Understanding different cultural ecosystem services: An exploration of rural landscape preferences based on geographic and social media data.

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.

Dynamics of Hierarchical Urban Green Space Patches and Implications for Management Policy.

Accurately quantifying the variation of urban green space is the prerequisite for fully understanding its ecosystem services. However, knowledge about the spatiotemporal dynamics of urban green space is still insufficient due to multiple challenges that remain in mapping green spaces within heterogeneous urban environments. This paper uses the city of Hangzhou to demonstrate an analysis methodology that integrates sub-pixel mapping technology and landscape analysis to fully investigate the spatiotemporal pattern and variation of hierarchical urban green space patches. Firstly, multiple endmember spectral mixture analysis was applied to time series Landsat data to derive green space coverage at the sub-pixel level. Landscape metric analysis was then employed to characterize the variation pattern of urban green space patches. Results indicate that Hangzhou has experienced a significant loss of urban greenness, producing a more fragmented and isolated vegetation landscape. Additionally, a remarkable amelioration of urban greenness occurred in the city core from 2002 to 2013, characterized by the significant increase of small-sized green space patches. The green space network has been formed as a consequence of new urban greening strategies in Hangzhou. These strategies have greatly fragmented the built-up areas and enriched the diversity of the urban landscape. Gradient analysis further revealed a distinct pattern of urban green space landscape variation in the process of urbanization. By integrating both sub-pixel mapping technology and landscape analysis, our approach revealed the subtle variation of urban green space patches which are otherwise easy to overlook. Findings from this study will help us to refine our understanding of the evolution of heterogeneous urban environments.

Multidimensional Evaluation of the Quality of Rural Life Using Big Data from the Perspective of Common Prosperity.

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.

Mapping the fine-scale spatial pattern of artificial light pollution at night in urban environments from the perspective of bird habitats.

The increase in artificial light at night (ALAN) is a global concern, while the pattern of ALAN pollution inside urban areas has not yet been fully explored. To fill this gap, we developed a novel method to map fine-scale ALAN pollution patterns in urban bird habitats using high spatial resolution ALAN satellite data. First, an ALAN pollution map was derived from JL1-3B satellite images. Then, the core habitat nodes (CHNs) representing the main habitats for urban birds to inhabit were identified from the land cover map, which was produced using Gaofen2 (GF2) data, and the high probability corridors (HPCs), indicating high connectivity paths, were derived from Circuitscape software. Finally, the ALAN patterns in the CHNs and HPCs were analysed, and the mismatch index was proposed to evaluate the trade-off between human activity ALAN demands and ALAN supply for the protection of urban birds. The results demonstrated that 115 woodland patches covering 4149.0 ha were selected as CHNs, and most of the CHNs were large urban parks or scenic spots located in the urban fringe. The 2923 modelled HPCs occupying 1179.2 ha were small remaining vegetation patches and vegetated corridors along the major transport arteries. The differences in the ALAN pollution patterns between CHNs and HPCs were mainly determined by the characteristics of the green space patches and the light source types. The polluted regions in the CHNs were clustered in a few regions that suffered from concentrated and intensive ALAN, while most of the CHNs remained unaffected. In contrast, the 727 HPCs were mainly polluted by street lighting was scattered and widely distributed, resulting a more varying influence to birds than that in the CHNs. Relating patterns of the ALAN to bird habitats and connectivity provides meaningful information for comprehensive planning to alleviate the disruptive effects of ALAN pollution.

Carbon emissions induced by land-use and land-cover change from 1970 to 2010 in Zhejiang, China.

Land-use and land-cover change (LUCC) is a crucial factor affecting carbon emissions. Zhejiang Province has witnessed unprecedented LUCC concomitant with rapid urbanization from 1970 to 2010. In this study, remote sensing, geographic information system (GIS) and the Intergovernmental Panel on Climate Change (IPCC) method were combined to quantify changes in both vegetation carbon storage and soil organic carbon (SOC) storage resulting from LUCC during 1970-1990 and 1990-2010. For both 1970-1990 and 1990-2010, the results showed successive decrease in farmlands (2.8 × 105 ha or -9.15% and 5.9 × 105 ha or -20.49%, respectively) and grasslands (3.4 × 104 ha or -10.73% and 1.5 × 105 ha or -54.1%, respectively), and continuous increase in forests (2.0 × 104 ha or 0.33% and 1.7 × 105 ha or 2.81%, respectively) and built-up lands (2.07 × 105 ha or 78.41% and 6.49 × 105 ha or 137.8%, respectively). From 1970 to 1990, approximately 8.3 Tg of the total carbon sink declined, including a 0.4 Tg reduction in vegetation carbon and a 7.9 Tg reduction in SOC. While from 1990 to 2010, approximately 17.5 Tg of carbon storage declined, comprising a 2.8 Tg of carbon accumulated by vegetation, and a 20.3 Tg reduction in SOC. Overall, LUCC has resulted in huge amount of carbon emissions in Zhejiang from 1970 to 2010. Efficient planning for LUCC and gradual mitigation of carbon emissions are indispensable for future urban development in China under increasing pressure from global warming.

Assessing and mapping cultural ecosystem services supply, demand and flow of farmlands in the Hangzhou metropolitan area, China.

Despite research on monitoring and mapping cultural ecosystem services (CESs) increasing exponentially in recent years, our knowledge of the CESs of farmlands is still inadequate, particularly in megacities. Analyzing the CESs of farmlands is a daunting challenge partly due to the lack of appropriate frameworks, and partly because of paucity of information on farmland. In this paper, the maximum entropy (Maxent) model along with agricultural big data were combined to measure and map CESs supply with respect to aesthetics and recreation, within farmlands in the Hangzhou metropolitan area of China between 2010 and 2016. We also quantified the characteristics of CESs based on demand and flow to enhance the understanding of the CESs of farmlands. The results indicated that the Maxent model was robust in mapping CESs supply. Moreover, the farmlands with high aesthetic supply were closely related to natural attributes and mainly distributed in rural areas. In contrast, the farmlands with high recreational supply were highly dependent on human factors which led to the rapid growth of such farmlands near the city center compared to aesthetic farmlands. Farmlands located along water bodies provided high integrated supply, while high demand was characteristic of strongly urbanized areas, and flow patterns of farmlands were greatly affected by popular scenic spots. The growth of CESs supply, demand and flow within farmlands might be closely related to the increase of agritourism, improved infrastructures, increasing income and leisure time of beneficiaries. This study highlighted the importance of the CESs of farmlands in the Hangzhou metropolitan area, although more research is needed to demonstrate the utility of the CESs of farmlands in urban environments.

Identifying the effects of land use change on sediment export: Integrating sediment source and sediment delivery in the Qiantang River Basin, China.

Dramatic land use change caused by the rapid economic development in China has impacted the sediment export dynamics in the large basin. However, how land use change affects sediment export is still poorly understood. This study provided an integrated analysis of the relationships in a "three-level" chain linked as follows: "land use change → changes in sediment source and sediment delivery → sediment export change" for a better understanding. It used the InVEST sediment delivery ratio (SDR) model to analyze the Qiantang River Basin (4.27 ∗ 104 km2), China. Sediment export change was examined from the two perspectives: the effects of land use change on sediment source and on sediment delivery. Correlations between changes in individual land use types and changes in sediment source and sediment delivery were identified. The results indicated that sediment export reduced from 1.69 t ha-1 yr-1 in 1990 to 1.22 t ha-1 yr-1 in 2015 because of the decreased sediment source and a weakened sediment delivery function. In the study area, the conversions of cropland to urban land (urbanization) and bare land to forestland (afforestation) were found to make the major contributions to reductions in soil loss and SDR, respectively. Furthermore, soil loss change resulted in the decreases in total value of sediment export and SDR change caused a large-scale spatial change in sediment export. Our hotspot analysis revealed that the Wuxi River watershed should be targeted for priority conservation to optimize land use/cover for reducing sediment export. This study demonstrates the benefits of taking a comprehensive approach to analyze the processes associated with sediment export change. These allow to improve sediment management and promote aquatic ecosystem health by providing specific future land use recommendations, aimed at source treatment and delivery interception.

Monitoring urban greenness dynamics using multiple endmember spectral mixture analysis.

Urban greenness is increasingly recognized as an essential constituent of the urban environment and can provide a range of services and enhance residents' quality of life. Understanding the pattern of urban greenness and exploring its spatiotemporal dynamics would contribute valuable information for urban planning. In this paper, we investigated the pattern of urban greenness in Hangzhou, China, over the past two decades using time series Landsat-5 TM data obtained in 1990, 2002, and 2010. Multiple endmember spectral mixture analysis was used to derive vegetation cover fractions at the subpixel level. An RGB-vegetation fraction model, change intensity analysis and the concentric technique were integrated to reveal the detailed, spatial characteristics and the overall pattern of change in the vegetation cover fraction. Our results demonstrated the ability of multiple endmember spectral mixture analysis to accurately model the vegetation cover fraction in pixels despite the complex spectral confusion of different land cover types. The integration of multiple techniques revealed various changing patterns in urban greenness in this region. The overall vegetation cover has exhibited a drastic decrease over the past two decades, while no significant change occurred in the scenic spots that were studied. Meanwhile, a remarkable recovery of greenness was observed in the existing urban area. The increasing coverage of small green patches has played a vital role in the recovery of urban greenness. These changing patterns were more obvious during the period from 2002 to 2010 than from 1990 to 2002, and they revealed the combined effects of rapid urbanization and greening policies. This work demonstrates the usefulness of time series of vegetation cover fractions for conducting accurate and in-depth studies of the long-term trajectories of urban greenness to obtain meaningful information for sustainable urban development.

Identification and assessment of potential water quality impact factors for drinking-water reservoirs.

Various reservoirs have been serving as the most important drinking water sources in Zhejiang Province, China, due to the uneven distribution of precipitation and severe river pollution. Unfortunately, rapid urbanization and industrialization have been continuously challenging the water quality of the drinking-water reservoirs. The identification and assessment of potential impacts is indispensable in water resource management and protection. This study investigates the drinking water reservoirs in Zhejiang Province to better understand the potential impact on water quality. Altogether seventy-three typical drinking reservoirs in Zhejiang Province encompassing various water storage levels were selected and evaluated. Using fifty-two reservoirs as training samples, the classification and regression tree (CART) method and sixteen comprehensive variables, including six sub-sets (land use, population, socio-economy, geographical features, inherent characteristics, and climate), were adopted to establish a decision-making model for identifying and assessing their potential impacts on drinking-water quality. The water quality class of the remaining twenty-one reservoirs was then predicted and tested based on the decision-making model, resulting in a water quality class attribution accuracy of 81.0%. Based on the decision rules and quantitative importance of the independent variables, industrial emissions was identified as the most important factor influencing the water quality of reservoirs; land use and human habitation also had a substantial impact on water quality. The results of this study provide insights into the factors impacting the water quality of reservoirs as well as basic information for protecting reservoir water resources.