Human settlements are areas closely related to human production and life, and their quality directly affects people’s physical health and quality of life. However, with air pollution continuing to worsen, people are becoming increasingly concerned about the exposure to air pollution in their residential regions. In addition, many studies ignore the long-term impact of environmental factors on the evolution of human settlement quality (HSQ). This study aims to assess the HSQ in the Mid-Spine Belt of Beautiful China (MSBBC) from 2000 to 2020 and to analyze the changes in its driving forces during different time periods. We divided the HSQ into five dimensions: terrain conditions, climate conditions, hydrological conditions, ground cover conditions, and air pollution exposure. The Entropy-TOPSIS and grey relational degree model were used to assess the HSQ in the MSBBC. To analyze the driving forces of HSQ, the optimal-parameters-based geographic detector model was utilized. The results show the following: (1) Within the study area, the degree of the population exposure risk to PM_2.5 and its change trend were significantly different on both sides of the Hu Line, with the east showing higher levels than the west. (2) The HSQ of the MSBBC decreased from east to west. Moreover, the HSQ in the metropolitan area of the urban agglomeration was characterized from low to high. The HSQ underwent three phases, consisting of an increase (2000–2010), a decrease (2010–2015), and an increase again (2015–2020). (3) Among the driving factors, the impact of PM_2.5 on the HSQ weakened year by year. The driving force of meteorological parameters on the HSQ was the strongest. Furthermore, the interactions of each factor could enhance the HSQ. The results of this study not only provide a strong reference for creating livable areas and promoting sustainability in the MSBBC but also contribute to addressing challenges such as pollution and climate change.

In this paper, we are concerned with the inverse acoustic scattering problem of determining the position and shape of a sound-soft obstacle from the limited aperture far-field data. We propose the Adaptive Ensemble Kalman Filter (AEKF) combined with the extended sampling method (ESM) to recover the location and shape of the obstacle. Firstly, ESM is applied to identify the position of the obstacle based on the limited data. Then, the AEKF is employed to reconstruct the shape of the obstacle by adaptively updating the ensemble through a covariance adjustment guided by the Data Misfit Controller (DMC). Numerical examples are provided to demonstrate the effectiveness of the proposed method.

We consider an ensemble Kalman inversion scheme for inverse elastic scattering problems in which the unknown quantity is the shape of the scatterer. Assume that the scatterer is a piecewise constant function with known value inside inhomogeneities. The level set method is described as an implicit representation of the scatterer boundary, with Gaussian random fields serving as prior to provide information on the level set functions. The ensemble Kalman filter method is then employed based on the level set functions to reconstruct the shape of the scatterer. We demonstrate the effectiveness of the proposed method using several numerical examples.

This study aims to overcome the technical bottleneck of non-invasive differentiation between the rammed earth layer and pebble layer in complex shallow subsurface environments, particularly focusing on the challenge of detecting highly heterogeneous pebble layers with complex wavefield characteristics. Using the western city wall of the Baodun site (Xinjin, Sichuan, China) as a case study, we introduce a high-resolution seismic detection technique combined with controllable high-frequency seismic source excitation to investigate the response characteristics of high-frequency components and energy variations of seismic waves in different strata, thereby revealing differences in physical properties between the rammed earth layer and pebble layer. Through high-frequency data acquisition, specialized processing, and interpretative analysis of seismic data, we successfully distinguish the two strata and delineate pebble-related anomalous zones. The results also indicate that, due to complex geological conditions, the reflection and refraction patterns of seismic waves in the pebble layer are exceptionally intricate. Moreover, the interplay of abrupt seismic velocity variations, interference waves, and other contributing factors leads to pronounced heterogeneity and strong scattering characteristics in the seismic data across the time, frequency, and phase domains. This research overcomes the limitations of conventional geophysical methods and confirms the applicability of high-frequency seismic techniques to complex near-surface archaeological contexts. It provides robust scientific support for the archaeological study of the Baodun site and offers a methodological reference for subsurface mapping of pebble layer in prehistoric urban landscapes.