An InSAR scattering model for multi-layer snow based on QuasiCrystalline Approximation(QCA) theory

Snow-cover parameters are important indicator factors for hydrological models and climate change studies and have typical vertical stratification characteristics. Remote sensing can be used for large-scale monitoring of snow parameters. In SAR(Interferometric Synthetic Aperture Radar) technology has advantages in detecting the vertical structure of snow cover. As a basis of snow vertical structure detection using In SAR, a scattering model can reveal the physical process of interaction between electromagnetic waves and snow. In recent years, the In SAR scattering model for single-layer snow has been fully studied;however, it cannot be applied to the case of multi-layer snow. To solve this problem, a multi-layer snow scattering mode is proposed in this paper, which applies the QCA(Quad-Crystal Approximation) theory to describe the coherent scattering characteristics of snow and introduces a stratification factor to describe the influence of snow stratification on the crosscorrelation of SAR echoes. Based on the proposed model, we simulate an In SAR volumetric correlation of different types of multi-layer snow at the X band(9.6 GHz). The results show that this model is suitable for multi-layer snow, and the sequence of sub-layers of snow has a significant influence on the volumetric correlation. Compared to the single layer model, the multi-layer model can predict a polarization difference in the volumetric correlation more accurately and thus has a wider scope of application. To make the model more available for snow parameter inversion, a simplified multi-layer model was also developed.The model did not have polarization information compared to that of the full model but showed good consistency with the full model. The phase of the co-polarization In SAR volumetric correlation difference is more sensitive to snow parameters than that of the phase difference of the co-polarization In SAR volumetric correlation and more conducive to the development of a parameter-inversion algorithm. The model can be applied to deepen our understanding of In SAR scattering mechanisms and to develop a snow parameter inversion algorithm.

Permafrost environment monitoring on the Qinghai-Tibet Plateau using time series ASAR images

The permafrost in Qinghai-Tibet Plateau(QTP)has long been the focus of many researchers.In this study,we first use the method that integrates synthetic aperture radar(SAR)intensity and phase information to monitor permafrost environment in the Beiluhe Region,using time series advanced SAR images.The backscattering coefficients(σ^(0))and deformation were extracted for the main features,and the influences of meteorological conditions to them were also quantified.The results show that both the change inσ^(0)and surface deformation are closely related to the active layer,and the deformation is also affected by the permafrost table.First,over meadow and sparse vegetation regions,σ^(0)rose about 6.9 and 4 dB from the freezing to thawing period,respectively,which can be mainly attributed to the thaw of the active layer and increased precipitation.Second,seasonal deformation,derived from the freeze-thaw cycle of the active layer,was characteristic of frost heave and thaw settlement and exhibited a negative correlation with air temperature.Its magnitude was larger than 1 cm in a seasonal cycle.Last,significant secular settlement was observed,with rates ranging from-16 to 2 mm/a,and it was primarily due to the thaw of the permafrost table caused by climate warming.

Number and nest-site selection of breeding black-necked cranes over the past 40 years in the Longbao Wetland Nature Reserve,Qinghai,China

Black-necked crane(Grus nigricollis,BNC),facing serious threats from human activities and habitat variations,is an endangered species classified as vulnerable under the revised IUCN Red List.In this article,we investigated and analyzed the population and nesting microhabitat of BNCs in the Longbao National Nature Reserve(NNR)from 1978 to 2016,and found the number of BNCs increased from 24 in 1978 to 216 in 2016.This establishment of the Longbao NNR represented the activities of protecting endangered animal species are effective.However,the land cover classification results of Landsat images showed that the marsh wetland,which was the BNC’s primary habitat,decreased during 1978–2016,while artificial buildings increased,which affected the habitat of BNCs.The increase in average temperature over the past 40 years has also had an impact on the number of BNCs.BNCs preferred to nest in marsh wetlands or on islands with open water or star-like distributions through observation.The results of the principal component analysis showed that the nearest distance between nests and habitat type were the primary factors influencing nesting site selection.To protect BNC,we suggest decreasing wetland fragmentation,reducing habitat degradation and providing an undisturbed habitat.