Volunteered geographic information (VGI) projects, such as OpenStreetMap (OSM), provide an alternative way to produce geographic data. Research has proven that the resulting data in some areas are of decent quality, which guarantees their usability in various applications. Though these achievements are normally attributed to the huge heterogeneous community mainly consisting of amateurs, it is in fact a small percentage of major contributors who make nearly all contributions. In this paper, we investigate the contributing behaviors of these contributors to deduce whether they are actually professionals. Various indicators are used to depict the behaviors on three themes: practice, skill and motivation, aiming to identify solid evidence for expertise. Our case studies show that most major contributors in Germany, France and the United Kingdom are hardly amateurs, but are professionals instead. These contributors have rich experiences on geographical data editing, have a decent grasp of professional software and work on the project with enthusiasm and concentration. It is less unexpected that they can create geographic data of high quality.

Contribution inequality widely exists in OpenStreetMap (OSM), which means that most data come from a minority of the contributors, while the majority only accounts for a small percentage of data. This phenomenon is of great importance to understanding from where the data come and how the project evolves. The investigation in this paper is dedicated to answering the following questions: How does contribution inequality change over time in OSM? Which group of contributors plays a more important role in influencing trends in contribution inequality: the "vocal minority" or the "silent majority"? To answer the first question, we provide overall measurements for contribution inequality using the Lorenz curve and the Gini coefficient. To answer the second question, we use quantile-based classifying strategy to analyze structural changes in the community, and use the Mann-Whitney-Wilcoxon test to analyze productivity changes. Our case study shows that in countries without significant imports, contributions become more unequal over time. This trend is consistent with the rapid expansion of the silent majority, even though other classes of contributors also grow at a slower pace. On the other hand, contribution inequality fluctuates a lot in countries with huge imports, and agrees well with the productivity changes in the vocal minority.

In efforts to improve regional ecosystem service functions, coordinate land development and ecological conservation, and establish a reference for optimizing land resource allocation and policy formulation to cope with climate change, it is critical to investigate the spatial distribution of land use/cover change (LUCC) and ecosystem services (ESs) under future climate change. This study proposes a framework based on the Shared Socioeconomic Pathway and Representative Concentration Pathway (SSP-RCP), integrating the patch-generating land use simulation (PLUS) model and the integrated valuation of ecosystem services and tradeoffs (InVEST) model to analyze the spatial agglomeration of ESs, to analyze the importance of each driving factors. The results of the study show as follows: (1) the combination of CMIP6 and PLUS models can effectively simulate land use with an overall accuracy of 0.9379. (2) In spatial correlation, ESs show good clustering in all three future scenarios, with similar distribution of cold hotspots in the SSP126 and SSP245 scenarios. Hotspots are more dispersed and cold spots are shifted to the west in the SSP585 scenario. (3) GDP is an important factor in carbon storage and habitat quality, and precipitation has a greater impact on soil retention and water production. Overall, ESs can be increased by appropriately controlling population and economic development, balancing economic development and ecological protection, promoting energy transition, maintaining ecological hotspot areas, and improving cold spot areas.