气候变化领域集成服务门户(CCPortal): Estimation of crop angle of inclination for lodged wheat using multi-sensor SAR data

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DOI	10.1016/j.rse.2019.111488
	Estimation of crop angle of inclination for lodged wheat using multi-sensor SAR data
	Chauhan S.; Darvishzadeh R.; Boschetti M.; Nelson A.
发表日期	2020
ISSN	00344257
卷号	236
英文摘要	Lodging - the bending of crop stems - reduces the quantity and quality of cereal crop yields. Early quantification of crop lodging is important to prevent further losses and to facilitate harvesting operations. Crop angle of inclination (CAI) is a quantitative measure of the lodging stage and a component of lodging severity/score. CAI is an important structural parameter for lodged crops and very few studies have investigated its estimation using satellite-based remote sensing. In this study, the performance of Sentinel-1 and multi-incidence angle (FQ8-27° and FQ21-41°) RADARSAT-2 data were investigated for estimating CAI. Temporal crop biophysical/structural parameters (CAI and crop height) and meteorological data (rainfall and wind speed) were collected throughout May 1-June 30, 2018 in a very large commercial farm located in Jolanda di Savoia, Ferrara, Italy. Field data were grouped into different crop lodging stages (non-lodged/healthy (H), moderate lodging (ML), severe lodging (SL) and very severe lodging (VSL)) based on CAI. Quantitative relationships were established between field-measured CAI values and the RS-derived metrics for Sentinel-1 and RADARSAT-2 timeseries using support vector regression (SVR) models. The RADARSAT-2 FQ8 model performed most robustly with a R2 CV (cross-validated R2) of 0.87 and a RMSECV (cross-validated RMSE) of 8.89° while the performance of the Sentinel-1 and RADARSAT-2 FQ21 models were comparable with an RMSECV of 11.35° and 11.63° respectively. Low incidence angle data were particularly sensitive to high CAI values (VSL) while high incidence angle data were useful for predicting lower CAI (ML and SL). While the RADARSAT-2 FQ-8 model outperformed the other two, the Sentinel-1 model still explained 78% of the CAI variability in the study site, which is important in the context of operational crop lodging stage assessment. This is the first study to demonstrate the utility of SAR remote sensing data for estimating CAI as a measure of the lodging stage and a component of lodging severity. © 2019 The Authors
英文关键词	Crop angle of inclination; Crop lodging; RADARSAT-2; SAR; Sentinel-1; Support vector regression
语种	英语
scopus关键词	Meteorology; Remote sensing; Synthetic aperture radar; Wind; Harvesting operations; Meteorological data; Multi-incidence angles; Quantitative measures; Radarsat-2; Sentinel-1; Structural parameter; Support vector regression (SVR); Crops; biomechanics; RADARSAT; sensor; Sentinel; support vector machine; wheat; Triticum aestivum
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/179591
作者单位	Faculty of Geo-information Science and Earth Observation (ITC), University of Twente, Enschede, 7500AE, Netherlands; CNR-IREA, Institute for Electromagnetic Sensing of the Environment, National Research Council, Milano, 20133, Italy
推荐引用方式 GB/T 7714	Chauhan S.,Darvishzadeh R.,Boschetti M.,et al. Estimation of crop angle of inclination for lodged wheat using multi-sensor SAR data[J],2020,236.
APA	Chauhan S.,Darvishzadeh R.,Boschetti M.,&Nelson A..(2020).Estimation of crop angle of inclination for lodged wheat using multi-sensor SAR data.Remote Sensing of Environment,236.
MLA	Chauhan S.,et al."Estimation of crop angle of inclination for lodged wheat using multi-sensor SAR data".Remote Sensing of Environment 236(2020).