Time Series of Quad-Pol C-Band Synthetic Aperture Radar for the Forecasting of Crop Biophysical Variables of Barley Fields Using Statistical Techniques
This paper aims to both fit and predict crop biophysical variables with a SAR image series by performing a factorial experiment and estimating time series models using a combination of forecasts. Two plots of barley grown under rainfed conditions in Spain were monitored during the growing cycle of 2...
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MDPI AG
2022-01-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/14/3/614 |
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| author | Ana E. Sipols Rubén Valcarce-Diñeiro Maria Teresa Santos-Martín Nilda Sánchez Clara Simón de Blas |
| author_facet | Ana E. Sipols Rubén Valcarce-Diñeiro Maria Teresa Santos-Martín Nilda Sánchez Clara Simón de Blas |
| author_sort | Ana E. Sipols |
| collection | DOAJ |
| description | This paper aims to both fit and predict crop biophysical variables with a SAR image series by performing a factorial experiment and estimating time series models using a combination of forecasts. Two plots of barley grown under rainfed conditions in Spain were monitored during the growing cycle of 2015 (February to June). The dataset included nine field estimations of agronomic parameters, 20 RADARSAT-2 images, and daily weather records. Ten polarimetric observables were retrieved and integrated to derive the six agronomic and monitoring variables, including the height, biomass, fraction of vegetation cover, leaf area index, water content, and soil moisture. The statistical methods applied, namely double smoothing, ARIMAX, and robust regression, allowed the adjustment and modelling of these field variables. The model equations showed a positive contribution of meteorological variables and a strong temporal component in the crop’s development, as occurs in natural conditions. After combining different models, the results showed the best efficiency in terms of forecasting and the influence of several weather variables. The existence of a cointegration relationship between the data series of the same crop in different fields allows for adjusting and predicting the results in other fields with similar crops without re-modelling. |
| first_indexed | 2024-03-09T23:13:39Z |
| format | Article |
| id | doaj.art-673584f5282e47e2a93bb074a8c99490 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-09T23:13:39Z |
| publishDate | 2022-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-673584f5282e47e2a93bb074a8c994902023-11-23T17:40:39ZengMDPI AGRemote Sensing2072-42922022-01-0114361410.3390/rs14030614Time Series of Quad-Pol C-Band Synthetic Aperture Radar for the Forecasting of Crop Biophysical Variables of Barley Fields Using Statistical TechniquesAna E. Sipols0Rubén Valcarce-Diñeiro1Maria Teresa Santos-Martín2Nilda Sánchez3Clara Simón de Blas4Department of Applied Mathematics, Materials Science and Engineering and Electronic Technology, Rey Juan Carlos University, Móstoles, 28933 Madrid, SpainSchool of Natural and Environmental Sciences, Newcastle University, Newcastle upon Tyne NE1 7RU, UKDepartment of Statistics, Institute of Fundamental Physics and Mathematics, University of Salamanca, 37008 Salamanca, SpainCIALE, Instituto Hispano Luso de Investigaciones Agrarias, University of Salamanca, Villamayor, 37185 Salamanca, SpainDepartment of Computer Sciences and Statistics, Rey Juan Carlos University, Móstoles, 28933 Madrid, SpainThis paper aims to both fit and predict crop biophysical variables with a SAR image series by performing a factorial experiment and estimating time series models using a combination of forecasts. Two plots of barley grown under rainfed conditions in Spain were monitored during the growing cycle of 2015 (February to June). The dataset included nine field estimations of agronomic parameters, 20 RADARSAT-2 images, and daily weather records. Ten polarimetric observables were retrieved and integrated to derive the six agronomic and monitoring variables, including the height, biomass, fraction of vegetation cover, leaf area index, water content, and soil moisture. The statistical methods applied, namely double smoothing, ARIMAX, and robust regression, allowed the adjustment and modelling of these field variables. The model equations showed a positive contribution of meteorological variables and a strong temporal component in the crop’s development, as occurs in natural conditions. After combining different models, the results showed the best efficiency in terms of forecasting and the influence of several weather variables. The existence of a cointegration relationship between the data series of the same crop in different fields allows for adjusting and predicting the results in other fields with similar crops without re-modelling.https://www.mdpi.com/2072-4292/14/3/614RADARSAT-2polarimetric SARbiophysical variablestime seriescointegration |
| spellingShingle | Ana E. Sipols Rubén Valcarce-Diñeiro Maria Teresa Santos-Martín Nilda Sánchez Clara Simón de Blas Time Series of Quad-Pol C-Band Synthetic Aperture Radar for the Forecasting of Crop Biophysical Variables of Barley Fields Using Statistical Techniques Remote Sensing RADARSAT-2 polarimetric SAR biophysical variables time series cointegration |
| title | Time Series of Quad-Pol C-Band Synthetic Aperture Radar for the Forecasting of Crop Biophysical Variables of Barley Fields Using Statistical Techniques |
| title_full | Time Series of Quad-Pol C-Band Synthetic Aperture Radar for the Forecasting of Crop Biophysical Variables of Barley Fields Using Statistical Techniques |
| title_fullStr | Time Series of Quad-Pol C-Band Synthetic Aperture Radar for the Forecasting of Crop Biophysical Variables of Barley Fields Using Statistical Techniques |
| title_full_unstemmed | Time Series of Quad-Pol C-Band Synthetic Aperture Radar for the Forecasting of Crop Biophysical Variables of Barley Fields Using Statistical Techniques |
| title_short | Time Series of Quad-Pol C-Band Synthetic Aperture Radar for the Forecasting of Crop Biophysical Variables of Barley Fields Using Statistical Techniques |
| title_sort | time series of quad pol c band synthetic aperture radar for the forecasting of crop biophysical variables of barley fields using statistical techniques |
| topic | RADARSAT-2 polarimetric SAR biophysical variables time series cointegration |
| url | https://www.mdpi.com/2072-4292/14/3/614 |
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