Urban ecosystem dysfunction, habitat fragmentation, and biodiversity loss caused by rapid urbanization have threatened sustainable urban development. Urban habitat quality is one of the important indicators for assessing the urban ecological environment. Therefore, it is of great practical significance to carry out a study on the driving mechanism of urban habitat quality and integrate the results into urban planning. In this study, taking Zhengzhou, China, as an example, the InVEST model was used to analyze the spatial differentiation characteristics of urban habitat quality and Geodetector software was adopted to explore the driving mechanism of habitat quality at different grid-scales. The results show the following: (1) LUCC, altitude, slope, surface roughness, relief amplitude, population, nighttime light, and NDVI are the dominant factors affecting the spatial differentiation of habitat quality. Among them, the impacts of slope, surface roughness, population, nighttime light, and NDVI on habitat quality are highly sensitive to varying grid-scales. At the grid-scale of 1000 to 1250 m, the impacts of the dominant factors on habitat quality is closer to the mean level of multiple scales. (2) The impact of each factor on the spatial distribution of habitat quality is different, and the difference between most factors has always been significant regardless of the variation of grid-scales. The superimposed impact of two factors on the spatial distribution of habitat quality is greater than the impact of the single factor. (3) Combined with the research results and the local conditions of Zhengzhou, we put forward some directions of habitat protection around adjusting urban land use structure, applying nature-based solutions and establishing a systematic thinking model for multi-level urban habitat sustainability.

The degradation and loss of global urban habitat and biodiversity have been extensively studied as a global issue. Urban heat islands caused by abnormal land surface temperature (LST) have been shown to be the main reason for this problem. With the accelerated urbanization process and the increasing possibility of abnormal temperatures in Zhengzhou, China, more and more creatures cannot adapt and survive in urban habitats, including humans; therefore, Zhengzhou was selected as the study area. The purpose of this study is to explore the response of urban habitat quality to LST, which provides a basis for the scientific protection of urban habitat and biodiversity in Zhengzhou from the perspective of alleviating heat island effect. We used the InVEST-Habitat Quality model to calculate the urban habitat quality, combined with GIS spatial statistics and bivariate spatial autocorrelation analysis, to explore the response of habitat quality to LST. The results show the following: (1) From 2000 to 2015, the mean value of urban habitat quality gradually decreased from 0.361 to 0.304, showing a downward trend as a whole. (2) There was an obvious gradient effect between habitat quality and LST. Habitat quality’s high values were distributed in the central and northern built-up area and low values were distributed in the high-altitude western forest habitat and northern water habitat. However, the distribution of LST gradient values were opposite to the habitat quality to a great extent. (3) There were four agglomeration types between LST and habitat quality at specific spatial locations: the high-high type was scattered mainly in the western part of the study area and in the northern region; the high-low type was mainly distributed in the densely populated and actively constructed central areas; the low-low type was mainly distributed in the urban-rural intersections and small and medium-sized rural settlements; and the low-high type was mainly distributed in the western mountainous hills and the northern waters.

The effect of urbanization on the urban thermal environment (UTE) has attracted increasing research attention because its significant effects on local weather and climate, and serious consequences for people. However, systematic study of the relationship between urbanization and UTE has been undertaken only to a limited extent. Using quantitative thermal remote sensing and multi-buffer ring method and multiple spatial scales method, here we analyze Landsat TM/ETM+ images of Zhengzhou in Central China acquired on four different dates in 2017 to investigate the spatiotemporal variations, trends, and driving force in the land surface temperature (LST). Our results showed that LST generally increased with urbanization intensity. This trend was extremely obvious in spring and summer, weak in winter, and slightly downward in autumn. Moreover, PLAND (e.g., percentage of impervious surface in a landscape) has the most significant effect on urban LST, and generally increases as the spatial scale becomes larger. In conclusion, the study recommends that urban planning in Zhengzhou should prioritize PLAND, especially at large spatial scales. These results provide a scientific reference for urban planners who are committed to the sustainable development of Zhengzhou City.

With the rapid development of urbanization, the habitat quality (HQ) in urban areas has been eroded. This phenomenon is destroying the balance of ecosystems, triggering the reduction of biodiversity and the decay of ecosystem service functions. The study of the relationship between urbanization and HQ in Zhengzhou City is beneficial for the reference of sustainable urban ecological planning and management. Based on landscape classification data and socioeconomic data for three years, this study analyzes the spatial correlations between socioeconomic and landscape pattern factors and HQ, compares the dynamic changes in the explanatory power of different factors, and explores the joint effects between multiple factors. The results show that: (1) The overall value of HQ index in Zhengzhou City decreased by .10 during 2000–2020, mainly occurring in suburban areas, with a small amount of HQ improvement occurring in the core areas of ecological protection, such as mountains and river channels. (2) The spatial autocorrelation of all influencing factors with HQ increased during this period, while the negative impact from socio-economic sources was stronger than the positive impact from landscape patterns. (3) Intensive human activities lead to a single habitat type, which reduces HQ; rich landscape types and complex landscape composition can enhance HQ. Improving the connectivity of blue-green landscapes helps to attenuate the negative effects of urbanization on HQ. (4) Changes of HQ in the study area and the development of multi-factor effects on HQ are driven by the Zhengzhou Metropolitan Area Plan. Urban development policies and management can build idyllic complexes at the edge of urban development, preserving pristine blue-green patches to avoid their homogenized distribution and thus slowing the decline of HQ. The above results provide new ideas for the development of sustainable urban ecology.

The ecological impacts of dam and reservoir construction necessitate systematic environmental quality evaluation (EEQ) to reconcile ecological protection with sustainable development. To address this need, we integrated the Remote Sensing Ecological Index (RSEI)—a comprehensive metric synthesizing greenness, humidity, heat, and dryness—with a Land Use Change Ecological Response (LUCER) model to quantify the long-term EEQ dynamics in reservoir-affected regions. This study utilized Landsat and Sentinel-2 remote sensing imagery with a 10 m resolution from the years 2000, 2005, 2010, 2015, and 2020 to compute the RSEI for the Qianping Reservoir area in Henan Province, investigating the spatiotemporal variations in EEQ. Key findings reveal: (1) Temporal trend: EEQ showed fluctuating improvement, with RSEI projected to rise gradually until 2030. (2) Spatial pattern: A lower ecological quality in central reservoir zones contrasts with higher quality in surrounding mountainous areas. (3) Mechanism: The Land Use Change Ecological Response (LUCER) model reveals that the conversion of cultivated land to forestland and grassland drives significant EEQ improvements, counterbalancing the negative impacts of hydrological fragmentation caused by reservoir construction and urbanization. This study advances RSEI applications in reservoir ecology by establishing a coupled monitoring–prediction framework, providing actionable insights for dam-related ecological restoration and governance.