A compact city is a special urban form with inherent physical, social, and institutional constraints on greenery that obstruct the achievement of sustainability. In this study, Hong Kong is used as a case to assess the constraints and challenges related to urban green spaces (UGS) development in compact cities. Strategies to overcome these obstacles and improve the UGS conditions are developed. Opportunities to implement the strategies are then evaluated. Because compact cities have extremely limited space allocated for UGS on the ground level, strategies to optimize the layouts of green spaces and seek additional spaces above or below the ground level, such as vertical green surfaces or structures, green roofs, and podiums, are possible solutions. Measures to implement the strategies are summarized as (1) reorganizing the departments and offices related to UGS and clarifying their individual responsibilities to increase their efficiency; (2) encouraging citizen participation; (3) establishing pro...

This study aimed to estimate farmers’ willingness to pay (WTP) for health risk reductions of pesticide use by applying the contingent valuation method (CVM) and to explore the factors that influence farmers’ WTP in China. In total, 244 farmers were randomly selected and interviewed. The mean WTP was estimated to be $65.38 (0.94% of total household income) per household per year for a 5/10,000 reduction in morbidity risk. This study shows that farmers’ socioeconomic and attitudinal factors that significantly affect their WTP include farmers’ farming income, education, household size and risk perceptions. In particular, the results demonstrate that respondents’ social trust, social reciprocity and social networks have significant impacts on their WTP. The findings of this study can provide useful insights for policy makers to design effective policies to address health problems related to pesticide use in the developing world.

Southwest China is the world's largest continuous karst region, where drought events are expected to intensify in the future. Understanding the postdrought recovery of vegetation growth sheds light on the resilience and stability of ecosystems and is of great importance to the sustainable management. However, the effects of the soil properties, beyond the climate variations, on the vegetation postdrought recovery are often overlooked and remain unknown. In this study, we characterized both the patterns and the underlying processes governing the postdrought recovery trajectories of vegetation growth after extreme droughts in karst regions of southwest China. Linear mixed‐effects model analyses revealed that higher mean Normalized Difference Vegetation Index (NDVI) preceding the spring/summer drought leads to shorter drought recovery time for both forests and grasslands, while opposite pattern appears in autumn/winter drought, particularly in forests. Significant effects of precipitation during recovery period were only found in grasslands but not in forests. More importantly, we discovered a crucial impact of the depth to bedrock on vegetation postdrought recovery in forests but not in grasslands, with deeper depth to bedrock associated to a shorter drought recovery. The field capacity is more important for postdrought recovery in karst regions than in nonkarst regions, which can be most likely attributed to differences in the water‐holding capacities and water use strategies of vegetation. Our understanding of the postdrought recovery of vegetation growth in karst regions will facilitate the reasonable prediction of ecosystem resilience and health to extreme climate events in such fragile ecological environments.

Connectivity is a vital element in landscape structure because of its importance in species–landscape interactions. Connectivity analysis of green spaces in urban landscapes, especially in high-density cities such as Hong Kong, differs from that of habitats in natural or rural landscapes. Using the human being as the target species, we formulated with GIS techniques a resistance weight, a structural connectivity index and an ecological barrier effect index to assess connectivity of green spaces. Two factors were included in the modeling, namely the resistance of different land uses related to human activities, and the distance between different urban green spaces. We analyzed the relationships between the connectivity index of green spaces and green cover, elevation, building density and population density. Our results indicate that low connectivity usually occurs in both old and new town centers with high building density and low green cover, and in areas occupied by land uses with a high resistance weight. However, urban density may not necessarily have a negative influence on the structural connectivity of green spaces. Green cover also may not necessarily have positive impact on connectivity if the green spaces have a poor spatial pattern. Adding more green stepping stones, large green spaces and green corridors to form greenways and shortening the distance between urban green spaces can offer a spatial-planning strategy to increase the green space connectivity in Hong Kong. The study provides insights to optimize connectivity of green spaces to improve the urban living environment in high-density metropolises.

Urban parks are key elements of the urban landscape. They provide important ecological, environmental, and social value as well as spaces for outdoor activities to contribute to urban sustainability. Reasonable accessibility is fundamental for people to take full advantage of the benefits of parks. Spatial interaction models are useful in many fields, especially in static systems. The proposed model has been validated for analyzing the accessibility of district parks in Hong Kong. The accessibility index was calculated using the population in catchment zones lying within a walking distance of 400 m, considering the population that the parks serve, the distance between residential areas and parks, the park area, and the facilities and current condition of green spaces in the parks. The results indicate that the index is strongly related to the spatial pattern of residential areas and the shape and spatial pattern of district parks. High accessibility is always associated with parks located in centers of population concentration rather than in the geographical centers of built-up areas. The catchment zones of district parks within walking distance only cover one-fourth of residential areas, and most residents do not have convenient access to reach parks on foot. The district parks were established without much concern for increasing accessibility. No districts have enough district parks to meet the needs of their residents. Future parks should preferably be elongated to serve more nearby residents, especially in extremely compact cities like Hong Kong.

Mapping vegetation cover is critical for understanding and monitoring ecosystem functions in semi-arid biomes. As existing estimates tend to underestimate the woody cover in areas with dry deciduous shrubland and woodland, we present an approach to improve the regional estimation of woody and herbaceous fractional cover in the East Asia steppe. This developed approach uses Random Forest models by combining multiple remote sensing data—training samples derived from high-resolution image in a tailored spatial sampling and model inputs composed of specific metrics from MODIS sensor and ancillary variables including topographic, bioclimatic, and land surface information. We emphasize that effective spatial sampling, high-quality classification, and adequate geospatial information are important prerequisites of establishing appropriate model inputs and achieving high-quality training samples. This study suggests that the optimal models improve estimation accuracy (NMSE 0.47 for woody and 0.64 for herbaceous plants) and show a consistent agreement with field observations. Compared with existing woody estimate product, the proposed woody cover estimation can delineate regions with subshrubs and shrubs, showing an improved capability of capturing spatialized detail of vegetation signals. This approach can be applicable over sizable semi-arid areas such as temperate steppes, savannas, and prairies.