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20181
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Subject: Agricultural Meteorology × Author: Bhatt, Chetan Kumar × End date: 2024 × Type: Thesis ×
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    ThesisItemOpen Access
    Retrieval of crop biophysical parameters and monitoring of rice using SAR images
    (G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2018-07) Bhatt, Chetan Kumar; Nain, Ajeet Singh
    Udham Singh Nagar is one of major rice producing area of Uttarakhand state, and falls in Tarai region. Sentinel-1A satellite launched in 2014 as part of the European Union's Copernicus program provides Synthetic aperture radar (SAR) data. SAR images are independent of weather conditions and solar illumination and allow observations of different features of earth. The basic goal behind the present study was to apply new generation Sentinel-1A data with dual polarization (VH and VV) to rice cropping system mapping and monitoring with the short revisit period of Sentinel-1A satellite. SAR data were pre-processed by applying European Space Agency’s Sentinel Application Platform (SNAP). The SAR images classified with a Support Vector Machine (SVM) algorithm provided in ENVI- 4.8 produced the accurate LULC map, which shows that rice area in Udham Singh Nagar covers 108,095 ha area. The overall classification accuracy of 92.88% and a Kappa coefficient of 0.9 were obtained. The relationship between Sentinel-1A backscattering coefficients (𝜎0) or their ratio and rice biophysical parameters were analyzed. The regression models were developed between biophysical parameters and (𝜎0𝑉𝑉/𝜎0𝑉𝐻). The value of coefficient of determination for LAI, fPar, crop height, biomass and water content were found 0.53, 0.47, 0.50, 0.63, 0.34 respectively which exhibit that these biophysical parameters are significantly, consistently and positively correlated with the VV and VH 𝜎0 ratio (𝜎0𝑉𝑉/𝜎0𝑉𝐻) throughout all growth stages. Two approaches (crop simulation model and SAR coupled model and statistical model) have been used to predict the field level rice yield and district level rice yield. The biases (RMSE) of coupled model and statistical model were recorded as 7.61% and 9.12%, respectively. The average district yield generated from these two models were 3190 and 3344 kg/ha respectively which is quite close to five years average district yield of 3160 kg/ha. However, estimates provided by coupled model are more accurate than statistical models. Therefore, coupled model could be a good option to predict the plot level and regional yield of rice. On the basis of results obtained it can be concluded that Sentinel-1A SAR data has great potential for mapping of rice, estimation of biophysical parameters and timely rice growth monitoring with the ability to forecast the yield of rice crop. The prediction of rice crop is an important step that could be used to assist farmers and policy makers by providing in-season estimates of the rice yield and production.The information could be used for better planning of the resources.