| Agriculture is the foundation of the national economy.Under the background of global change, the information demand become more pressingon crop growth and crop yield etc. Timely and effective crop monitoring will be helpful for ensuring national food security and supporting the sustainabledevelopment of modern agriculture.Remote sensing techniques porvide effective means for grasping dynamic crop growth condition timely. Optical remote sensing is often affected by bad weather, especially during the key growth period.Radar remote sensing has a unique advantage in crop monitoring due to its features, such as owning higer "saturation point" in vegetation, be sensitive to moisture, structure etc. However, Radar remote sensing application in agriculture, especially on the quantitative parameters inversion, is much less mature than the optical remote sensing. At present, radar remote sensing application is mainly based on scattering intensity or phase information, but the polarization information has not received its deserved attention. With the increasingly rich data source of polarimetric Synthetic Aperture Radar(PolSAR) and the rapid development of polarization theory, especially on fully polarimetric(FP) and compactpolarimetric(CP) SAR, it is possible to make use of polarization information.To this end, the polarization characteristics of SAR were explored in agricultural vegetation monitoring for typical upland crops of wheat, barley and conola, with the fully polarimetric and compact SAR data in this study. Quantitative methods were developed for crop biomass, lodging disasters, sowing time and harvest progress etc. The main contents are as follows:(1) Early season sowing date monitoring by fully polarimetric SARPolarimetric SAR responses of six parameters were investigated as a function of days after sowing during the entire growing season, by means of five consecutive Radarsat-2 images. A near-continuous temporal evolution of these parameters was observed based on 88 oilseed rape fields. It provided a solid basis for determining the suitable temporal window and the best polarimetric parameters for sowing date monitoring. A high sensitivity of all polarimetric parameters to the DAS at different growing stages was shown. Simple linear models could be calibrated to estimate sowing dates at early growth stages and were validated on an independent data set. Although Volume and Spanparameters provided the highest sowing date estimation accuracy at the earlier growth stages, the other four parameters(Volume/Total, Odd/Total, Entropy and Alpha) were more accurate for a wider temporal window. These results demonstrate the capability and high potential of polarimetric SAR data for monitoring the sowing date of crops in theearly season.(2) Crop harvest progress monitoring by fully polarimetric SARFive multitemporal, quad-pol Radarsat-2 images and one optical ZY-1 02 C image were acquired over a farmland area in China during the 2013 growing season. Typical polarimetric signatures were obtained relying on polarimetric decomposition methods. Temporal evolutions of these signatures of harvested fields were compared with the ones of unharvested fields in the context of the entire growing cycle. Significant sensitivity was observed between the specific polarimetric parameters and the harvest status of oilseed rape fields. Based on this sensitivity, a new method that integrates two polarimetric features was devised to detect the harvest status of oilseed rape fields using a single image. The validation results are encouraging even for the harvested fields covered with high residues. This research demonstrates the capability of PolSAR remote sensing in crop harvest monitoring, which is a step toward more complex applications of Pol SAR data in precision agriculture.(3) Wheat lodging monitoring by fully polarimetric SARA set of backscattering intensity features and polarimetric features by target decomposition techniques, was extracted from 5 consecutive Radarsat-2 images. The temporal evolutions of these features of lodging wheat fields were investigated as a function of days after sowingduring the entire growing season. The temporal behavior was compared between typical lodging fields and normal fields. It was found that polarimetric feature from SAR data was very sensitive to wheat lodging. Then a method called polarimetric index, availing the sensitivity of polarimetry to the structure, was put forward to monitorwheat lodging. The method was validated by two sets of in situ data collected in Shangkuli Farmland area,Inner Mongolia, China, at heading and ripe stages of spring wheat. Almost all the lodging fields were successfully distinguished from normal fields. Furthermore, the result revealed that the polarimetric index can reflect the intrinsic feature of lodging wheat with good anti-inference ability such as wheatgrowth difference.(4) Canola biomass monitoring by compact polarimetric SARFive compact polarimetric SAR imagery was simulated using five fully polarimetric Radarsat-2 data, and the dynamic evolution of polarimetric features, relying on different polarimetric decomposition methods, with the crop growth, was compared in this study. It was found that the Dbl parameter, by m-chi decomposition method, can reflect well the dynamic growth of canola. Therefore, a method of monitoring fresh and dry biomass of canola was put forward in this study. The result show that the root mean square error(RMSE) was 56.5g/m2,448.2g/m2,and the relative error(RE)was 23.9%, 25.0%for fresh and dry biomass respectively. In addition, the precision of the model will be affected when the crops become mature sinceits vegetation water content decline.The results are compared with those of the fully polarization SAR. It revealed that the performance of compact SAR on rapeseed monitoring can achieve the level of fully polarization SAR, considering the advantages of CP SAR, such as wider coverage and less data volume etc. It revealed that the polarization information was necessary in quantitatively monitoring of broad leaf crops, such as rapeseed, and CP SAR has a great potential in crop monitoring.(5) Biomass monitoring of wheat and barley by compact polarimetric SARThis study simulated the compact polarimetric SAR data by fully polarimetric Radarsat-2 data. The dynamic response evolution was explored by time series analysis method. The potential of these polarimetric parameters in modeling the growth parameters was investigated. It was found that the u L and pL in CP mode have a great potential in wheat and barley crop monitoring. High sensitivity was observed, R2 arrived 0.8, for crop height, dry biomass, and fresh biomass, etc. Therefore, a method of monitring crop growth of wheat and barley was proposed base on CP SAR data. The validation showed that this method is successfull before the crop become mature and turn yellow. And the result was compared with that based on traditional dual polarimetric SAR data, such as HH/VV and PDR. It revealed that the uL can achieve the same capacibility in crop growth monitoring. |
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