变化发展中的中国人文与经济地理学

学科方向与研究领域的确定是学科发展的灵魂。人文与经济地理学是研究领域乃至研究方向均处于变化中的学科,重新认识人文与经济地理学的研究领域与学科方向至关重要。通过梳理几十年来中国人文与经济地理学主要分支学科发展阶段,总结了人文与经济地理学对转型发展社会背景的响应,一方面要坚持学科交叉的性质,以“人-地系统”为理论方向和走理论与实践相结合的道路,另一方面人文与经济地理学者要以新的心态、新的视野,来思考未来发展的重点领域、发展理念以及理论与方法的创新。对长期以来学科涉及到的主要问题,战略性、咨询性、预测性甚至总结经验性（成果表现为发展学科理论）的工作将会逐渐增加,重要性将逐渐显现。阐述了信息化与社会空间经济组织、区域经济新格局与新型城镇化等重要研究领域的发展变化趋势,就“国际热点”与“国际前沿”、理论研究及理论与实践的关系等重要问题的研究理念以提出了新设想,并提出将“人文地理学”改称为“人文与经济地理学”的建议。     

自然的社会建构：西方人文地理学对自然的再认识

自然的社会建构作为西方人文地理学界对自然的再思考,渐成为理解自然与社会互动的重要理论框架,并逐步成为推动人地和谐、可持续发展研究的新范式。通过梳理自然的社会建构研究理论源起并对西方涉及自然的社会建构的研究文献进行全面梳理发现,自然的社会建构并非单纯指基于建构主义视角考察自然的知识生产或价值与意义,还应该关注自然被生产与形构的商品化过程。现有议题主要聚焦于政治与自然、商品化与自然、社会情感与自然以及日常生活与自然四大方面。在此基础上,进一步提出了国内未来研究需要关注的重要方向。     

The return of confiscated land and property in the new Länder: The process and its geographical implications

The unification of Germany has led to claims for the restitution of more than 2.47 million pieces of property confiscated under the auspices of either the Third Reich or the East German government. The legal and administrative taks of restitution is a huge challenge for the new Germany, with far-reaching implications for the country's social and economic fabric. This paper examines the nature and scale of restitution claims and how they are being settled across the five new German states (Bundesländer) and Berlin. It reveals a picture of considerable progress overall, but with substantial regional variations.     

中国农民工聚居区研究进展

作为快速城市化、工业化、相关制度和文化背景等多种因素影响下形成的一种聚落形态,中国农民工聚居区诞生于20世纪80年代。本文在梳理相关研究的基础上,将农民工聚居区研究划分为起步阶段、扩展阶段、社会空间转向和社区治理3个阶段。总体上看,对农民工聚居区的研究,在空间形态方面从静态走向动态,社会网络方面从群体走向空间,形成机制方面从传统的社会学、城市地理学视角转向制度经济学、文化地理学和空间生产视角,聚居区从改造管理走向合作治理,研究方法日益多元化。论文从研究思潮、研究视角、研究重点等方面比较了中国农民工聚居区与西方移民聚居区的差别,并对未来研究作了展望。     

Using an unbaited stationary video system to investigate the behaviour and interactions of bull sharks Carcharhinus leucas under an aquaculture farm

Bull sharks Carcharhinus leucas are common along the coast of Reunion Island (South-West Indian Ocean) and were suspected to aggregate in the vicinity of an aquaculture farm in Saint-Paul Bay on the west coast. In order to understand the behaviour and interaction of bull sharks near aquaculture cages at Saint-Paul Bay, we deployed an experimental unbaited stationary video camera. From 175 hours of recording during daylight hours from March to April 2012, eight individual female bull sharks (seven adults and one immature) were identified based on their natural markings. These sharks were resighted between 3 and 45 times. Residency analysis revealed site attachment under the aquaculture cages for at least three individuals over the course of the study. Recorded behaviours included intraspecific social interactions such as synchronised swimming. Social interactions and relatively strong paired associations for two pairs of females suggest some level of sociality among bull sharks around Reunion Island. Overall, our results demonstrate the utility of unbaited video systems to monitor the behaviour of adult coastal sharks.     

Bottlenose dolphin Tursiops truncatus group dynamics,site fidelity,residency and movement patterns in the Madeira Archipelago (North-East Atlantic)

The bottlenose dolphin Tursiops truncatus is one of the most frequently sighted cetacean species in the Madeira Archipelago (North-East Atlantic); however, little is known about its population ecology in these waters. Photo-identification undertaken during systematic, non-systematic and opportunistic surveys conducted between 2001 and 2012 was used to assess group dynamics, site fidelity, residency and movement patterns of bottlenose dolphins in the archipelago. Three different patterns of residency were assigned, based on individual sighting histories. Group size ranged between 2 and 90 individuals (median 12), with no significant monthly difference in group size. All resident dolphins formed a core, complex network with migrant and transient dolphins. In contrast, satellite clusters were formed exclusively by transient individuals. The lagged identification rate (LIR) model indicated that a dolphin remained in the area for an average of 90 days, whereas the average time an individual spent outside the study area was approximately 313 days. The Madeira Archipelago appears to be only a section of a much larger home range for this population, with the dolphins exhibiting three different patterns of occurrence that associate with each other. The information gained about this poorly studied population contributes to the overall knowledge of bottlenose dolphins in insular oceanic habitats.     

基于VGI的台风灾情评估研究

近年来,在灾害应急的舞台上,一种新的数据来源——自发地理信息(VGI)由于其在海地地震、台风海燕等巨灾中的优异表现逐渐为人们所重视。结合我国实际情况,本文选取了新浪微博上的台风达维的相关数据,从微博的数量和内容分析两个方面初步探讨了VGI在台风灾情评估中的作用,证明了采用VGI数据分析台风灾情具有充分的可行性。     

Latent spatio-temporal activity structures: a new approach to inferring intra-urban functional regions via social media check-in data

Abstract

This article introduces a novel low rank approximation (LRA)-based model to detect the functional regions with the data from about 15 million social media check-in records during a year-long period in Shanghai, China. We identified a series of latent structures, named latent spatio-temporal activity structures. While interpreting these structures, we can obtain a series of underlying associations between the spatial and temporal activity patterns. Moreover, we can not only reproduce the observed data with a lower dimensional representative, but also project spatio-temporal activity patterns in the same coordinate system. With the K-means clustering algorithm, five significant types of clusters that are directly annotated with a combination of temporal activities can be obtained, providing a clear picture of the correlation between the groups of regions and different activities at different times during a day. Besides the commercial and transportation dominant areas, we also detected two kinds of residential areas, the developed residential areas and the developing residential areas. We further interpret the spatial distribution of these clusters using urban form analytics. The results are highly consistent with the government planning in the same periods, indicating that our model is applicable to infer the functional regions from social media check-in data and can benefit a wide range of fields, such as urban planning, public services, and location-based recommender systems.     

社交媒体地理大数据的旅游景点热度分析

针对大数据时代,蕴含地理位置信息的社交媒体(Social Media)数据规模正呈爆炸性增长,通过对这类时空数据的挖掘可以整合用户的群体智慧,发现热门景点或线路,为用户提供更加精细的旅行服务。该文基于2005—2016年Flickr图片分享网站中用户分享的带地理标签的图片信息,通过空间聚类以及文本语义挖掘的方法对北京市的热门景点进行了提取。此外,本文还利用北京市的历史天气信息与用户图片信息进行融合,分析在不同时间、不同天气情景下,不同景点的热度分布规律,可以为旅行爱好者提供热门景点在多种视角下的游览规律。     

Integrating social network data into GISystems

Today, online social media outlets provide new and plentiful sources of data on social networks (SNs) and location-based social networks (LBSNs), i.e., geolocated evidence of connections between individuals. While SNs have been used to show how the magnitude of social connectivity decreases with distance, there are few examples of how to include SNs as layers in a GISystem. If SNs, and thus, interpersonal relationships, could be analyzed in a geographic information system (GIS) setting, we could better model how humans socialize, share information, and form social groups within the complex geographic landscape.

Our goal is to facilitate a guide for analyzing SNs (as derived from online social media, telecommunications, surveys, etc.) within geographic space by combining the mature fields of social network analysis (SNA) and GISystems. First, we describe why modeling socialization in geographic space is essential for understanding human behavior. We then outline best practices and techniques for embedding SN nodes and edges in GISystems by introducing terms like ‘social flow’ and ‘anthrospace’, and categorizations for data and spatial aggregation types. Finally, we explore case study vignettes of SNA within GISystems from diverse regions located in Bolivia, China, Côte d’Ivoire, Singapore, the United Kingdom, and the United States, using concepts such as geolocated dyads, ego–alter relationships, node feature roles, modularity, and network transitivity.