Spatiotemporal Variation and Influence Factors of Habitat Quality in Loess Hilly and Gully Area of Yellow River Basin: A Case Study of Liulin County, China

China has set up ecological protection and high-quality development of the Yellow River Basin as its national strategy. However, the fragile natural ecosystem and intensive human disturbances pose challenges to it. This study evaluates habitat quality change and analyzes its drivers in a representative county of this region, aiming to provide scientific basis for ecological protection and sustainable development. We took Liulin, a representative county of middle Yellow River Basin as the study area and evaluated the spatiotemporal variation of habitat quality from 2000 to 2020 with the InVEST model. Further, the influencing factors of habitat quality pattern were explored using GeoDetector, and their gradient ranges dominating the habitat quality change were determined by gradient analysis. The results showed that: (1) Areas of low and medium-low habitat quality grades were distributed interactively in the whole county; medium grade areas were scattered in the northeast and southwest parts of the county; and medium-high and high grades area were distributed sporadically along the Yellow River and its branches. (2) Habitat quality of the county almost unchanged from 2000 to 2010. However, from 2010 to 2020, with the rapid expansion of construction land (increased by 9.62 times), the area proportion of medium, medium-high, and high habitat quality grades decreased from 7.01% to 5.31%, while that of low and medium-low habitat quality grades increased from 92.99% to 94.69%. (3) The habitat quality was influenced by multiple natural-human factors. The main influencing factor was land use, followed by elevation. (4) Most changes of habitat quality occurred in areas with lower elevation, gentler slope, and higher vegetation coverage, which were affected by intensive human activities. These results suggest that in future land use policy making and, the construction land expansion in Liulin County should be restricted and differentiated ecological protection and restoration strategies should be implemented in areas with different habitat quality.

Long-Term Spatiotemporal Variation of Net Primary Productivity and Its Correlation With the Urbanization: A Case Study in Hubei Province, China

Net primary productivity (NPP) is a critical component in terrestrial ecosystem carbon cycles. Thus, quantitatively estimating and monitoring the dynamics of NPP have become key aspects for exploring the carbon cycle of terrestrial ecosystems. Anthropogenic activity, such as urbanization, has significant effects on NPP and increases pressure on the natural resources of a specific region. However, to date, although many studies have focused on the relationship between NPP variation and urbanization, they usually ignored any differences at a long-term spatiotemporal variation of urbanization factors, which led to the insufficient understanding of the urbanization-induced impacts on NPP. As a result, this study effectively explored the spatiotemporal variation of NPP from 2001 to 2012 and its corresponding relationship with urbanization, taking the Hubei Province in China as a case study area. To clarify the degree of urbanization, the spatial distribution and temporal variation of population and gross domestic product (GDP) were simulated based on the elevation-adjusted human settlement index and nighttime lights data. The major results showed that high NPP areas were located in those highlands with widespread woodland, in which the NPP value continued to grow during the period. The low NPP areas were mainly distributed in urban areas, and the NPP value had a continued and visible loss. The population and GDP both had a strong correlation with NPP. The significant negative correlation was concentrated in the center of Hubei, with a dense population and developed economy. In order to further realize their complex relationship, the correlation coefficients between the annual NPP and the two factors from 2001 to 2012 were calculated, and the changing trends were investigated. Overall, the findings of this study may provide a reference for studies on the interaction between ecological environment and socioeconomic processes under the background of global rapid urbanization.

Understanding the Spatiotemporal Variation of High-Efficiency Ride-Hailing Orders: A Case Study of Haikou, China

Understanding the spatiotemporal variation of high-efficiency ride-hailing orders (HROs) is helpful for transportation network companies (TNCs) to balance the income of drivers through reasonable order dispatch, and to alleviate the imbalance between supply and demand by improving the pricing mechanism, so as to promote the sustainable and healthy development of the ride-hailing industry and urban transportation. From the perspective of TNCs for order management, this study investigates the spatiotemporal variation of HROs and common ride-hailing orders (CROs) for ride-hailing services using the trip data of Didi Chuxing in Haikou, China. Ordinary least squares (OLS) and geographically weighted regression (GWR) models are established to examine the factors that affect the densities of HROs and CROs during different time periods, such as morning, evening, afternoon and night, with considering various built environment variables. The OLS models show that factors including road density, average travel time rate, companies and enterprises and transportation facilities have significant impacts on HROs and CROs for most periods. The results of the GWR models are consistent with the global regression results and show the local effects of the built environment on HROs and CROs in different regions.

Spatiotemporal variation in global floods with different affected areas and the contribution of influencing factors to flood-induced mortality (1985–2019)

Floods are great threats to human life and property. Extensive research has investigated the spatiotemporal variation in flood occurrence, while few have studied the heterogeneity in global flood events of different sizes, which may require different coping strategies and risk reduction policies. In this study, we analysed the spatiotemporal patterns of global flood events with different affected areas (classified in three levels) during 1985–2019 and examined the contribution of different influencing factors to flood-induced mortality using Geodetector. The results show that (1) the increase in global flood frequency was mainly caused by Level II and Level III floods, and the average area affected by flood events has been increasing yearly since 1985. (2) In America and Africa, the frequency of Level III floods has increased monotonically. At the same time, the frequency of Level I floods in Europe and Level II floods in Asia has increased significantly. (3) For Europe and Asia, most of the deaths occurred with Level II floods; while for America and Africa, Level III floods caused the most mortality. (4) The top three factors contributing to the spatial heterogeneity in flood-induced mortality were the affected population, GDP per capita and flood duration. The contribution of each factor varied among the different types of floods. Topographic factors (percentage of mountainous area) magnified flood-induced mortality during extreme events with heavy rainfall, especially for Level III floods. The heterogeneity in flood frequency and flood-induced mortality indicates that flood protection measures should be more targeted. In addition, the increase in large-scale floods (Level III) highlights the need for transregional cooperation in flood risk management.