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This paper attempts to reveal the impact and mechanisms of digital inclusive finance (DIF) on agricultural carbon emission performance (ACEP). Specifically, based on the provincial panel data in China from 2011 to 2020, a super slacks-based measure (Super SBM) model is applied to measure ACEP. The panel regression model and spatial regression model are used to empirically analyze the impact of DIF on ACEP and its mechanism. The results show that: (1) during the study period, China’s ACEP exhibited a continuous growth trend, and began to accelerate after 2017. The high-value agglomeration areas of ACEP shifted from the Huang-Huai-Hai plain and the Pearl River Delta to the coastal regions and the Yellow River basin, the provincial differences displayed an increasing trend from 2011 to 2020. (2) DIF was found to have a significant positive impact on ACEP. The main manifestation is that the development of the coverage breadth and depth of use of DIF helps to improve the ACEP. (3) The positive impact of DIF on ACEP had a significant spatial spillover effect, that is, it had a positive effect on the improvement of ACEP in the surrounding provinces. These empirical results can help policymakers better understand the contribution of DIF to low-carbon agriculture, and provide them with valuable information for the formulation of supportive policies.

Monitoring and mapping agricultural cultural ecosystem services (CES) is essential, especially in areas with a sharp contradiction between agricultural land protection and urban development. Despite research assessing CES increasing exponentially in recent years, our knowledge of the CES of agricultural landscapes is still inadequate. This study used four types of agricultural landscapes in Hangzhou, China, as the study area, analyzed their CES spatial patterns, and explored their societal preferences by integrating the multi-sourced datasets, clustering algorithms, and Maxent model. The results indicated that hot spots of agricultural CES correspond to river valley plains, which were also easily vulnerable to urbanization. Moreover, we found that the CES level of paddy field and dry farmland were higher than tea garden and orchard. Based on the above spatial patterns of supply, demand, and flow of CES, we identified four groups of agricultural land by cluster analysis, distinguishing between significant, unimportant, little used, and potential CES. Further, our results showed that natural and human factors could explain societal preferences. This study can provide a valuable basis for stakeholders to develop balanced strategies by the aforementioned results.

The scientific evaluation of landscape fragmentation and connectivity is important for habitat conservation. It is strongly influenced by the spatial resolution of source maps, particularly in urban environments. However, there is limited comprehensive investigation of the spatial grain effect on urban habitat and few in-depth analysis across different urban gradients. In this paper, we scrutinize the spatial grain effects of urban green space (UGS) cover maps (derived from remote sensing imagery and survey data) with respect to evaluating habitat fragmentation and connectivity, comparing among different urban gradient scenarios (downtown, urban periphery, and suburban area) in Hangzhou, a megacity in China. The fragmentation was detected from three indices, including Entropy, Contagion, and Hypsometry. Then morphological spatial pattern analysis (MSPA) was applied for the landscape element identification. The possibility of connectivity (PC) and patch importance (dPC) were proposed for measuring the landscape connectivity based on Cores and Bridges from MSPA results. The results indicate that the farther the location is from downtown, the less sensitive the landscape element proportion to the spatial resolution. Among the three fragmentation indices, the overall hypsometry index has the lowest sensitivity to the spatial resolution, which implies this index’s broader application value. Considering connectivity, high spatial resolution maps are appropriate for analyzing highly heterogeneous urban areas, while medium spatial resolution maps are more applicable to urban periphery and suburban area with larger UGS patches and less fragmentation. This study suggests that the spatial resolution of UGS maps substantially influence habitat fragmentation and connectivity, which is critical for decision making in urban planning and management.

The distribution of heavy metal pollution in cultivated land is closely related to the quality of the cultivated land. In this study, 533 soil samples were collected from cultivated land in the Yangtze River delta region in China for Cd, Pb, and Hg analyses. Spatial statistical analysis was used to study the heavy metal pollution in the cultivated land, and the driving forces of heavy metal distribution in different cultivated land quality subdivisions were analyzed with GeogDetector. The conclusions are as follows: (1) Among the three heavy metals in the study area, the coefficient of variation of Cd is the largest, and that of Pb is the smallest. The proportion of Cd and Hg exceeding the standard value (the standard of level two in GB 15618—2018) is relatively large, both of which are 5%, (2) From the perspective of the spatial distribution of soil heavy metal pollution, only four counties (CX, HN, WY, and LH) were free of heavy metal pollution. Soil heavy metal pollution in AJ, SY, QJ, and DS counties is relatively serious, and the pollution may come from agricultural activities, manufacturing, and prevalent coastal shipping industries in these counties, (3) The heavy metal pollution levels of cultivated land with different quality levels are different. The high-quality cultivated land has no high contamination, while the medium and the general cultivated land both have high contamination. High contamination is related to Cd for medium and general cultivated lands, and to Hg in only general cultivated land, (4) The main driving factors of heavy metal concentration in cultivated soil were GDP, followed by soil organic matter, and pH. These results indicate that the spatial distribution of heavy metal concentration in cultivated soil was affected by the level of economic development, followed by the ecological environment, indicating that human activities had a critical impact on the ecological environment of cultivated land.

In the context of ensuring national food security, high-intensity agricultural production and construction activities have aggravated the conflicts between agricultural and ecological spaces in ecologically fragile areas, which have become one of the most important factors hindering regional sustainable development. This study took Lin’an District, a typical hilly region of southeastern China, as an example. By constructing a landscape ecological risk evaluation model, land-use conflicts between agricultural and ecological spaces were identified, spatial autocorrelation and topographic gradient characteristics were analyzed, and land-use conflict trade-off mechanisms were proposed. During 2008 and 2018, the degree of land-use conflict in Lin’an District displayed an increasing trend, and the proportion of severe conflicts increased obviously. Slope is the main factor affecting land-use conflicts in a hilly region and shows a negative correlation, mainly because areas with flat terrain are more conducive to human activities. Based on the characteristics of land-use conflicts in Lin’an District, conflict trade-off mechanisms were proposed to provide a theoretical basis and practical support for land-use conflict management. Our study provides scientific evidence for sustainable land-use planning and ecological management in ecologically fragile areas.

Shrinking cities—cities suffering from population and economic decline—has become a pressing societal issue of worldwide concern. While night-time light (NTL) data have been applied as an important tool for the identification of shrinking cities, the current methods are constrained and biased by the lack of using long-term continuous NTL time series and the use of unidimensional indices. In this study, we proposed a novel method to identify and classify shrinking cities by long-term continuous NTL time series and population data, and applied the method in northeastern China (NEC) from 1996 to 2020. First, we established a long-term consistent NTL time series by applying a geographically weighted regression model to two distinct NTL datasets. Then, we generated NTL index (NI) and population index (PI) by random forest model and the slope of population data, respectively. Finally, we developed a shrinking city index (SCI), based on NI and PI to identify and classify city shrinkage. The results showed that the shrinkage pattern of NEC in 1996–2009 (stage 1) and 2010–2020 (stage 2) was quite different. From stage 1 to stage 2, the shrinkage situation worsened as the number of shrinking cities increased from 102 to 162, and the proportion of severe shrinkage increased from 9.2% to 30.3%. In stage 2, 85.4% of the cities exhibited population decline, and 15.7% of the cities displayed an NTL decrease, suggesting that the changes in NTL and population were not synchronized. Our proposed method provides a robust and long-term characterization of city shrinkage and is beneficial to provide valuable information for sustainable urban planning and decision-making.

Rapid rural social-economic transitions in China have given rise to increasingly serious agricultural eco-environmental (AEE) problems. The deterioration of AEE poses great challenges to the sustainable agriculture and results in an incoordination among rural economy, society and ecology. Coordinating the relationship between rural transition development and AEE has great significance in agricultural sustainability and rural revitalization strategy. However, few studies focus on the interactions between social-economic transitions and AEE in rural areas. In this study, comprehensive index systems were built to assess the levels of rural transition development and AEE in Zhejiang Province, China. Coupling coordination model and Kuznets curve analysis were used to explore the interactive relationship between these two subsystems. The results showed that the level of rural transition development in Zhejiang Province showed an overall uptrend during 2000 and 2018, while the AEE evolved from a rapid decline to a stable trend. Both rural transition development and AEE level exhibited obvious spatial variability. The coupling coordination degree between rural transition development and AEE in the whole region fluctuated upward, and changed from the incoordination state to the basic coordination state. The spatial distribution of coupling coordination degree was characterized by high in the northwestern areas and low in the central and southeastern areas of Zhejiang Province, the majority of coupling coordination type transformed from lagging AEE to lagging rural transition development. The dynamic evolution of the relationship between rural transition development and AEE displayed a U-shaped curve and presented different characteristics at different aspects of rural transition process. These results will provide effective references for promoting the coordinated development between rural social-economic transitions and AEE, and formulating targeted rural revitalization policies to achieve rural sustainability.

Evaluating and revealing the spatial differentiations of quality of rural life (QRL) is the basis for formulating rural revitalization planning to promote rural transformation and achieve common prosperity. Taking the Lin’an District of Hangzhou city in China, an economically developed mountainous area, as an example, this study explored the connotation of QRL from the perspective of common prosperity and constructed a QRL evaluation framework involving living, employment, consumption, and leisure aspects. Then, based on multi-sourced data of 270 administrative villages as the assessment unit, we revealed the spatial patterns of QRL and proposed optimization paths to improving QRL. The results showed that (1) differences in the spatial distribution of quality of rural living, employment, consumption, and leisure of Lin’an District were significant, presenting stepped, block clustering, irregularity, and scattered patterns, respectively. (2) The overall QRL was mainly at a low level, clustered spatially, distributed in a strip pattern, and with obvious road directionality. (3) Based on the evaluation results of QRL, we divided the 270 administrative villages into six types of improvement: livability, employment, consumption, leisure, and balanced and lagged development types. This study could provide a scientific cognitive basis for the improvement of QRL and a useful reference for rural revitalization in China.

Improving the accuracy of cultural ecosystem services (CESs) value assessment and paying more attention to the preferences and trade-offs of stakeholders in the administration of CESs are of vital importance for achieving resilient ecosystem management. Combining methodologies from sociology (Q method) and economics (choice experiment), an assessment framework of CESs is introduced to examine stakeholders’ preferences and willingness to pay to participate in CESs in protected areas so as to explore how the value of CESs in protected areas can be optimized. The results show that the selection of CESs by stakeholders reflects certain synergies and trade-offs. Visitors can be classified as preferring humanistic–natural recreation, aesthetic–sense of place, or environmental education according to the factor ranking of the Q method. Visitors have a higher willingness to pay for humanistic heritage and a lower willingness to pay for sense of place experience, which can be measured at $6.55 per visit and $0.96 per visit, respectively. This indicates that the local customs and characteristics should be further explored and promoted through traditional festival celebrations and farming activities in further development of protected areas, apart from protecting local cultural heritages such as Huizhou ancient villages and halls. Furthermore, it is also necessary to actively explore the synergistic development of CESs, promote social participation, raise stakeholders’ awareness of available services, manage visitors and stakeholders from a demand perspective, and promote the realization of the value of ecological products in protected areas.

Rural landscapes offer a variety of cultural ecosystem services (CESs). However, the relationship between rural landscape characteristics and different CESs is still poorly understood. Therefore, this study explored the rural areas of Huzhou city, China, as a case study to assess the main rural landscape characteristics of different CESs based on public preferences. First, 148 scenic spots were classified into four CESs (physical, experiential, intellectual and inspirational), and the public preferences for each scenic spot were determined by combining tourists' scores obtained from social media and government assessment scores. Then, the landscape characteristic indicators were constructed from the natural, infrastructural and sensory perspectives by combining geographic and social media data. Finally, the random forest model was used to evaluate the public preferences for rural landscape characteristics overall and for different CESs. The word frequency analysis showed that, in addition to the nature landscape, infrastructure and service had a strong influence on public preferences. The relationship with rural landscape characteristics varied across different CESs. For physical CESs, the convenience of infrastructure played a greater role than natural landscape characteristics. Experiential CESs, on the other hand, were affected by natural landscape characteristics themselves. Intellectual CESs had higher requirements for both infrastructure and nature. Inspirational CESs included sensory evaluation indicators, in addition to their focus on natural landscape characteristics and infrastructure, indicating that this category of CESs was more concerned with inner experience. The use of social media data has enriched the dimensions of sensory elements and provided new ideas and information supplements for comprehensively understanding different CESs, thus better supporting the management, planning and protection of rural landscapes.

Understanding the spatiotemporal dynamics of bamboo forests is of critical importance as it characterizes the interaction between forest and agricultural ecosystems and provides essential information for sustainable ecosystem management and decision-making. Thus far, the specific dynamics of moso bamboo (Phyllostachys edulis) and other bamboo are still unknown. In this study, we used temporal information extracted from Landsat time series stacks with Google Earth Engine (GEE) to characterize the spatiotemporal dynamics of bamboo forests, including moso bamboo and other bamboo, in Lin’an County, China, from 2000 to 2019. The bamboo forests were mapped in four periods: the early 2000s (2000–2004), the late 2000s (2005–2009), the early 2010s (2010–2014), and the late 2010s (2015–2019). The overall accuracy of these maps ranged from 97% to 99%. We then analyzed the spatiotemporal dynamics of the bamboo forests at the county and subdistrict/township scales, and probed the bamboo forest gain and loss with respect to the terrain features. Our findings show that bamboo forests increased by 4% from 2000 to 2014, followed by a sharp decrease of 13% in the late 2010s. The decrease was mainly caused by the loss of other bamboo. Approximately 69% of the bamboo forest gain occurred in non-bamboo forest areas, and the rest occupied non-forest areas. Bamboo forest loss was mainly due to conversion into orchard (59%) and forest plantation (22%). Compared to bamboo forest gain, bamboo forest loss was typically observed in areas with lower elevations and steeper slopes. Our study offers spatially explicit and timely insight into bamboo forest changes at the regional scale. The derived maps can be applied to study the drivers, consequences, and future trends of bamboo forest dynamics, which will contribute to sustainable ecosystem management.

Disordered urban expansion has encroached on a large amount of ecological land, resulting in the steady degradation of urban ecology, which has an adverse effect on the sustainable development of the region. An ecological security pattern can effectively control urban expansion, and it is of great significance to balance urban development and ecological protection. In order to analyze the impact of ecological security patterns on urban expansion, Hangzhou was taken as an example, the CA-Markov model and FLUS model were used to simulate the urban expansion pattern in 2030 under the natural development scenario and the ecological security scenario. The results showed that (1) the ecological source area in the study area is 630.90 km2 and was mainly distributed in the western mountainous area. There are 14 ecological corridors, primarily composed of valleys and rivers. Ecological nodes are mainly distributed on the north and south sides of the main urban area. (2) From 2000 to 2018, the annual increase index (AI) of construction land decreased in the northeast and southeast directions but increased in the northwest and southwest directions, and in the northeast direction the value was always the highest. Except for the southwest direction, the average annual growth rate (AGR) of construction land in the other directions decreased. At a distance from the city center of 30 km, AI was relatively higher and was increasing, while AGR was declining. At a distance of 30–45 km, both AI and AGR were increasing, indicating that the focus of construction land was moving outwards. (3) From 2018 to 2030, under both natural development scenario and ecological security scenario, construction land would keep expanding, but the construction land area, proportion, AI, and AGR of the latter would both be smaller than the former, indicating that the ecological security pattern can effectively curb urban expansion. Because of a large amount area of ecological sources, the expansion of construction land in the southwest direction would be constrained, especially under the ecological security scenario. The methods and results of this study can provide theoretical and application references for urban planning and green development in metropolises.

In the context of ecological civilization and food security, identifying and easing conflicts between agricultural and ecological functions are crucial for managing and optimizing territorial space patterns. However, exploring driving mechanisms for conflict changes is relatively rare, and the attention for conflicts between agricultural and ecological functions in the agroforestry ecotone area is limited. Taking Hangzhou, a typical agroforestry ecotone area as an example, this study included resident behavior factors to construct a multi-criteria evaluation system for assessing agricultural and ecological functions during 2000–2019, and probed their conflicts by using an empirical model. Geographic detector model was applied to explore driving factors associated with conflict changes and effects of their interactions on conflict changes. The results showed that agricultural function was strong in the northeastern plain areas and weak in the southwestern mountains areas, and ecological function was opposite to it. Conflict between agricultural and ecological functions became strengthened during 2000–2019. The stronger conflict area had high contiguous degree in the southwestern mountains areas in 2000–2010, and it was mainly distributed in the northern hilly areas and northeastern plain areas in 2010–2019. Among twelve driving factors, ecological protection red line had the greatest impact on conflict changes in 2000 and 2010, and rural settlement density was strongest in 2019. Interaction relationships of all driving factors were bivariate enhanced or nonlinear enhanced. The interaction effect of ecological protection red line and basic farmland protection red line in 2000 was greatest, while that of ecological protection red line and rural settlement density in 2010 and 2019 was the greatest one. This study provides a reference for mitigating conflicts between agricultural and ecological functions in the agroforestry ecotone area and similar areas, and further promotes the coordinated development of territorial space.

Understanding the relationships among multiple land use functions (LUFs) and their influencing factors is conducive to optimizing land spatial patterns and promoting land use sustainability. However, the spatial variations and determinants of trade-offs/synergies among multiple LUFs have not been well studied. This paper proposed a multifaceted framework using multisource data to assess three main LUFs (production, living and ecology function) in Hangzhou city, China. Then, the trade-offs/synergies among multiple LUFs were identified by correlation analysis. The determinants of LUF trade-offs/synergies were then quantified using spatial regression models. The results showed that land production, living and ecology functions in Hangzhou city experienced notable spatiotemporal changes between 2000 and 2018. The trade-off state dominated the relationships among LUFs, and the areas with LUF trade-offs were concentrated mainly in the northeast plain and southwest valley of Hangzhou. Socioeconomic factors, especially land conversion, had the greatest impacts on the trade-offs/synergies among LUFs, followed by physical, location and transportation elements. This study provides a comprehensive and systematic investigation characterizing spatial variations and determinants of trade-offs/synergies among LUFs, and the results can help decision makers in integrating LUF trade-offs/synergies into territorial spatial planning and management.

Ecologically sensitive suburban areas provide important ecosystem services and protect urban ecological security because of their multiple functions in natural and human systems. The research on the ecological environment effects of land use activities in ecologically sensitive suburban areas is important in guiding the healthy and sustainable development of cities. Taking the west suburbs of Hangzhou in China as a case study, we quantified land use changes from Landsat satellite imagery and calculated the value of ecosystem services using the well-established equivalent factor table for land use/cover change (LUCC) and ecosystem services value (ESV). The impacts of LUCC on the ecological environment were analyzed using the transfer matrix of land use and coefficient of elasticity. Results revealed the following. (1) The total ESV in the western suburban area of Hangzhou decreased from $109.95 million in 2000 to $87.09 million in 2016. Moreover, the ESV of gas regulation, climate regulation, soil formation and protection, as well as biodiversity conservation presented a large decrease of more than 25%, especially between 2010 and 2016. (2) The spatial distribution of ESV was high in the west and low in the east. The regions with a significant reduction in ESV were mainly distributed in the eastern town of Wuchang and in Jincheng Town located in the midwest valley. (3) Industrial agglomeration activities in the ecologically sensitive suburban area emerged as the primary factor influencing ESV for various land uses. The elasticity indicator for assessing the responses to ESV changes relative to LUCC showed that 1% of the land conversion in this area resulted in average changes in ESV of 4.1% after the establishment of the industrial agglomeration area. (4) The increase in construction land was associated with a significant decrease in forest area because of the policy of cultivated land requisition&ndash, compensation balance and development strategies for low-slope hilly lands. Consequently, the ESV in the ecologically sensitive suburban areas rapidly declined.

Exploring impacts of urban expansion on ecosystem services has become a hot topic for regional sustainable development, while analyzing the ecological effects of urban expansion forms under different expansion intensities and city sizes is relatively rare. Therefore, taking a typical urban agglomeration, Shanghai-Hangzhou Bay Urban Agglomeration, as a case study, this study first analyzed the dynamics of urban expansion forms (leapfrogging, edge-expansion, and infilling) and four critical ecosystem services (carbon sequestration, food supply, habitat quality, and soil retention) in three periods from 1990 to 2019. The multiple linear regression model and zonal statistics analysis model were used to quantitatively identify the impacts of urban expansion forms on ecosystem services, taking into account different expansion intensities and city sizes. The results showed that the urban expansion trend in the study area experienced a morphological change from integration to diffusion and then to integration in 1990–2019; edge-expansion was the dominant expansion form. Food supply decreased continuously while other ecosystem services had fluctuating changes, and they all had spatial heterogeneity. The leapfrogging, edge-expansion, and infilling all had negative impacts on ecosystem services, and among them, the edge-expansion intensity had the highest influence degree in the early expansion, and the leapfrogging intensity occupied the dominant position in all influences with the expansion of urban scales. For different city sizes, the impact of edge-expansion in large-scale cities was greater than in small-scale cities in the early expansion, and the impact of leapfrogging in large-scale cities exceeded the edge-expansion in the subsequent expansion. These findings will help further understand the influential mechanisms between urban expansion and ecosystem services and provide a scientific basis for formulating reasonable urban planning.

China has experienced the most serious habitat degradation, especially in fast-growing metropolis cities. Although increasing attentions have been brought to this issue, we still lack the understanding of the quantitative impacts of urbanization and landscape pattern on habitats. In this study, we used the “Integrated Valuation of Environmental Services and Trade-off” (InVEST) model to evaluate the habitat quality in Hangzhou city. We further employed spatial auto-correlation to analyze its spatiotemporal pattern variation characteristics. Finally, the ordinary least squares (OLS) and geographically weighted regression (GWR) models were used to explore the impacts of urbanization and landscape pattern change on habitat quality. The results show that the habitat quality index of Hangzhou decreased from 0.608 to 0.577 during 2004–2015, and these areas mainly located around the suburb decreased significantly. The spatial distribution of habitat quality showed significantly positive spatial auto-correlation, and the overall spatial auto-correlation degree of the habitat quality increased during this time. Rapid urbanization has significant negative effects on habitat quality in various areas, while the magnitude and direction of the impacts of landscape pattern on habitat quality differed in time and space. These results provide decision-making criteria for formulating differential urban development policies and landscape management measures for urban ecological sustainability.