Evaluation of different orientation angle distributions within the X-Bragg scattering model for bare soil moisture estimation

In this paper, the applicability of three different orientation angle distributions of surface facets within the extended Bragg (X-Bragg) scattering model is investigated for estimation of soil moisture over bare surfaces using both Eigen-based and model-based polarimetric synthetic aperture radar (PolSAR) decomposition techniques. The three distributions considered for investigation in the X-Bragg model are uniform, half cosine, and the Lee distributions. In order to understand the sensitivity of the model using the three orientation angle distributions, key polarimetric parameters, such as scattering entropy (H), scattering anisotropy (A), scattering mechanism (α), cross-pol power (T₃₃), linear T₁₂ coherence (|γ_{(HH+VV)(HH–VV)}|), are simulated and analysed for various widths of distributions. The analysis of the simulated polarimetric parameters show that the Lee distribution has a reduced roughness validity range compared with the uniform and half cosine distributions. DLR E-SAR L-band data from the AgriSAR’2006 campaign over the Demmin test site in Northern Germany are inverted for soil moisture over bare surfaces. The inverted soil moisture from the physics-based X-Bragg model is compared with in situ measured TDR (time domain reflectometry) soil moisture values. The inversion results using the Eigen-based decomposition reveal similar root mean square error (RMSE = 14 vol.%) and inversion rates for three distributions. The model-based decomposition inversion results obtained at various fixed widths of distributions reveal that the Lee distribution shows less RMSE of 8 vol.% and high inversion rates for moderate surface roughness (ks = 0.5) as compared with half cosine and uniform distributions.     

A unified framework for crop classification in southern China using fully polarimetric,dual polarimetric,and compact polarimetric SAR data

With the development of synthetic aperture radar (SAR) techniques, various imaging modes that involve single polarimetry, dual polarimetry, full polarimetry (FP), and compact polarimetry (CP) have been proposed and applied to SAR systems. This article attempts to introduce a unified framework for crop classification in southern China using FP, coherent HH/VV, and CP data. By analysing the polarimetric response from different land-cover types (including rice, banana trees, sugarcane, eucalyptus, water, and built-up areas in the experimental site) and by exploring the similarities between data in these three modes, a knowledge-based characteristic space is created and a unified classification framework is presented. Time-series data acquired by TerraSAR-X over the Leizhou Peninsula, southern China, are used in our experiments. The overall classification accuracies for data in the FP and coherent HH/VV modes are approximately 95%, and for data in the CP mode, the accuracy is 91%, which suggest that the proposed classification scheme is effective. Compared with the Wishart Maximum Likelihood (ML) classifier, the proposed method provides approximately 5.64%, 7.30%, and 6.48% higher classification accuracies in the FP, HH/VV, and circular transmit and dual circular receive modes, respectively.     

Assessing relationships between Radarsat-2 C-band and structural parameters of a degraded mangrove forest

Relationships were assessed between mangrove structural data (leaf area index (LAI), stem density, basal area, diameter at breast height (DBH)) collected from 61 stands located in a black mangrove (Avicennia germinans)-dominated forest and both single polarized ultra-fine (3 m) and multipolarized fine beam (8 m) Radarsat-2 C-band synthetic aperture radar (SAR) data. The stands examined included representatives from the four types of mangroves that typify this degraded system, specifically: predominantly dead mangrove, poor-condition mangrove, healthy dwarf mangrove, and tall healthy mangrove. The results indicate that the selection of the spatial resolution (3 m vs. 8 m) of the incidence angle (27–39°) and the polarimetric mode greatly influence the relationship between the SAR and mangrove structural data. Moreover, the extent of degradation, i.e. whether dead stands are considered, also determines the strength of the relationships between the various SAR and mangrove parameters.

When dead stands are included, the strongest overall relationships between the ultra-fine backscatter (incidence angle of ～32°) and the various structural parameters were found using the horizontal-horizontal (HH) polarization/horizontal-vertical (HV) polarization ratio. However, if the dead stands are not included, then significant relationships with the ultra-fine data were only calculated with the HH data. Similar results were observed using the corresponding incidence angle (～33°) of the fine beam data. When a shallower incidence angle was considered (～39°), fewer and weaker relationships were calculated. Moreover, no significant relationships were observed if the dead stands were excluded from the sample at this incidence angle. The highest correlation coefficients using the steepest incidence (～27°) were found with the co-polarized (HH, vertical-vertical (VV) polarization) modes. Several polarimetric parameters (entropy, pedestal height, surface roughness, alpha angle) based on the decomposition of the scattering matrix of the fine beam mode at this incidence angle were also found to be significantly correlated to mangrove structural data. The highest correlation (R = 0.71) was recorded for entropy and LAI. When the dead stands were excluded, volume scattering was found to be the most significant polarimetric parameter. Finally, multiple regression models, based on texture measures derived from both the grey level co-occurrence matrix (GLCM) and the sum and difference histogram (SADH) of the ultra-fine data, were developed to estimate mangrove parameters. The results indicate that only models derived from the HH data are significant and that several of these were strong predictors of all but stem density.     

Simulation of SAR images of urban areas by using the ray tracing method with measured values of backscatter coefficients

This study uses the ray tracing method to simulate synthetic aperture radar (SAR) images of urban areas. The images are constructed for polarisations: horizontal-horizontal (HH) and vertical-vertical (VV), and different types of buildings, vegetation, and streets. Simulated images of a given area are compared with real SAR images of the same area acquired by the TerraSAR-X satellite. The simulations use the measured backscatter coefficient for HH and VV polarisations and for five different classes of terrain: houses, trees, shrubs, grass, and ground. For multiple reflections, we apply the generalized bistatic Lambertian model. The results show that, despite the limits of the ray tracing method and the approximations involved in modelling three-dimensional objects in the simulated scene, the simulated SAR images correspond well with the actual scene. All features present in the real image are reproduced in the simulated image; in particular, the double reflections of buildings and the surrounding ground appear clearly. However, discrepancies exist, and these are also discussed.     

Characterization of the coherent scattering induced by ridging patterns in agriculture by the use of polarimetric SAR imagery

This article investigates the scattering characteristics of ridging patterns in agriculture by the use of C-band polarimetric synthetic aperture radar (PolSAR) images. The polarimetric signatures of periodic potato fields and row wheat in different directions are highlighted using a set of polarimetric parameters. Enhanced coherent scattering is observed when the alignment direction of the ridging patterns is perpendicular to the radar’s line of sight (LOS). The dominant backscattering mechanism of the ridging patterns is deduced by evaluating different polarimetric parameters. The increased copolarized backscattering coefficients and copolarized correlation coefficient, and the reduced entropy and polarimetric alpha angle, indicate a strong contribution of odd scattering to ridging patterns aligned perpendicular to the LOS. We also compare the dominant contributions to the backscattering of ridging patterns in different phenological stages. Although the canopy changes of potato and wheat with time are significant, the underlying periodic surface changes the dominant scattering mechanism of potato fields over all the phenological stages, and the wheat aligned parallel with the flight direction of radar still has relatively high coherent scattering in the different vegetation development stages. The variability analyses undertake in this study allow a more detailed documentation of the physical scattering process of the ridging patterns in agriculture, and will improve the applicability of synthetic aperture radar images in agriculture.     

Ground-based C-band tomographic profiling of a conifer forest stand

We provide a demonstration of the new tomographic profiling (TP) technique, here applied to forestry for the first time. The portable ground-based synthetic aperture radar (GB-SAR) system was used to capture profiles of the vertical polarimetric backscattering patterns through a ～7 m tall stand of Norway spruce trees. The TP scheme collects data as for normal SAR imaging, but with the antennae aligned in the along-track direction. Adaptive post-processing meant that each TP scan simultaneously captured along-track image transects over the incidence angle range 0°–60°. An important feature of the derived image products is that incidence angle is constant at every point within an image. The measured HH–VV height backscatter profiles were very similar, whilst the cross-/co-polarization ratio showed very little variation with height through the stand. Backscattering profiles showed closest agreement with the branch biomass distribution through the canopy, rather than with trunk or branch + trunk biomasses. Equivalent interferometric tree heights were estimated from the centre of mass of the backscatter-height distribution, which displayed increasing height with increasing incidence angle. There was no significant vertical separation between the cross- and co-polarization returns.     

Calculations of radar backscattering coefficient of vegetation-covered soils

A model for simulating the measured radar backscattering coefficient of vegetation-covered soil surfaces is presented in this study. The model consists of two parts: the first is a soil surface model to describe the backscattered radar pulses from a rough soil surface, and the second part takes into account the effect of vegetation cover. The soil surface is characterized by two parameters, the surface height standard deviation σ and the horizontal correlation length l. The effect of vegetation canopy scattering is incorporated into the model by making the radar pulse subject to two-way attenuation and volume scattering when it passes through the vegetation layer. These processes are characterized by the two parameters, the canopy optical thickness τ and the volume scattering factor η. The model results agree well with the measured angular distributions of the radar backscattering coefficient for HH polarization at the 1.6 GHz and 4.75 GHz frequencies over grass-covered fields. These observations were made from an aircraft platform during six flights over a grass watershed in Oklahoma. It was found that the coherent scattering from soil surfaces is very important at angles near nadir, while the vegetation volume scattering is dominant at larger incident angles (> 30°). The results show that least-squares fits to scatterometer data can provide reliable estimates of the surface roughness parameters, particularly the surface height standard deviation σ. The range of values for σ for the six flights is consistent with a 2 or 3 dB uncertainty in the magnitude of the radar response.     

Microwave electromagnetic modelling of Sahelian grassland

In this paper radar scattering models based on coherent and incoherent formulations for an African grassland (Sahelian) are examined. The coherent model is used to account for the structure of the grass plants and the results are compared with the same model assuming random placement and orientation of scatters, and the radiative transfer model. The validity of the three models applied to grass vegetation is determined by comparing the model predictions with Envisat Advanced Synthetic Aperture Radar (ASAR) data gathered in 2005 over Sahelian grassland. The Agoufou site, as defined in the African Monsoon Multidisciplinary Analysis (AMMA) project, is selected as the test target and a set of ground data was collected during 2004 and 2005. Through a comprehensive data comparison, it is shown that the coherent scattering model with a generator considering botanical information is the best model to predict the backscattering data that matches Envisat measurements well (correlation?=?0.92). At low incidence angles (<30°), the radar backscatter shows a strong dependence on soil moisture variations. The analysis of the different contributions leads to a study of the main scattering mechanisms. For high incidence angles, the backscattering coefficient at HH polarization shows a marked seasonal variation associated with grass presence.     

Imaging and structural feature decomposition of a complex target using multi-aspect polarimetric scattering

Based on the Huynen parametric decomposition of target scattering matrix, the polarimetric ellipse parameters are transformed and applied to decomposition of scattering mechanisms of a complex target in VHR POL-SAR images (very high resolution, polarimetric synthetic aperture radar). Making use of multi-aspect (or circle-aspect) and wideband VHR POL-SAR images, scattering mechanisms of a volumetric target and its structural components are recognized over image pixels. Utilizing the layover features, the target height profile is also estimated from two-dimensional image. As example, polarimetric scattering data of some vehicles on ground, including multi-aspect simulated data and experimental measurements, are applied to validations of scattering mechanism decompositions and target structural feature recognition.     

Potential of SAR sensors TerraSAR-X, ASAR/ENVISAT and PALSAR/ALOS for monitoring sugarcane crops on Reunion Island

Multi-temporal TerraSAR-X, ASAR/ENVISAT and PALSAR SAR data acquired at various incidence angles and polarizations were analyzed to study the potential of these new spaceborne SAR systems for monitoring sugarcane crops. The sensitivity of different radar parameters (wavelength, incidence angles, and polarization) to sugarcane growth stages was analyzed to determine the most suitable radar configuration for better characterisation of sugarcane fields and in particular the monitoring of sugarcane harvest.Correlation between backscattered signals and crop height was also carried out. Radar signal increased quickly with sugarcane height until a threshold height, which depended on radar wavelength and incidence angle. Beyond this threshold, the signal increased only slightly, remained constant, or even decreased. The threshold height is higher with longer wavelengths (L-band in comparison with C- and X-bands) and higher incidence angles (~ 40° in comparison with ~ 20°).The radar backscattering coefficients (σ°) were also compared to the Normalized Difference Vegetation Index (NDVI) calculated from SPOT-4/5 images. Results showed a high correlation between the behaviors of σ° and NDVI as a function of sugarcane crop parameters. A decrease in NDVI for fully mature sugarcane fields due to drying of the sugarcane (water stress) was also observed in the radar signal. This decrease in radar signal was of the same order as the decrease in radar signal after the sugarcane harvest. In general, it is more suitable to monitor the sugarcane harvest using high incidence angles regardless of the radar wavelength. SAR data in L- and C-bands showed an ambiguity between the signals of ploughed fields and those of fields in vegetation because of the high sensitivity of the radar signal at these wavelengths to surface roughness of bare soils. Indeed, sometimes the radar signal of ploughed fields was of the same order as that of harvested or mature sugarcane fields. Results showed better discrimination between ploughed fields and sugarcane fields in vegetation (sugarcane canopy) when using TerraSAR-X data (X-band).Concerning the influence of radar polarization, results showed that the co-polarizations channels (HH and VV) were well correlated, but had slightly less potential than cross-polarization channels (HV and VH) for the detection of the sugarcane harvest. Finally, SAR data at high spatial resolution were shown to be useful and necessary for better analysis of SAR images when the fields were of small size.     

Potential of ASAR/ENVISAT for the characterization of soil surface parameters over bare agricultural fields

The objective of this investigation is to analyze the sensitivity of ASAR (Advanced Synthetic Aperture Radar) data to soil surface parameters (surface roughness and soil moisture) over bare fields, at various polarizations (HH, HV, and VV) and incidence angles (20°-43°). The relationships between backscattering coefficients and soil parameters were examined by means of 16 ASAR images and several field campaigns. We have found that HH and HV polarizations are more sensitive than VV polarization to surface roughness. The results also show that the radar signal is more sensitive to surface roughness at high incidence angle (43°). However, the dynamics of the radar signal as a function of soil roughness are weak for root mean square (rms) surface heights between 0.5 cm and 3.56 cm (only 3 dB for HH polarization and 43° incidence angle). The estimation of soil moisture is optimal at low and medium incidence angles (20°-37°). The backscattering coefficient is more sensitive to volumetric soil moisture in HH polarization than in HV polarization. In fact, the results show that the depolarization ratio σ_HH⁰/σ_HV⁰ is weakly dependent on the roughness condition, whatever the radar incidence. On the other hand, we observe a linear relationship between the ratio σ_HH⁰/σ_HV⁰ and the soil moisture. The backscattering coefficient ratio between a low and a high incidence angle decreases with the rms surface height, and minimizes the effect of the soil moisture.     

Investigating the effect of the physical scattering mechanism of the dual-polarization sentinel-1 data on the temporal coherence optimization results

Polarimetric Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) is an effective technique for increasing the number and phase quality of selected persistent scatterer (PS) pixels. In this technique, multitemporal polarimetric data is used to find the dominant scattering mechanism of targets in a stack of SAR data by polarimetric optimization and to improve the performance of PSI methods for deformation studies. The main goal of polarimetric optimization is to find the optimum scattering mechanism to generate interferograms with better quality. In this paper, we investigated the effect of the physical scattering mechanism on the temporal coherence optimization results. In this framework, we only optimized the physical scattering mechanism. This optimization is based on maximizing the temporal coherency criterion by changing the type of scattering mechanism to increase the number of PS with good phase quality. The proposed method is tested using a dataset of 17 dual-pol SAR data (VV/VH) acquired by Sentinel1-A satellite. This paper concludes that the phase quality of PS pixels can be improved by optimization of physical scattering mechanism. Also, the results show an overall increase of PS pixels density in different areas with respect to the conventional channel of VV.     

Analysis of TerraSAR-X data and their sensitivity to soil surface parameters over bare agricultural fields

The sensitivity of TerraSAR-X radar signals to surface soil parameters has been examined over agricultural fields, using HH polarization and various incidence angles (26°, 28°, 50°, 52°). The results show that the radar signal is slightly more sensitive to surface roughness at high incidence (50°–52°) than at low incidence (26°–28°). The difference observed in the X-band, between radar signals reflected by the roughest and smoothest areas, reaches a maximum of the order of 5.5 dB at 50°–52°, and 4 dB at 26°–28°. This sensitivity increases in the L-band with PALSAR/ALOS data, for which the dynamics of the return radar signal as a function of soil roughness reach 8 dB at HH38°. In the C-band, ASAR/ENVISAT data (HH and VV polarizations at an incidence angle of 23°) are characterised by a difference of about 4 dB between the signals backscattered by smooth and rough areas.Our results also show that the sensitivity of TerraSAR-X signal to surface roughness decreases in very wet and frozen soil conditions. Moreover, the difference in backscattered signal between smooth and rough fields is greater at high incidence angles. The low-to-high incidence signal ratio (Δσ° = σ_26°–28°/σ_50°–52°) decreases with surface roughness, and has a dynamic range, as a function of surface roughness, smaller than that of the backscattering coefficients at low and high incidences alone. Under very wet soil conditions (for soil moistures between 32% and 41%), the radar signal decreases by about 4 dB. This decrease appears to be independent of incidence angle, and the ratio Δσ° is found to be independent of soil moisture.     

Anisotropic analysis of polarimetric scattering and case studies with UAVSAR images

This article analyses the anisotropy of polarimetric scattering changing with azimuth incidence angle using a multi-look processed synthetic aperture radar (SAR) image. First, three canonical scattering models were developed to simulate the migration tracks on the Cameron polarimetric space. The migration tracks indicate that these polarimetric parameters have anisotropic property. Second, unmanned aerial vehicle synthetic aperture radar (UAVSAR) data are used to validate the simulated results. The Cameron scattering-type parameter z and the orientation angle calculated by SAR data are consistent with the simulated results by small perturbation method (SPM) double-scattering. Finally, based on the anisotropic analysis, a new method of extracting polarimetric information is proposed. Using this method, six parameters were obtained and two additional parameters, Purity and Stability, were derived. These parameters contain specific physical meaning and are useful in the recognition of the scattering mechanism. Purity can be used to recognize the simple structure scatterers with zero orientation. Stability has the potential to describe the dynamic property of scatterers.     

COSMO-SkyMed high resolution fully polarimetric synthetic aperture radar exploitation - the ‘strip-spot’ approach

This focused study aimed to generate a fully polarimetric synthetic aperture radar (SAR) data set of 1 m resolution based on the spotlight and stripmap COSMO-SkyMed (CSK) satellite data fusion. The results show the feasibility of overcoming the limitation of the nominal 3 m resolution generated by a series of multi-temporal stripmap SAR data observed in all the polarisations. The CSK satellite system does not allow the observation of cross-polar data in the spotlight acquisition mode because only co-polar data are available. In this work, a fully polarimetric scattering matrix is estimated by using two spotlights in the horizontal horizontal (HH) and vertical vertical (VV) polarisations and two stripmaps in the horizontal vertical (HV) and vertical horizontal (VH) polarisations. The stripmaps were resampled and super-resolved by using the amplitude and phase estimation of sinusoids (APES) filter to achieve the spotlight resolution. The results show that the proposed strip-spot approach has immediate operative applications.     

Development of polarization ratio model for sea surface wind field retrieval from TerraSAR-X HH polarization data

In this article, the polarization ratio (PR) of TerraSAR-X (TS-X) vertical–vertical (VV) and horizontal–horizontal (HH) polarization data acquired over the ocean is investigated. Similar to the PR of C-band synthetic aperture radar (SAR), the PR of X-band SAR data also shows significant dependence on incidence angle. The normalized radar cross-section (NRCS) in VV polarization data is generally larger than that in HH polarization for incidence angles above 23°. Based on the analysis, two PR models proposed for C-band SAR were retuned using TS-X dual-polarization data. A new PR model, called X-PR hereafter, is proposed as well to convert the NRCS of TS-X in HH polarization to that in VV polarization. By using the developed geophysical model functions of XMOD1 and XMOD2 and the tuned PR models, the sea surface field is retrieved from the TS-X data in HH polarization. The comparisons with in situ buoy measurements show that the combination of XMOD2 and X-PR models yields a good retrieval with a root mean square error (RMSE) of 2.03 m s^–1 and scatter index (SI) of 22.4%. A further comparison with a high-resolution analysis wind model in the North Sea is also presented, which shows better agreement with RMSE of 1.76 m s^–1 and SI of 20.3%. We also find that the difference between the fitting of the X-PR model and the PR derived from TS-X dual-polarization data is close to a constant. By adding the constant to the X-PR model, the accuracy of HH polarization sea surface wind speed is further improved with the bias reduced by 0.3 m s^–1. A case acquired at the offshore wind farm in the East China Sea further demonstrates that the improvement tends to be more effective for incidence angles above 40°.     

Estimating the characteristics of vegetation canopies with airborne radar measurements

Abstract

Possible use of synthetic aperture radars (SAR) for monitoring agricultural canopies is investigated in this paper. Data have been acquired on the Orgcval watershed during the AGRISCATT'88 campaign. Four radar experiments were carried out with the airborne scattcrometer ERASME (C and X bands, HH and VV polarizations, multi-incidence angles). Simultaneous ground measurements (soil moisture, leaf area index, water content of the canopy) were conducted on 11 wheat fields. Backscattering coefficients of the canopies arc interpreted in the framework of semi-empirical ‘water-cloud’ models. A simple paramctrization of the angular effect of soil roughness is introduced, allowing the simultaneous use of multi-incidence angle radar data. With a unique set of parameters for each radar configuration ‘ frequency and polarization’ the water-cloud model appears to describe adequately the backscattering of all the fields, over the range of incidence angles. It is shown that in this case, attenuation is the dominant effect of the vegetation and an inversion algorithm is proposed for estimating the water content of vegetation. This algorithm requires measurements at two different incidence angles and various combinations of radar configurations are then tested.     

Multi‐frequency scatterometer measurements on water surfaces agitated by artificial and natural rain

Images of rain events over the ocean acquired by a multi‐frequency/multi‐polarization Synthetic Aperture Radar (SAR) show different radar contrasts at different frequencies and polarizations. In order to better understand these effects, field and laboratory experiments were performed at different rain rates and wind speeds with scatterometers working at different radar frequencies, polarizations, and incidence angles. Our results show that the dominant scattering mechanism on a rain‐roughened water surface, observed at VV polarization, at all incidence angles is Bragg scattering from ring waves. At HH polarization the radar backscatter is caused by both ring waves and non‐propagating splash products, with the dominating effect depending on incidence angle. The reduction and enhancement of the surface roughness by ring waves and sub‐surface phenomena, respectively, result in a transition wavenumber between reduction of the radar backscattering and its enhancement of about 100 rad m^?1. We assume that this transition wavenumber depends on the drop‐size distribution of the rain. Taking into consideration the different dependencies of the radar backscatter at different frequencies and polarizations on rain rate, we suggest a method to estimate rain rates by calculating the ratio of the radar cross‐sections at L band, VV polarization and at C band, HV polarization. Provided an availability of SAR data at the respective frequency–polarization combinations, this method allows for investigating the nature of small‐scale (convective) rain events over the ocean.     

Object-based image analysis of optical and radar variables for wetland evaluation

Optical and radar imagery has been shown to be useful for classifying wetland types and surrounding non-wetland classes such as forest and agriculture. Throughout the literature, recommendations have been made that optical and radar image variables together should improve overall and individual class accuracies. object-based image analysis (OBIA) uses multiple data types to segment objects representing land cover entities that are subsequently classified. There are few studies that have utilized optical and polarimetric radar variables together in OBIA to map wetland classes. This research investigated the potential to combine WorldView-2 optical image variables with fully polarimetric Radarsat-2 image variables in OBIA classification of wetland type. With the addition of radar polarimetric variables, classification accuracy improved for the wetland classes of fen, bog, and swamp over the use of optical imagery alone; specifically the addition of Cloude–Pottier (CP) variables of entropy, anisotropy, and alpha angle improved the classification of fen, and the addition of horizontal transmit and horizontal receive (HH) and horizontal transmit and vertical receive (HV) backscatter intensity improved the classification of swamp.     

Analysis of multi-frequency and multi-polarization SAR data for wetland mapping in Hamoun-e-Hirmand wetland

ABSTRACT

The complex, dynamic and narrow boundaries between vegetation types make wetland mapping challenging. Hereafter the case study of the Hamoun-e-Hirmand wetland is considered by analysing eight Synthetic Aperture Radar (SAR) Images acquired in dry and wet periods with three wavelengths (X-band ~ 3 cm, C-band ~ 6 cm, and L-band ~ 25 cm), three polarizations (HH, VV and VH), and four incidence angles (22°, 30°, 34° and 53°). Then, the Support Vector Machine (SVM) classification method was applied to classify TerraSAR-X, Sentinel-1, and ALOS-PALSAR images. The final wetland land cover map was created by combining the classification results obtained from each sensor. In the case in question, results show that TerraSAR-X (X-band, HH-53°) and Sentinel-1 data (C-band, VV-34°) were useful for determining the flooded vegetation area in the wet period. This is crucial for the conservation of water bird habitats since flooded vegetation is an ideal environment for the nesting and feeding of water birds. PALSAR data (L-band in both HH and VH polarizations, 30°) were capable of separating the classes of vegetation density in the wetland. In the dry period, Sentinel-1 (VV and VH, 34°) and TerraSAR-X (HH, 22° and 53°) had higher potential in land cover mapping than PALSAR (HH and VH, 30°). Based on these results, Sentinel-1 in VV and VH provides the highest ability to discriminate between dry and green plants. TerraSAR-X is better for separating meadow and bare land. The results obtained in this paper can reduce the ambiguity in selecting satellite data for wetland studies. The results can also be used to produce more accurate data from satellite images and to facilitate wetland investigation, conservation and restoration.