry and wet direct seeding has implications for many remote sensing-based rice detection methods that rely on a strong water signal (typical of transplanting) during the early season. different management approaches to create favourable rice-growing https://doi.

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Section: Temporal Backscatter Signatures Of Tp and Wds Ricementioning

confidence: 99%

Section: Limitations Potential Applications and Recommendationsmentioning

confidence: 99%

Discriminating transplanted and direct seeded rice using Sentinel-1 intensity data

Fikriyah

Darvishzadeh

Khan

et al. 2019

International Journal of Applied Earth Observation and Geoinfor

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“…C-band and L-band show promising capabilities in LAI or fAPAR estimates for rice growth (Inoue et al, 2014) and paddy rice field mapping (Kurosu et al, 1995;Torbick et al, 2011). Furthermore, Wang et al (2009) andYisok et al (2009) also found the L-band HH backscatter was more sensitive to rice structural variation and growth than the VV backscatter. Microwave data has been used for paddy rice mapping for a long time and more details were described in Section 4.…”

Section: Polarimetric Features Of Paddy Rice Fieldsmentioning

confidence: 99%

Evolution of regional to global paddy rice mapping methods: A review

Dong

Xiao

2016

ISPRS Journal of Photogrammetry and Remote Sensing

219

127

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a b s t r a c tPaddy rice agriculture plays an important role in various environmental issues including food security, water use, climate change, and disease transmission. However, regional and global paddy rice maps are surprisingly scarce and sporadic despite numerous efforts in paddy rice mapping algorithms and applications. With the increasing need for regional to global paddy rice maps, this paper reviewed the existing paddy rice mapping methods from the literatures ranging from the 1980s to 2015. In particular, we illustrated the evolution of these paddy rice mapping efforts, looking specifically at the future trajectory of paddy rice mapping methodologies. The biophysical features and growth phases of paddy rice were analyzed first, and feature selections for paddy rice mapping were analyzed from spectral, polarimetric, temporal, spatial, and textural aspects. We sorted out paddy rice mapping algorithms into four categories: (1) Reflectance data and image statistic-based approaches, (2) vegetation index (VI) data and enhanced image statistic-based approaches, (3) VI or RADAR backscatter-based temporal analysis approaches, and (4) phenology-based approaches through remote sensing recognition of key growth phases. The phenology-based approaches using unique features of paddy rice (e.g., transplanting) for mapping have been increasingly used in paddy rice mapping. Current applications of these phenologybased approaches generally use coarse resolution MODIS data, which involves mixed pixel issues in Asia where smallholders comprise the majority of paddy rice agriculture. The free release of Landsat archive data and the launch of Landsat 8 and Sentinel-2 are providing unprecedented opportunities to map paddy rice in fragmented landscapes with higher spatial resolution. Based on the literature review, we discussed a series of issues for large scale operational paddy rice mapping. Ó

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“…However, as Figure 7 shows, in mountainous areas with rugged terrain, the local incidence angle at the scatterer is no longer adequately approximated by the value of radar viewing angle. The backscattering coefficients for the VH polarization was simulated by adopting the crosspolarized ratio function that was previously proposed and reported by Oh et al [58][59][60]. After the VH-polarimetric backscattering coefficients had been computed, the numerical relation between cross-polarimetric backscattering coefficients and R s were computed as:…”

Section: The Local Incidence Angle Inversion By the Iacmmentioning

confidence: 99%

An Improved Approach for Soil Moisture Estimation in Gully Fields of the Loess Plateau Using Sentinel-1A Radar Images

et al. 2019

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As an essential ecological parameter, soil moisture is important for understanding the water exchange between the land surface and the atmosphere, especially in the Loess Plateau (China). Although Synthetic Aperture Radar (SAR) images can be used for soil moisture retrieval, it is still a challenge to mitigate the impacts of complex terrain over hilly areas. Therefore, the objective of this paper is to propose an improved approach for soil moisture estimation in gully fields based on the joint use of the Advanced Integral Equation Model (AIEM) and the Incidence Angle Correction Model (IACM) from Sentinel-1A observations. AIEM is utilized to build a simulation database of microwave backscattering coefficients from various radar parameters and surface parameters, which is the data basis for the retrieval modeling. IACM is proposed to correct the deviation between the local incidence angle at the scatterer and the radar viewing angle. The study area is located in the Loess Plateau of China, where the main land cover is mostly bare land and the terrain is complex. The Sentinel-1A SAR data in C-band with dual polarization acquired on October 19th, 2017 was adopted to extract the VV&VH polarimetric backscattering coefficients. The in situ measurements of soil moisture were collected on the same day of the SAR acquisition, for evaluating the accuracy of the SAR-derived soil moisture. The results showed that, firstly, the estimated soil moisture with volumetric content between 0% and 20% was in the majority. Subsequently, both the RMSE of estimation values (0.963%) and the standard deviation of absolute errors (0.957%) demonstrated a good accuracy of the improved approach. Moreover, the evaluation of IACM confirmed that the improved approach coupling IACM and AIEM was more efficient than employing AIEM solely. In conclusion, the proposed approach has a strong ability to estimate the soil moisture in the gully fields of the Loess Plateau from Sentinel-1A data.

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Polarimetric Backscattering Coefficients of Flooded Rice Fields at L- and C-Bands: Measurements, Modeling, and Data Analysis

Cited by 49 publications

References 7 publications

Discriminating transplanted and direct seeded rice using Sentinel-1 intensity data

Discriminating transplanted and direct seeded rice using Sentinel-1 intensity data

Evolution of regional to global paddy rice mapping methods: A review

An Improved Approach for Soil Moisture Estimation in Gully Fields of the Loess Plateau Using Sentinel-1A Radar Images

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