Onur Yuzugullu

Polarization Impact in TanDEM-X Data Over Vertical-Oriented Vegetation: The Paddy-Rice Case Study

It has been recently shown that the TanDEM-X mission is capable of tracking the plant growth of rice paddies. The precision of the elevation measure depends on the physical interaction between the synthetic aperture radar (SAR) signal and the canopy. In this letter, this interaction is studied by considering the signal polarization. In particular, the vertical and horizontal wave polarizations are compared, and their performance in the temporal mapping of the crop height is analyzed. The temporal elevation difference analysis shows a monotonically increasing trend within the reproductive stage of the canopy, with maximum height discrepancies between polarizations of about 9 cm. From an operational point of view of InSAR-based vegetation height measurements, this letter demonstrates that the oriented structure of the canopy shall be considered not only in polarimetric InSAR studies but also in the interpretation of bistatic spaceborne interferometric elevation models.

Rice Growth Monitoring by Means of X-Band Co-polar SAR: Feature Clustering and BBCH Scale

Precision agriculture research, which aims to monitor agricultural fields and to manage agricultural practice by considering overall environmental impacts, has gained momentum with the recent improvements in the remote sensing area. The objective of this letter, as a part of precision farming, is to implement Biologische Bundesanstalt, Bundessortenamt und CHemische Industrie (BBCH) scale assignment in plant growth monitoring by means of SAR. The proposed approach copes with structural heterogeneity in agricultural fields by grouping together similar morphologies. For this, densely cultivated paddy rice fields are analyzed using TerraSAR-X (TSX) co-polar SAR data. For generating structurally similar groups, K-means clustering is used in a polarimetric feature vector space, which is composed of backscattering intensities and polarimetric phase differences. This step is followed by a preliminary classification approach based on the temporal separability of the explanatory parameters. In the last step of the proposed methodology, assigned classes are updated based on the biological principles that are followed in rice cultivation. This letter provides the results of the proposed algorithm and compares them to the standard threshold-based approach in two independent agricultural areas. The results show the superiority of the feature-clustering-based classification compared with the standard approach in handling field heterogeneity.

Estimation of Rice Crop Height From X- and C-Band PolSAR by Metamodel-Based Optimization

Rice crops are important in global food economy and are monitored by precise agricultural methods, in which crop morphology in high spatial resolution becomes the point of interest. Synthetic aperture radar (SAR) technology is being used for such agricultural purposes. Using polarimetric SAR (PolSAR) data, plant morphology dependent electromagnetic scattering models can be used to approximate the backscattering behaviors of the crops. However, the inversion of such models for the morphology estimation is complex, ill-posed, and computationally expensive. Here, a metamodel-based probabilistic inversion algorithm is proposed to invert the morphology-based scattering model for the crop biophysical parameter mainly focusing on the crop height estimation. The accuracy of the proposed approach is tested with ground measured biophysical parameters on rice fields in two different bands (X and C) and several channel combinations. Results show that in C-band the combination of the HH and VV channels has the highest overall accuracy through the crop growth cycle. Finally, the proposed metamodel-based probabilistic biophysical parameter retrieval algorithm allows estimation of rice crop height using PolSAR data with high accuracy and low computation cost. This research provides a new perspective on the use of PolSAR data in modern precise agriculture studies.

Determining Rice Growth Stage with X-Band SAR: A Metamodel Based Inversion

Rice crops are important in the global food economy, and new techniques are being implemented for their effective management. These techniques rely mainly on the changes in the phenological cycle, which can be investigated by remote sensing systems. High frequency and high spatial resolution Synthetic Aperture Radar (SAR) sensors have great potential in all-weather conditions for detecting temporal phenological changes. This study focuses on a novel approach for growth stage determination of rice fields from SAR data using a parameter space search algorithm. The method employs an inversion scheme for a morphology-based electromagnetic backscattering model. Since such a morphology-based model is complicated and computationally expensive, a surrogate metamodel-based inversion algorithm is proposed for the growth stage estimation. The approach is designed to provide estimates of crop morphology and corresponding growth stage from a continuous growth scale. The accuracy of the proposed method is tested with ground measurements from Turkey and Spain using the images acquired by the TerraSAR-X (TSX) sensor during a full growth cycle of rice crops. The analysis shows good agreement for both datasets. The results of the proposed method emphasize the effectiveness of X-band PolSAR data for morphology-based growth stage determination of rice crops.

Phenological growth stages of paddy rice according to the BBCH scale and SAR images

Paddy rice is a staple food that feeds more than half of the worlds population. As such, monitoring paddy rice with Synthetic Aperture Radar (SAR) image is a critical area of research. Many possible measures of rice growth as canopy height, LAI, biomass and etc. are considered in the previous works. Among them, canopy height is the most direct measurement and has direct relationship with growth rate. In this study, to monitor paddy rice fields canopy heights are estimated by SAR images containing phase and amplitude information. These two inherent properties of SAR images are examined to retrieve canopy height by a canopy scattering and by a differential interferometric method at X-band. Accuracy analysis showed that differential interferometric technique gives very precise results in terms of canopy height if the canopy is fresh. However, in the case of dry canopy layer, the X-band canopy backscattering model gives much more precise results than the interferometric method as the X-band radar signals penetrate more into canopy in dry case. Even though interferometric techniques do not give detailed information about the physical structure of the canopy as backscattering model do, in this work it is shown that they can be used in operational monitoring.

Using metamodels for agricultural monitoring

Polarimetric Synthetic Aperture Radar (PolSAR) data is sensitive to physical structure of agricultural crops. In line with this fact radiative transfer theory based backscattering models have been used to explain the complicated interaction between electromagnetic waves and vegetation canopy. However, high degree of computational complexity of such models causes challenging inversion process. In this study, sparse Polynomial Chaos Expansion (PCE) metamodel is used for the inversion and the evaluation of the Global Sensitivity Analysis (GSA) of the model parameters. Finally promising results have been obtained for the estimation of height and diameter of stalks, length and width of leaves and growth stages for X-band PolSAR data.

Sar algorithms for crop height estimation: The paddy-rice case study

This paper presents a study of the sensibility of the incoherent (electromagnetic backscattering model) and coherent (DInSAR and PolInSAR inversion) crop height estimation methods of SAR imaging. The methods were compared for paddy-rice crop height monitoring with a TanDEM-X dataset. For this, rice-cultivated agricultural fields located in Northern Turkey were selected. Intensive ground data collection during the cultivation period in 2015 was carried out. The accuracy analysis showed that the requirement of external (vegetation-free) DEM in DInSAR-based crop height estimation decreases its performance compared to the PolInSAR and backscattering inversion methods.

Morphology estimation of rice fields using X-band PolSAR data

Synthetic Aperture Radar (SAR) remote sensing techniques play a significant role in modern agricultural crop monitoring by relating the plant structure (height, biomass, yield and growth-stage) to the backscattering behavior of the vegetative canopy. The current trend in crop monitoring is towards precision agriculture, which needs detailed morphology information. By predicting the physical structure, one can just determine the under and overgrowth conditions. In this study, we propose a probabilistic inversion algorithm for a Radiative Transfer Theory (RTT) model which relates the backscattering response of a canopy to its physical structure. The outcomes of the inversion provided promising results by estimating the dimensions of the primary structures with a small bias.

Comparison of the TanDEM-X response between vertical and horizontal oriented vegetation

The results of a two-year precision agriculture project have clearly demonstrated that TanDEM-X can successfully classify crops morphology through cultivation period. It has been found that TanDEM-X mission is capable of tracking the crop height, and the accuracy of the height estimation depends on the crop morphology, which causes a diversity between canopy top and acquisition phase center. In this work, in addition to interferometry with single polarized channels, polarimetric-interferometric acquisitions have been employed to figure out phase center diversity. The analysis showed that there is a diversity between height estimations from HH and VV polarized interferometric channels, which can reach to 10 cm in the reproductive stages of the crops.

Observation of phenological changes by using dual polarization SAR data

Remote sensing is actively used in observation of the nature. Synthetic aperture radar (SAR) systems are capable of obtaining physical based data under day/night and clear/cloudy sky situations. With sensitivity over the physical changes, they have importance in monitoring of agricultural areas. Paddy rice has been a widely used crop in the World, which requires wetland areas. In Turkey, it is mainly irrigated in Edirne and Samsun. With its importance in Worlds agricultural economy, researches regarding the precision farming of rice increased significantly, which includes remote sensing methods. Here, the effect of phenological changes during growth of rice over dual-pol SAR (phase + amplitude) data are discussed. Fields that are located in Ipsala (Edirne) are chosen as test-site. Ground measurements are conducted during May-September 2013. SAR data that are used to explain the physical changes, are obtained in horizontal-horizontal and vertical-vertical polarization configurations from TerraSAR-X (TSX) and TanDEM-X (TDX) satellites in 2012 and 2013.