Xiaoning Wang

The elevational patterns of plant β diversity and their underlying drivers are known to be scale-dependent, but pinpointing the spatial scales at which different ecological processes occur remains challenging using traditional field inventory methods. Remote sensing has emerged as a promising alternative, providing continuous spatial data for monitoring plant diversity. In this study, we used field inventory data and corresponding Sentinel-2 images from a subtropical mountain to simulate pooled assemblages and assess the potential of using multispectral satellite images in predicting tree β diversity. We further examined the scale-dependent elevational gradient of the spectral β diversity and identified primary topographic variables across different spatial extents (0.16–64 ha). The spectral β diversity showed a consistently positive relationship with the inventory β diversity calculated using various indices (average pairwise Sørensen, Jaccard, and Bray–Curtis dissimilarities, as well as multi-community differentiation measures based on Hill numbers), with the strongest correlation observed for abundance-weighted indices and images from early spring and late autumn (R²_max = 0.63). However, a null model-derived β deviation showed only a weak correlation between remote sensing and field-based measures. A declining trend in the spectral β diversity with an increasing elevation was observed and became more pronounced at larger extents. The topographic heterogeneity, represented by the slope and northness, explained the elevational gradients at spatial extents >4 ha, attesting the significant role of environmental filtering in shaping plant diversity patterns, even at fine scales. While the northness was more influential at smaller spatial extents (4 ha). This study showcases the potential of using readily available remote sensing data to address difficult questions in plant diversity research.

For current time-sensitive anti-deception jamming methods, waveform diversity, spatial-polarization domain filtering and feature library identification are employed to eliminate deception jammings. However, high system design complexity and engineering implementation cost severely limit the application of these algorithms. In order to address the above mentioned problem, a novel anti-deception jamming method based on trajectory characteristics is proposed from the perspective of trajectory processing. Through analysing the trajectory characteristic difference between different types of deception jamming and real target, high-order trajectory fitting coefficients, parameter matching relationship and multi-channel amplitude statistical characteristics are extracted severally. Accordingly, passive deception jamming, active range-Doppler deception jamming, active angle deception jamming and real targets can be distinguished. The proposed algorithm makes full use of the advantages of multi-frame trajectory processing for anti-deception jamming, meanwhile, it takes account both the system design complexity and the anti-jamming performance. Simulation results show effectiveness of this algorithm.

The Yangtze River Delta and North China Plain are experiencing serious land subsidence development and are also the areas that have undergone the fastest urbanization. Rapid urban development inevitably requires more water resources. However, China is a country with small per capita water resources, nonuniform distribution of water resources, and over-exploitation of groundwater – all of which are critical factors contributing to the potential for a land subsidence disaster. In addition, land subsidence has brought about elevation loss, damaged buildings, decreased safety of rail transit projects, lowered land value, and other huge economic losses and potential safety hazards in China. In this paper, Beijing, a typical northern Chinese city deficient in water, is taken as an example to explore (a) the problems of urban development, utilization of water resources, and land subsidence development; (b) the harm and influence of land subsidence hazards on urban construction; and (c) the relationship between urban development and land subsidence. Based on the results, the author has predicted the trend of urban development and land subsidence in Beijing and puts forward her viewpoints and suggestions.