Browsing by Author "Sasmita Chaurasia"

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Assessment of SCATSAT-1 Backscattering by Using the State-of-the-Art Water Cloud Model
(Springer, 2020) Ujjwal Singh; Prashant K. Srivastava; Dharmendra Kumar Pandey; Sasmita Chaurasia
The SCATSAT-1 satellite data can be used for various applications in the field of agriculture. The main aim of the study is to investigate the water cloud model (WCM) for backscattering simulation by using the field-measured soil moisture in order to validate the SCATSAT-1 measured backscattering. WCM requires various input datasets for simulation of backscattering such as vegetation parameters A and B and soil parameters C and D, which can be estimated by Non-linear least square fitting method by using with experimental dataset. The results showed that the simulated WCM values are well correlated with the backscattering of SCATSAT-1 satellite data. However, it can be further improved when each parameter of WCM is generated by using the ground-based measurements. In this study, some progress has been made toward backscattering simulations using the SCATSAT-1; however, it can be further refined with the advancement in the retrieval algorithms and sensor sensitivity. © Springer Nature Singapore Pte Ltd. 2020.
Crop phenology and soil moisture applications of SCATSAT-1
(Indian Academy of Sciences, 2019) Nilima R. Chaube; Sasmita Chaurasia; Rojalin Tripathy; Dharmendra Kumar Pandey; Arundhati Misra; B.K. Bhattacharya; Prakash Chauhan; Kiran Yarakulla; G.D. Bairagi; Prashant Kumar Srivastava; Preeti Teheliani; S.S. Ray
SCATSAT-1 measures the backscattering coefficient over land surfaces, which is a function of vegetation structure, surface roughness, soil moisture content, incidence angle and dielectric properties of vegetation. Scatterometer image reconstruction techniques provide fine resolution data to explore the emerging applications over land by using ambiguous backscatter from land. In this paper, 2 km resolution products of ISRO's scatterometer SCATSAT-1 are exploited for land target detection, rice crop phenology stages detection for kharif and rabi seasons and estimation of relative soil moisture over parts of India. Temporal and spatial backscatter changes are due to seasonal and changes in Land Use Land Cover. Crop phenology stages such as transplanting, maximum tillering, panicle emergence and physiological maturity stages are identified by analysing SCATSAT-1 time series along with NDVI and findings are supported by appropriate ground truth observations and crop cutting experiment (CCE) data. The relative soil moisture change detection is validated with in situ ground truth measurements using Hydraprobe, carried for SCATSAT-1 ascending and descending passes. © 2019 Current Science Association, Bengaluru.
ScatSat-1 Leaf Area Index Product: Models Comparison, Development, and Validation over Cropland
(Institute of Electrical and Electronics Engineers Inc., 2020) Ujjwal Singh; Prashant K. Srivastava; Dharmendra Kumar Pandey; Sasmita Chaurasia; Dileep Kumar Gupta; Sumit Kumar Chaudhary; Rajendra Prasad; A.S. Raghubanshi
The leaf area index (LAI) is a crucial parameter that governs the physical and biophysical processes of plant canopies and acts as an input variable in land surface and soil moisture modeling. The ScatSat-1 is the latest microwave Ku-band scatterometer mission of Indian Space Research Organization (ISRO), provides data at a higher temporal and spatial resolution for various applications. Due to its all-weather operational capability, it could be used as an alternative to the optical/IR sensors for the LAI estimation. In the technical literature domain, no testing has been done to estimate the LAI using ScatSat-1 scatterometer data. Therefore, the objective of this study is to retrieve the LAI using the ScatSat-1 backscattering by modifications of two different models viz. water cloud model (WCM) and the recently developed Oveisgharan et al. model and compared against the PROBA-V, MODIS, and ground-based LAI products. To assess the performance of these models, coefficient of determination (R2), root-mean-squared error (RMSE) and bias are computed. For Oveisgharan et al., the values of R2, RMSE and bias were obtained as 0.87, 0.57 m2m-2, and 0.05 m2m-2 respectively, whereas for WCM model, the values were found as 0.82, 0.67 m2m-2, and 0.32 m2m-2 respectively. This investigation showed that the modifications in Oveisgharan et al. model provide marginally better results in the retrieval of LAI using ScatSat-1 data than the WCM model. The models' limitation may be less serious for crop management studies because the majority of crops attains its maturity at LAI values less than 6 m2/m2. © 2004-2012 IEEE.