A synthetic aperture radar (SAR) target recognition approach is developed in this paper by exploiting the multiscale monogenic components, which are extracted from SAR images based on the 2D monogenic signal. The 2D canonical correlation analysis is then employed to analyze the correlations of the same monogenic components at different scales. Afterwards, the three monogenic components, i.e., local amplitude, local phase, and local orientation, at different scales are fused as three feature matrices, respectively. In order to further capture the correlations between different types of monogenic components, the joint sparse representation is used for target classification. Therefore, both the correlations of the same monogenic components at multiple scales and the relatedness among different types of monogenic components can be exploited in the proposed scheme. The real measured SAR images from the moving and stationary target acquisition and recognition dataset are classified to examine the validity of the proposal. Compared with some state-of-the-art SAR target recognition methods, the proposed approach is validated to be superior under both standard operating condition and several usual extended operating conditions according to the experimental results. In comparison with some other methods, which also use monogenic components as the basic features, the superiority of the proposed method demonstrates that it could better make use of the monogenic components to improve the classification performance. INDEX TERMS Synthetic aperture radar (SAR), target recognition, monogenic signal, 2D canonical correlation analysis (2DCCA), joint sparse representation (JSR).

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Soil salinization is a global problem that limits agricultural development and impacts human life. This study aimed to understand the dynamic changes in water and salinity in saline-alkali soil based on an indoor soil column simulation. We studied the changes in the water and salt contents of soils with different degrees of salinization under various irrigation conditions. The results showed that after seven irrigations, the pH, conductivity and total soluble salt content of the percolation samples after irrigation generally increased initially then decreased with repeated irrigation. The soil moisture did not change significantly after irrigation. The pH, conductivity, and total soluble salt content of each layer of the soil profile exhibited general declining trends. In the soil profile from Changguo Township (CG), the pH decreased from 8.21–8.35 to 7.71–7.88, the conductivity decreased from 0.95–1.14 ms/cm to 0.45–0.68 ms/cm, and the total soluble salt content decreased from 2.63–2.81 g/kg to 2.28–2.51 g/kg. In the soil profile from Zhongjie Industrial Park (ZJ), the pH decreased from 8.36–8.54 to 7.73–7.96, the conductivity decreased from 1.58–1.68 ms/cm to 1.45–1.54 ms/cm, and the total soluble salt decreased from 2.81–4.03 g/kg to 2.56–3.28 g/kg. The transported salt ions were primarily K+, Na+ and Cl-. After several irrigations, a representative desalination effect was achieved. The results of this study can provide technical guidance for the comprehensive management of saline-alkali soils.

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Competition for land is increasing as demand for multiple land uses and ecosystem services rises. Land regulation of the principles of landscape ecology is necessary to develop more sustainable approaches to land use planning. The research evaluated the present land patterns and determined best practices for its regulation of Dongwang Township in Quyang County, located in the Taihang Mountain area of Hebei Province, China. The research used the landscape ecology theory to construct an index system for landscape pattern analysis based on the GIS and Fragstats 3.3 software. In this study, we examined the specific reasons that landscape ecology is superior to traditional methods in land consolidation planning and design, which is conducive to the comprehensive development of land ecological benefits. Landscape ecological planning can effectively reduce landscape fragmentation and improve intensive management. The result found that the descending order of the Shannon index was current landscape, landscape ecological planning, and traditional planning. Landscape ecological planning could protect the natural diversity than traditional planning. Landscape ecological planning enables the creation of long corridors, with higher densities and connectivity and lower average corridor widths than traditional planning. Besides, it can improve ecological service function values in the study area to varying degrees, thus discouraging residents from limiting themselves to grain production. This research has great potential to improve the visibility of ecosystem services in local land use planning and, thus, to improve the ecological functioning of future landscapes.