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Public services equalization is closely related to local economic and social development. Hence, it is crucial to explore the changing dynamics of public services equalization and its correlation with regional economic disparities. We first examine the changing spatiotemporal patterns of public services provision and local economic performance at the provincial level across China from 2003 to 2017, using a set of indicators and the Mann–Kendall test. It is found that different types of public services are divergent in both temporal trend and geographical locations. However, both income and expenditure have been significantly increased for all provinces during the study period. Second, we unravel the heterogeneous relationship between public services provision and local economy across time and space using the geographically and temporally weighted regression. Variance decomposition is further employed to quantify the relative contribution of public services provision to local economy. Results show that the impact of different types of public services on local economic system is divergent, which jointly affects local economy system together with political and other economic factors. Thirdly, we use the Theil index and traditional least square regression to further examine the relationships between public services equalization and regional economic disparities. We find that public services equalization is correlated with regional economic disparities at the national level, yet their interrelation varies significantly in different regions. Taken together, through revisiting the role of public services equalization in regional economic disparities and unpacking its geographical and temporal heterogeneity, this study fills salient research gaps and informs policymaking towards a long-term goal of social equalization.

Today, the marriage between cartographic language and narrative strategies has reshaped maps with the generative capability to represent the intangible historical characters and events involved in social memories following a narrative manner. Despite these advances, rather few efforts have been spared to unveil the potential of tourism maps in a narrative form. This paper seeks to rectify the gaps in this line of research by unfolding the underlying theories and cartographic design guidelines for making narrative tourism maps. In particular, a narrative cartographic design approach is demonstrated and evidenced to be practical using the case of 'Red Boat Spirit Map', a tourism map designed for Jiaxing City, one of the most well-known destinations of China's red tourism. It is believed that the theoretical instrument and cartographic design guidelines presented in our paper are particularly relevant and can be easily adapted to more general research of narrative maps.

Campus tourism has been flourishing across the globe in recent decades. Some universities pioneer the development of campus electronic maps (e-maps) so as to provide more efficient map-based services to visitors. However, existing campus e-maps, regarding the hierarchical ordering of elements and visualization strategies, generally adhere to the approaches designed for urban-scale e-maps, leading to the dilemma that the campus e-maps are limited in practical use. Using the case of Wuhan University in China, this study first presents the methodology for classifying campus e-map elements and organizing the campus e-map zoom levels from the perspective of tourists, further demonstrates the visualization strategies, and finally provides some guidelines for making campus e-maps. This research lays a solid foundation for hierarchically ordering map elements and zoom levels, shedding fresh insights for e-map design.

Heritage tourism has been booming all around the world during the recent past. However, current heritage tourism maps have been locked into the traditional cartographic paradigms in standard formats and are thus incapable of exhibiting the local cultures and the stories behind them. To address this issue, this paper introduces the cultural schema theory into narrative cartographic design and proposes a novel theoretical framework for making heritage tourism maps. We use a typical 'Suzhou Classical Gardens' Narrative Map to demonstrate the usefulness and practicability of the proposed theoretical framework. We finally summarize five cartographic design guidelines for making heritage tourism maps. This study is believed to shed fresh light on cartographic design research.

This paper employed geographically weighted regression (GWR) to characterize the determinants of farmland conversion at administrative scale between 1994 and 2003 across Qiantang watershed, China. Six determinants were identified: total area of forest, distance to highway, distance to second road, distance to river, population, and gross domestic product. Relationships between these identified determinants and farmland conversion showed great spatial non-stationarity, since their character, nature, and strength varied significantly across space. Typically, for cities whose development was heavily relied on road infrastructure development, the impacts of “distance to second road” and “distance to river” was negative. However, in mountainous areas, the restriction of terrain factors led to positive impacts from these two variables. For areas undergoing rapid socio-economic development, farmland conversion was accelerated by population growth and economic development. However, for more urbanized regions, a slow-down rate of farmland conversion would be expected. Our study highlighted that the problem of spatial non-stationarity should be addressed when qualifying the determinants of farmland conversion. Linking our results within the context of farmland protection, we argue that implementing local-specific land management practices, instead of the current one-size-fits-all framework, is the key for the success of farmland protection in China.

Crowdsourcing is essential for real-time map updates. However, low-cost GPS devices often cause issues such as trajectory point deviation and key attribute missing, which reduces the potential application of trajectory data and subsequently impacts the accuracy of map updates and the quality of transportation services. Map-matching algorithms (MMs) are commonly employed to vertically match trajectory points with the road on which the vehicle is traveling, based on characteristics between the trajectory points and urban road network data. Nonetheless, challenges such as relative deviation between trajectory points, overall deviation parallel to the road direction, and abnormal vehicle heading angles still persist, increasing the difficulty of trajectory position correction. Considering the potential of onboard videos in crowdsourced data to reflect the driving environment and attitude changes of vehicles, this study proposes a trajectory quality enhancement method using onboard videos and computer vision technology to address the aforementioned issues. The experimental results indicate that the maximum difference between the estimated angle and the true angle does not exceed 35°. The estimated position can correct over 95% of the local offsets in trajectory points, and the accuracy of trajectory overall positional deviation correction is within 20 m. These findings demonstrate that the proposed method effectively addresses the impacts of angle abnormalities, trajectory point local deviations, and trajectory overall positional deviations on MMs. Furthermore, integrating the proposed method with MMs can significantly enhance trajectory position correction accuracy, which provides valuable technical support and method references for promoting the practical application of map crowdsourcing updates.

The design of tourist maps of historical cities sometimes fails to balance functionality and artistry or does not fully reflect cities' cultural connotations. In this paper, we select Xi'an, China, as a study case and design a tourist map through a spatial narrative to reflect its artistic characteristics in the layout design, color design and symbol design. A few operational suggestions are proposed for improving functionality and artistry in tourist mapping, including variable scales, topological optimization, hand-painted symbols and colors extracted from the architecture of the city.

Rice paddies have been identified as major methane (CH(4)) source induced by human activities. As a major rice production region in Northern China, the rice paddies in the Three-Rivers Plain (TRP) have experienced large changes in spatial distribution over the recent 20 years (from 1990 to 2010). Consequently, accurate estimation and characterization of spatiotemporal patterns of CH₄ emissions from rice paddies has become an pressing issue for assessing the environmental impacts of agroecosystems, and further making GHG mitigation strategies at regional or global levels. Integrating remote sensing mapping with a process-based biogeochemistry model, Denitrification and Decomposition (DNDC), was utilized to quantify the regional CH(4) emissions from the entire rice paddies in study region. Based on site validation and sensitivity tests, geographic information system (GIS) databases with the spatially differentiated input information were constructed to drive DNDC upscaling for its regional simulations. Results showed that (1) The large change in total methane emission that occurred in 2000 and 2010 compared to 1990 is distributed to the explosive growth in amounts of rice planted; (2) the spatial variations in CH₄ fluxes in this study are mainly attributed to the most sensitive factor soil properties, i.e., soil clay fraction and soil organic carbon (SOC) content, and (3) the warming climate could enhance CH₄ emission in the cool paddies. The study concluded that the introduction of remote sensing analysis into the DNDC upscaling has a great capability in timely quantifying the methane emissions from cool paddies with fast land use and cover changes. And also, it confirmed that the northern wetland agroecosystems made great contributions to global greenhouse gas inventory.

Poverty remains one of the most serious chronic dilemmas facing civilization and economic development in the 21st century. How to accurately measure, identify and alleviate poverty have been urgent topics on different geographical scales for decades. Based on census data at the county level from 2000 to 2010 in China, principal component analysis was used to establish an integrated multidimensional poverty index (IMPI) for geographical identification of poverty-stricken counties using an indicators system guided by a sustainable livelihoods framework. Further cluster analysis, spatial analysis and a self-organizing map show obvious spatiotemporal heterogeneity of multidimensional poverty across the 2311 counties in China. The results demonstrate that the counties with higher IMPI are concentrated and conjointly distributed in southwest China, north of central China and southeast of northwest China in mountainous regions and plateaus. Longitudinal comparisons demonstrate that the degree of multidimensional poverty has relatively decreased across China from 2000 to 2010, but regional disparities continue to expand and new aspects are emerging. In addition, compared with 2000, the number of counties with multidimensional poverty in 2010 increased in northeast China and decreased in central China. Many counties have experienced generally increased levels in certain domains of poverty. The relative contribution of each indicator to the IMPI also provides important references for formulating and implementing poverty policy. Quantile regression was utilized to explore the application of the IMPI in assessing environmental inequality. The result indicates that many poverty-stricken and developed counties are exposed to poor air quality. The accurate identification of geographical and spatiotemporal patterns of poverty in China can lead to the implementation of anti-poverty strategies. This paper also offers new insights into poverty measurement for other developing countries.

A comparison of different transportation route types and their combined effects on landscape diversity was conducted within Tiaoxi watershed (China) between 1994 and 2005. Buffer analysis and Mann–Kendall’s test were used to quantify the relationships between distance from transportation routes (railway, highway, national, and provincial road) and a family of landscape diversity parameters (Simpson’s diversity index, Simpson’s evenness index, Shannon’s diversity index, and Shannon’s evenness index). One-way ANOVA was further applied to compare influences from different route types and their combined effects. Five other landscape metrics (patch density, edge density, area-weighted mean shape index, connectance index, and Euclidean nearest neighbor distance) were also calculated to analyze the associations between landscape diversity and landscape pattern characteristics. Results showed that transportation routes exerted significant impacts on landscape diversity. Impact from railway was comparable to that from highway and national road but was more significant than that from provincial road. The spatial influential range of railway and national road was wider than that of highway and provincial road. Combined effects of routes were nonlinear, and impacts from different route types were more complex than those from the same type. The four landscape diversity metrics were comparably effective at the buffer zone scale. In addition, landscape diversity can be alternatively used to indicate fragmentation, connectivity, and isolation at route buffer scale. This study demonstrates an applicable approach to quantitatively characterize the impacts from transportation routes on landscape patterns and has potential to facilitate route network planning.