气候变化领域集成服务门户(CCPortal): Assessment of rice growth conditions in a semi-arid region of India using the Generalized Radar Vegetation Index derived from RADARSAT-2 polarimetric SAR data

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DOI	10.1016/j.rse.2019.111561
	Assessment of rice growth conditions in a semi-arid region of India using the Generalized Radar Vegetation Index derived from RADARSAT-2 polarimetric SAR data
	Mandal D.; Kumar V.; Ratha D.; Lopez-Sanchez J.M.; Bhattacharya A.; McNairn H.; Rao Y.S.; Ramana K.V.
发表日期	2020
ISSN	00344257
卷号	237
英文摘要	Rice growth monitoring using Synthetic Aperture Radar (SAR) is recognized as a promising approach for tracking the development of this important crop. Accurate spatio-temporal information of rice inventories is required for water resource management, production risk occurrence, and yield forecasting. This research investigates the potential of the proposed Generalized volume scattering model based Radar Vegetation Index (GRVI) for monitoring rice growth at different phenological stages. The GRVI is derived using the concept of a geodesic distance (GD) between Kennaugh matrices projected on a unit sphere. We utilized this concept of GD to quantify a similarity measure between the observed Kennaugh matrix (representation of observed Polarimetric SAR information) and the Kennaugh matrix of a generalized volume scattering model (a realization of scattering media). The similarity measure is then modulated with a factor estimated from the ratio of the minimum to the maximum GD between the observed Kennaugh matrix and the set of elementary targets: trihedral, cylinder, dihedral, and narrow dihedral. In this work, we utilize a time series of C-band quad-pol RADARSAT-2 observations over a semi-arid region in Vijayawada, India. Among the several rice cultivation practices adopted in this region, we analyze the growth stages of direct seeded rice (DSR) and conventional tansplanted rice (TR) with the GRVI and crop biophysical parameters viz., Plant Area Index – PAI. The GRVI is compared for both rice types against the Radar Vegetation Index (RVI) proposed by Kim and van Zyl. A temporal analysis of the GRVI with crop biophysical parameters at different phenological stages confirms its trend with the plant growth stages. Also, the linear regression analysis confirms that the GRVI outperforms RVI with significant correlations with PAI (r ≥ 0.83 for both DSR and TR). In addition, PAI estimations from GRVI show promising retrieval accuracy with Root Mean Square Error (RMSE) <1.05m2 m−2 and Mean Absolute Error (MAE) <0.85m2 m−2. © 2019 Elsevier Inc.
英文关键词	Direct seeded rice; GRVI; Rice; RVI; SAR polarimetry
语种	英语
scopus关键词	Arid regions; Crops; Cultivation; Information management; Matrix algebra; Mean square error; Polarimeters; Regression analysis; Vegetation; Water management; Biophysical parameters; Direct seeded rice; GRVI; Rice; Root mean square errors; SAR polarimetry; Spatiotemporal information; Waterresource management; Synthetic aperture radar; accuracy assessment; assessment method; environmental monitoring; estimation method; growth; numerical model; phenology; radar altimetry; RADARSAT; rice; satellite data; semiarid region; spatiotemporal analysis; synthetic aperture radar; vegetation index; Andhra Pradesh; India; Vijayawada
来源期刊	Remote Sensing of Environment
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/179534
作者单位	Microwave Remote Sensing Lab, Centre of Studies in Resources Engineering, Indian Institute of Technology Bombay, Mumbai, India; University Institute for Computing Research, University of Alicante, Spain; Ottawa Research and Development Centre, Agriculture and Agri-Food Canada, Canada, Canada; Agriculture Sciences and Application Group, National Remote Sensing Centre, Indian Space Research Organisation (ISRO), India
推荐引用方式 GB/T 7714	Mandal D.,Kumar V.,Ratha D.,et al. Assessment of rice growth conditions in a semi-arid region of India using the Generalized Radar Vegetation Index derived from RADARSAT-2 polarimetric SAR data[J],2020,237.
APA	Mandal D..,Kumar V..,Ratha D..,Lopez-Sanchez J.M..,Bhattacharya A..,...&Ramana K.V..(2020).Assessment of rice growth conditions in a semi-arid region of India using the Generalized Radar Vegetation Index derived from RADARSAT-2 polarimetric SAR data.Remote Sensing of Environment,237.
MLA	Mandal D.,et al."Assessment of rice growth conditions in a semi-arid region of India using the Generalized Radar Vegetation Index derived from RADARSAT-2 polarimetric SAR data".Remote Sensing of Environment 237(2020).