Aimin Cai

Polarization signature analysis of paddy rice in southern China

Rice is one of the three largest food grains in the world. Radar remote sensing has been proven to be an effective tool for rice monitoring. With the emergence of spaceborne polarimetric synthetic aperture radar (SAR) satellites, research on polarization backscatter behaviors and identification methods for rice are of great significance and attract the attention of remote sensing communities. The Zhazuo area located in Guizhou province of southwest China was selected as the test site for this study. The RADARSAT-2 polarimetric data acquired on four different dates were used to analyze the polarization backscatter behaviors and temporal variation of rice. Identification methods for rice based on polarization combinations and polarization decompositions were developed. The results indicated that HH with HH/HV was the optimal polarization combination for rice identification, with an accuracy of up to 86.65%. Based on the Pauli decomposition, rice can be discriminated effectively, with an accuracy of about 87.00%. Furthermore, using combinations of different polarization decompositions the identification results were greatly improved. The combination of the Pauli decomposition and the parameter β derived from eigenvector-eigenvalue-based decomposition was best for rice identification, with an accuracy of up to 93.51%.

Subsurface microwave remote sensing and scattering modelling on hyper-saline soil: Example of Lop Nur

Subsurface microwave remote sensing is a direction of Synthetic Aperture Radar (SAR) research. With the penetration capability, SAR is capable of detecting the subsurface targets and materials, especially in arid environment. Lop Nur Lake is located at the east of Tarim Basin in Xinjiang province of China, which is described as “dry core” of the world, and it can provide conditions for SAR penetration. This paper presents preliminary analysis about Lop Nur, and gives out an abstract subsurface structure about it. Then, the major scattering processes are concluded and a two-layer scattering model is developed. Based on parameters of soil samples, some rules about Lop Nur evolution will be figured out. With Genetic Algorithm (GA), an inversion procedure is constructed. All the attempts are viewed as the basis of future comprehensive interpretation about Lop Nur phenomenon.

Applications of polarimetric decomposition technology in a dried up lake evolution

This paper presents fundamental reason to Lop Nur “Ear” feature based on polarimetric decomposition technology. Lop Nur is located at the east Tarim Basin in China, and in history, all the major rivers running in Tarim Basin converged to this lowest place. Lop Nur belongs to arid region, and satisfies penetration conditions for SAR signals. Through comparison between decomposed volume scattering contribution and sub-surface salinity, it is found that subsurface properties (such as salinity) is the fundamental reason to “Ear” feature. And dynamic mechanism of geomorphology builds the relationship between surface and subsurface evolution processes, and indirectly unifies previous points on the reasons to formation of Lop Nur “Ear”. Polarimetric technology is anticipated to be used to retrieve more information and to help extend applications in environment of arid region.

Detection subsurface hyper-saline soil in Lop Nur using full-polarimetric SAR data

This paper presents the research results about Lop Nur using full-polarimetric technology. Lop Nur Lake is one of the driest places in the world and finally lost its last drop of water in 1972. It is well known for its “Earth Ear” feature in optical remote sensing images. Likewise, “Ear” feature is shown in Synthetic Aperture Radar (SAR) images, and even larger because of penetration effect. With the penetration capability SAR is capable of detecting the subsurface targets and materials, especially in arid environment. As for SAR images, both C-band and L-band, there are two key features about Lop Nur area. One is the whole Lop Nur area is high-bright that means the backscattering is much stronger than other sites, such as Gobi, desert and so on. The other feature is the “Ear” pattern formation. polarimetric analysis about these two questions will be conducted based on past research results and field investigations.

Parameters extraction of crop based on PolSAR Data

It is beneficial to extract the parameters of the objects by rich information of PolSAR (Polarimetric Synthetic Aperture Radar) data. With polSAR data of Radarsat-2, the polarimetric character of winter wheat in booting and milk stage is studied based on polarization theory. The results show that: there is a great difference between the polarimetric characters of two stages due to the change of wheat structure. Winter wheat growth can be retrieved by entropy, which changes in different way in the two stages. In booting stage, with LAI increasing, the scattering mechanism tends to be more complex. While in milk stage, with plant density increasing, the scattering mechanism tends to be simpler. The eigenvalue of λ2 is a valuable parameter to retrieve soil moisture with crop cover. Results show the potential advantage of polarimetric radar.

Study on the influence of drought to crop growth based on SAR remote sensing

This paper aims to get the relationship between drought and crop growth. By investigating synthetic aperture radar (SAR) backscattering coefficients, HH- and VV- polarization were found different due to influence from canopy, because of strong attenuation of the VV- polarization by the vertically oriented wheat stems. In small incidence angle, HH is sensitive to soil moisture, while VV is more sensitive to canopy. Two classes of crop with low and high soil moisture are investigated by “water-cloud” model with vegetation descriptor vegetation water mass (VWM). Parameters of the model show that in drought the crop growth will be worse. This research presents that it is possible to study the influence of drought to wheat growth with small incidence angle of C-band SAR.