Crop acreage estimation using ERS-1 SAR data

Premalatha, M.; Rao, P. Parthasarathy

doi:10.1007/bf03024775

Cited by 20 publications

(6 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The approach takes advantage of the strong temporal variation of radar backscattering from paddy fields. Premlatha and Rao (1994) and Patel et al (1995) have reported that preliminary analysis of ERS-1 SAR data has shown good results for rice crop identification. Chakraborty et al (1997) and Panigrahy et al (1999) used SAR data to discriminate rice crop grown under different cultural practices and also to identify rice crops grown in different parts of India.…”

Section: Introductionmentioning

confidence: 96%

SAR signature investigation of rice crop using RADARSAT data

Choudhury

Chakraborty

2006

International Journal of Remote Sensing

View full text Add to dashboard Cite

The current study investigates the potential of multi-temporal RADARSAT ScanSAR Narrow Beam B (SCNB) data to monitor rice crop growth and condition where special emphasis was given to the signature analysis of the crop. The study area is located in the Baleshwar and Bhadrak districts of Orissa. The temporal variations of radar backscatter of all land-cover classes were analysed as a function of time. The analysis of the Synthetic Aperture Radar (SAR) backscatter coefficient (s 0 ) of rice crop shows significant temporal behaviour and a large dynamic range during its growth period, which is due to the interaction of microwave radiation with the crop canopy, increasing from the transplanting stage to the reproductive stage. This temporal variation of SAR backscatter clearly differentiates rice fields from other land-cover classes.Separability studies among different class pairs carried out using t-test and Bhattacharya distance show that all the rice classes are separable from each other except the early rice, which was mixed with far sides of hills and shadow. Knowledge-based decision rule classifier based on the temporal evaluation of SAR backscatter was attempted to classify rice and non-rice areas, and achieved more than 98% accuracy in the case of rice class. The results are promising and confirm the possibility of operational use of RADARSAT data for rice crop growth monitoring.

show abstract

Section: Introductionmentioning

confidence: 96%

SAR signature investigation of rice crop using RADARSAT data

Choudhury

Chakraborty

2006

International Journal of Remote Sensing

View full text Add to dashboard Cite

show abstract

“…The backscatter images, acquired by the C-band SAR onboard ERS-1 with a repeat time of 35 days, were used in numerous SAR-based multi-temporal backscatter analyses for rice mapping case studies in Thailand [22], Indonesia [21], Japan [21,23,24], Vietnam [29], Canada [30,31] and India [25,26,32,33]. Methods developed for ERS-1 SAR data have been advanced and successfully transferred to RADARSAT-1 acquisitions at C-band with horizontal co-polarization and a 24-day repeat cycle [19,[34][35][36][37][38][39].…”

mentioning

confidence: 99%

Mapping Rice Seasonality in the Mekong Delta with Multi-Year Envisat ASAR WSM Data

et al. 2015

View full text Add to dashboard Cite

Abstract:Rice is the most important food crop in Asia, and the timely mapping and monitoring of paddy rice fields subsequently emerged as an important task in the context of food security and modelling of greenhouse gas emissions. Rice growth has a distinct influence on Synthetic Aperture Radar (SAR) backscatter images, and time-series analysis of C-band images has been successfully employed to map rice fields. The poor data availability on regional scales is a major drawback of this method. We devised an approach to classify paddy rice with the use of all available Envisat ASAR WSM (Advanced Synthetic Aperture Radar Wide Swath Mode) data for our study area, the Mekong Delta in Vietnam. We used regression-based incidence angle normalization and temporal averaging to combine acquisitions from multiple tracks and years. A crop phenology-based classifier has been applied to this time series to detect single-, double-and triple-cropped rice areas (one to three harvests per year), as well as dates and lengths of growing seasons. Our classification has an overall accuracy of 85.3% and a kappa coefficient of 0.74 compared to a reference dataset and correlates highly with official rice area statistics at the provincial level (R² of 0.98). SAR-based time-series analysis allows accurate mapping and monitoring of rice areas even under adverse atmospheric conditions.

show abstract

“…Preliminary analysis of ERS-1 SAR data for identification of different field crops showed promising results for rice, wheat and rape seed/ mustard crops (ESA, 1995). Studies using ERS-1 SAR data over different agroclimatic regions of India for rice indicated it is essential to have multi-temporal data for such studies , Patel et al 1994, 1995, Premlatha and Rao 1994, Rao et al 1995. In this study, attempts have been made to evaluate the utility of temporal ERS SAR data for classification and acreage estimation of field crops.…”

Section: Introductionmentioning

confidence: 98%

Evaluation of ERS‐1 SAR Data for Agricultural Crop Monitoring in India

Chakraborty¹,

Parihar²,

Manjunath³

et al. 2002

Geocarto International

View full text Add to dashboard Cite

Multi-temporal ERS-1 SAR data acquired over a large agricultural region in West Bengal was used to classify kharif crops like rice, jute and sugarcane. Rice crop grown under lowland management practice showed a temporal characteristic. The dynamic range of backscatter was highest for this crop in temporal SAR data. This was used to classify rice using temporal SAR data. Such temporal character was not observed for the other study crops, which may be due to the difference in cultivation practice and crop calendar. Significant increase in backscatter from the ploughed fields was used to derive information on onset and duration of land preparations. Synergistic use of optical remote sensing data and SAR data increased the separability of rice crop from homesteads and permanent vegetation classes.

show abstract

Crop acreage estimation using ERS-1 SAR data

Cited by 20 publications

References 6 publications

SAR signature investigation of rice crop using RADARSAT data

SAR signature investigation of rice crop using RADARSAT data

Mapping Rice Seasonality in the Mekong Delta with Multi-Year Envisat ASAR WSM Data

Evaluation of ERS‐1 SAR Data for Agricultural Crop Monitoring in India

Contact Info

Product

Resources

About