Compact polarimetry assessment for rice and wetland mapping

Abstract

Polarimetric RADARSAT-2 data of rice and wetlands are used to simulate compact polarimetry (CP) mode data from the upcoming RADARSAT Constellation Mission (RCM). The simulated CP data are then used to evaluate the information content for rice and wetland mapping using supervised classification, and the results are compared for linear and circular polarization combinations and polarimetric decompositions from the fully polarimetric data and the simulated CP data. The results are consistent for both rice and wetlands and show that the classification accuracy increases as one goes up the polarization hierarchy. The circular polarizations produced the best classification results for the polarization combinations. This result requires further research to verify. Although the CP data did not perform as well as the fully polarimetric data, the results were better than for dual polarization, and this mode may offer the best option for rice and wetland mapping applications because of swath coverage. Note that both the compact simulations and the fully polarimetric data produced operationally suitable classification accuracies. Additional research is underway to evaluate the monitoring capability of this new CP mode. This article describes the approach used for the analyses and the classification results for both rice and wetlands.

Contributions of Actual and Simulated Satellite SAR Data for Substrate Type Differentiation and Shoreline Mapping in the Canadian Arctic

“…This is mostly as a result of increased confusion with Tundra, for which user's and producer's accuracies were also generally lower for models constructed with simulated RCM data. These results are consistent with [73] who similarly noted a decrease in the classification accuracy of wetlands when substituting quad pol RADARSAT-2 for simulated RCM data. Nevertheless, the authors found that the CP mode still achieved relatively high accuracies, and so suggested it was suitable for broad scale mapping.…”

Best Accuracy Land Use/Land Cover (LULC) Classification to Derive Crop Types Using Multitemporal, Multisensor, and Multi-Polarization SAR Satellite Images

“…This is not a new discovery, and is a consequence of the special interaction of microwaves with inundated rice fields [30,57]. By making use of this interaction, rice fields can be separated from the other land use classes with high accuracy [27,31,58]. Another known fact that can be justified by this study is that only multi-temporal radar acquisitions are adequate to dissolve different crops [20,21].…”

A Collection of SAR Methodologies for Monitoring Wetlands

“…This allows the user to decompose the SAR backscatter being returned from the objects being sensed into four common scattering types: (1) specular scattering (no return to the SAR), which occurs from smoother surfaces such as calm water or bare soil; (2) rough scattering, which results when there is a single bounce return to the SAR from surfaces such as small shrubs or rough water; (3) volume scattering, which is when the signal is backscattered in multiple directions from features such as vegetation canopies; and (4) double-bounce or dihedral scattering, which results when two smooth surfaces create a right angle that deflects the incoming radar signal off both surfaces such that most of the energy is returned to the sensor. This latter scattering case typically occurs when vertical emergent vegetation is surrounded by a visible, smooth water surface [32,[47][48][49][50][51]. Flooded vegetation can also have a combination of double-bounce and volume backscattering [50,51].…”

“…This latter scattering case typically occurs when vertical emergent vegetation is surrounded by a visible, smooth water surface [32,[47][48][49][50][51]. Flooded vegetation can also have a combination of double-bounce and volume backscattering [50,51]. When fully polarimetric SAR images are acquired throughout the growing season, the user can analyze the backscatter response from each stage of the hydrologic and vegetation development (leaf-on and leaf-off) to better understand responses during wetter and dryer periods.…”

“…With the advancement of fully polarimetric satellite systems such as RADARSAT-2 the satellite can transmit and receive energy in all four planes (HH, VV, HV and VH), maintaining the phase and allowing for mapping of the different scattering mechanisms within a wetland [49], rather than just the difference between low and high backscatter values (Figure 1). The phase measures the time it takes for the radar signal sent from the satellite to interact with the target on the ground and return to the satellite [50]. This allows the user to decompose the SAR backscatter being returned from the objects being sensed into four common scattering types: (1) specular scattering (no return to the SAR), which occurs from smoother surfaces such as calm water or bare soil; (2) rough scattering, which results when there is a single bounce return to the SAR from surfaces such as small shrubs or rough water; (3) volume scattering, which is when the signal is backscattered in multiple directions from features such as vegetation canopies; and (4) double-bounce or dihedral scattering, which results when two smooth surfaces create a right angle that deflects the incoming radar signal off both surfaces such that most of the energy is returned to the sensor.…”