Promoting the sustainable development of traditional villages: Exploring the comprehensive assessment, spatial and temporal evolution, and internal and external impacts of traditional village human settlements in hunan province.

The protection and development of traditional villages are crucial for improving the human settlement suitability (HSS). The paper takes 703 traditional villages in Hunan Province as the research object and establishes the HSS evaluation system by using the pressure-state-response model. Then this paper introduces the vector autoregressive model to explore the interactions and contributions within the three major subsystems. Finally, this paper adopts Geodetector model and GTWR model to study the external driving effects and temporal-spatial influence mechanisms. The main findings of this paper are as follows. First, the overall trend of the composite index of traditional villages is upward. Its spatial pattern transitions from a low index in the northwest to a medium index in the central region and a high index in the southeast. Second, the state system becomes the main driver of the response system change and it is highly influenced by the pressure system. Distance from medical facilities, Distance from educational institutions, Distance from the intangible cultural heritage sites, and Degree of relief are the four most important driving factors affecting the HSS in Hunan Province. At the same time, Distance to medical facilities and Distance to intangible cultural heritage sites have a positive impact, while Distance to educational institutions and Degree of relief have a negative impact. Fourly, these four factors have a significant spatiotemporal impact on the HSS in the Xiangxi region. This paper provides a scientific basis for the sustainable development and conservation of traditional villages in Hunan from multiple perspectives.

Quantitative assessment, spatial and temporal characteristics, and dynamic evolution of carbon emissions from animal husbandry in China: 2001-2020.

Carbon emissions from animal agriculture are a major source of global greenhouse gases. This paper measures the spatial and temporal characteristics and evolution patterns of carbon emissions from livestock farming in China and 31 provinces from 2001 to 2020 based on IPCC coefficients. The paper also uses Moran's I index, kernel density estimation, and spatial Markov chains for the analysis. The results show that the total carbon emissions from China's livestock sector show a fluctuating downward trend. And livestock carbon emissions are concentrated in areas with better resource endowments, with grassland and grain-producing areas dominating China's livestock carbon emissions. The spatial analysis shows that the spatial correlation of the national livestock carbon emissions is increasing, showing prominent local aggregation characteristics, mainly in the form of high-high and low-low aggregation. The transfer of carbon emissions from China's livestock industry shows strong spatial and temporal dependence, and the transfer of regional carbon emissions is limited by the original type and stock of carbon emissions, showing growth inertia and path dependence. The findings of this paper can provide suggestions for planning and modifying policies to reduce carbon emissions in China's livestock industry.

Comprehensive evaluation of community human settlement resilience and spatial characteristics based on the supply-demand mismatch between health activities and environment: a case study of downtown Shanghai, China.

INTRODUCTION: Under globalization, human settlement has become a major risk factor affecting life. The relationship between humans and the environment is crucial for improving community resilience and coping with globalization. This study focuses on the key contradictions of community development under globalization, exploring community resilience by analyzing the mismatch between residents' health activities and the environment. METHODS: Using data from Shanghai downtown, including land use, Sports app, geospatial and urban statistics, this paper constructs a comprehensive community resilience index (CRI) model based on the DPSIR model. This model enables quantitative analysis of the spatial and temporal distribution of Community Human Settlement Resilience (CR). Additionally, the paper uses geodetector and Origin software to analyze the coupling relationship between drivers and human settlement resilience. RESULTS: i) The scores of CR showed a "slide-shaped" fluctuation difference situation; ii) The spatial pattern of CR showed a "pole-core agglomeration and radiation" type and a "ring-like agglomeration and radiation" type. iii) Distance to bus stops, average annual temperature, CO2 emissions, building density and number of jogging trajectories are the dominant factors affecting the resilience level of community human settlement. CONCLUSION: This paper contributes to the compilation of human settlement evaluation systems globally, offering insights into healthy community and city assessments worldwide. The findings can guide the creation of similar evaluation systems and provide valuable references for building healthy communities worldwide.