In Situ Maintenance of Traditional Ecological Knowledge on Malekula Island,Vanuatu

Traditional ecological knowledge (TEK) guides resource management across the globe, but is at risk amid social and ecological change. This has prompted numerous calls for TEK maintenance efforts, but these remain largely unexamined in the literature. Here, we discuss three examples of in situ TEK maintenance from Malekula Island in Vanuatu, locally known as kastom schools. Based on qualitative data, we find that the kastom schools may create several opportunities to maintain TEK (e.g., establishing local control over education), and argue that they represent the creative and adaptive management of tradition in dynamic social–ecological contexts. However, a number of challenges, both practical (e.g., lack of funding) and epistemological (e.g., changing modes of cultural transmission), threaten the efficacy of the kastom schools. We argue that in situ modes of TEK maintenance have promise, but that issues of power and heterogeneity require serious consideration if such measures are to succeed.     

Modeling and representation for earthquake emergency response knowledge: perspective for working with geo-ontology

Earthquake emergency response is one of the three earthquake disaster mitigation work systems in China, already achieving good results in some earthquake disaster mitigation situations. Earthquake emergency plans and emergency command systems are among the most important research and operations components of emergency response. These components commonly come with challenges, such as the pertinence of emergency commands and the operability of the countermeasures to be improved. The promise for solving this problem resides with applying knowledge that aids intelligence creation for decision-making. In this paper, we put forward a conceptual model of knowledge for earthquake disaster emergency response (EDER); compositions of EDER knowledge are introduced within architecture. A modeling method incorporating geo-ontology is used to build basic modeling primitives. Geo-ontology serves to represent geospatial characteristics of the EDER knowledge and addresses a need for semantic interoperability in the modeling process. A decision problem framework and a case study have been used as theoretical framework and an application test, respectively, to evaluate the EDER knowledge architecture and models. The EDER knowledge model provides a foundation for intelligent emergency response that helps solve knowledge problems to improve earthquake disaster response.     

Making a Mark: a computational and visual analysis of one researcher’s intellectual domain

Dr. David Mark is widely regarded as a path-breaking researcher in geographic information science. What are the structural and temporal characteristics of his intellectual contributions, as seen through the eyes of the broader academic community? Aiming to answer that question, this article presents a scientometric analysis of publications that have been cited alongside David Mark’s papers. In deliberate contrast to the widespread focus on using citation data to condense scientific impact into a handful of indicators, the methodological contribution of this study lies in its mix of computational and visualization approaches. In the search for latent domain structures, state-of-the-art practices in information science, bibliometrics, and network visualization are combined and extended. An initial network of 50,000+ publications and 4,000,000+ document co-citations undergoes a series of transformations reducing it to 9000 publications that are then clustered in a two-stage process, leading to 678 communities whose co-citation linkages are used to delineate 19 super-communities. To enable replication of this approach for other studies, much focus in this article is on detailed discussion of that workflow as well as on highlighting the reasoning behind the choices made among data sources and analytical methods. The topical evolution of David Mark’s domain of influence is explored in some detail, based on tabular and graphic representations of extracted community structures. Results confirm not only the enormous overall breadth of his influence but also how lasting and recurrent it has been in some areas.     

构造地理要素趋势面的尺度转换普适性方法探讨

当前的遥感科学面临着遥感数据获取能力与数据应用能力之间突出的供需矛盾。尺度问题作为遥感科学中的关键问题,既限制了遥感作为一门科学向系统性、普适性的发展,又限制了遥感应用能力的发展。本文对定量遥感中的尺度问题进行了梳理,包括:遥感与传统站点观测之间的不一致、不同尺度遥感产品之间的不一致、机理模型的尺度适用问题,以及遥感产品与用户需求时空尺度间的不一致。对遥感中的尺度转换方法展开了讨论,总结了尺度转换的关键问题在于原数据信息量不足时引入额外信息和保留关键信息两方面。提出了构造地理要素趋势面的基本构想,搭建了一个具有普适性的尺度转换方法框架。核心内容是充分利用地表环境要素时间、空间上的信息作为先验知识,通过关联遥感观测新信息和先验趋势面生成指定时空尺度的地表要素产品。     

Does effective climate policy require well-informed citizen support?

Citizen support for climate policies is typically seen as an important criterion in climate policy making. Some studies of climate policy support assume that a significant number of citizens need to be aware of the policies in question and able to provide informed opinions. In this study, we probe this assumption using a web-based survey of residents of the Canadian province of British Columbia (n = 475) by assessing: (1) citizen awareness and knowledge of climate policies, (2) citizen support for different climate policies, (3) the relationship between citizen knowledge and policy support, and (4) the effect of information provision on policy support. Our main finding is that most survey respondents are not aware of any of British Columbia's climate policies, and have little understanding of the potential effect of these on reducing greenhouse gas emissions. Once they are made aware of different types of climate policies, respondents are more likely to express support for regulations, such as the zero-emissions electricity standard and energy efficiency regulations, and less likely to support a carbon tax. Statistical analysis indicates that citizen knowledge of policy is not associated with higher policy support. Furthermore, providing information on likely policy effectiveness to our survey respondents did not translate into higher support, suggesting that widespread knowledge and well-informed citizen support are not necessarily required for implementation of effective climate policies.     

自然资源调查监测技术体系构建的方向与任务

自然资源统一调查监测技术体系（简称《技术体系》）的构建与应用,是建立健全自然资源监管体制、推动资源集约节约利用、促进人与自然和谐共生的一项重要举措,也是一项内容众多、复杂艰巨的科技工程。本文根据自然资源统一调查监测的任务与要求,从调查监测信息过程的整体性特征和工程化业务实施的系统性特征出发,分析了《技术体系》构建所面临的基本问题,提出了基于整体性的《技术体系》的总体架构;继而以协同化数据感知、自动化信息处理、精细化场景管理、智能化知识服务等为主线,论述了《技术体系》的发展方向;然后根据先进性与适用性相结合的要求,分析了《技术体系》的数智化实现路径,提出了“空天地海网”一体化协同感知网络体系构建、信息自动处理平台研发、时空场景模型构建、自然资源时空知识服务系统研发、工程化技术重构等主要研发任务。为了切实地做好该技术体系的构建与推广应用,今后还应进一步加强战略需求分析,推动关键技术创新,促进跨学科交叉研究。     

国际经济地理学研究的知识图谱分析

基于Web of Science核心数据库收录的1982－2020年7 260篇期刊论文及其参考文献,借助CiteSpace绘制国际经济地理学的知识图谱,梳理该领域的知识基础、研究热点和研究前沿。结果发现：1）知识基础的演进轨迹遵循了新区域主义——制度、社会、文化、演化转向的时序变化,21世纪以来,关系、演化经济地理学下的经典文献成为主要的知识来源。2）研究热点突出,创新和增长始终是研究核心,近年来韧性、全球生产网络、金融地理、全球城市、不平等、企业家精神等成为新的研究热点。3）研究前沿具有较强的问题导向,主要基于西方发达国家的产业发展实践。4）研究空间呈现英美主导的两级格局,大部分国家仍处于边缘地带。5）国际经济地理学呈现明显的数字转向、可持续转型趋势,新冠疫情对学科走向也有一定影响。借鉴国际研究经验,中国经济地理学应加强理论创新并提出具有中国实践特色的理论体系,同时推动多学科之间的交叉融合并加强从社会学视角解读社会经济活动的地理学意义。     

基于CiteSpace和VOSviewer的国内半城市化研究可视化分析

随着新型城镇化和国土空间规划工作的推进,半城市化地区的科学发展与治理已成为城乡融合发展的重要环节。基于文献计量分析方法,运用CiteSpace和VOSviewer可视化工具,对近30年来国内半城市化研究进行知识图谱分析。结果表明：1）作者与机构研究力量分散,地域分布特征明显;2）研究热点聚焦于分析北京、广州、上海等发达城市的土地利用、景观格局、失地农民、影响因素等问题,其内容可聚类为形态特征、空间界定、驱动机制、协调发展4类主题;3）半城市化研究发展经历了3个阶段,研究区域从东南沿海向内陆转移,内容从定性理论分析向定量实证探讨转化,视角也由自然特性分析向社会发展研究转变,体现出更多人文关怀。最后,从半城市化地区空间范围界定、人居环境建设、农业转移人口市民化路径探讨和基本公共服务均等化实施4个方面进行展望,旨在为中国半城市化地区的发展提供参考。     

国外儿童地理学研究进展与启示

20世纪70至80年代,在地理学“空间转向”的背景下,国外儿童地理学研究兴起。2003年Children’s Geographies诞生,成为儿童地理学的旗帜性刊物,标志着儿童地理学的发展进入新阶段。借助可视化工具,系统梳理国外儿童地理学研究的核心主题、研究热点以及研究方法。研究发现：（1）国外儿童地理学的科研人员、科研机构以及研究所属区域都呈现高度集中性,欧美国家占据主导地位;（2）核心研究主题包括移民与流动身份、伦理与地区差异、教育与青年志向、童年与多元空间以及游戏与情感体验等;（3）亚洲儿童地理研究成为近期研究热点,聚焦于“跨国儿童移民”以及“亚洲青年教育及就业问题”两部分;（4）研究方法历经探索期、发展期、繁盛期以及信息技术广泛应用时期的演进,技术手段随时代发展不断更新。     

Bayesian area-to-point kriging using expert knowledge as informative priors

Area-to-point (ATP) kriging is a common geostatistical framework to address the problem of spatial disaggregation or downscaling from block support observations (BSO) to point support (PoS) predictions for continuous variables. This approach requires that the PoS variogram is known. Without PoS observations, the parameters of the PoS variogram cannot be deterministically estimated from BSO, and as a result, the PoS variogram parameters are uncertain. In this research, we used Bayesian ATP conditional simulation to estimate the PoS variogram parameters from expert knowledge and BSO, and quantify uncertainty of the PoS variogram parameters and disaggregation outcomes. We first clarified that the nugget parameter of the PoS variogram cannot be estimated from only BSO. Next, we used statistical expert elicitation techniques to elicit the PoS variogram parameters from expert knowledge. These were used as informative priors in a Bayesian inference of the PoS variogram from BSO and implemented using a Markov chain Monte Carlo algorithm. ATP conditional simulation was done to obtain stochastic simulations at point support. MODIS (Moderate Resolution Imaging Spectroradiometer) atmospheric temperature profile data were used in an illustrative example. The outcomes from the Bayesian ATP inference for the Matérn variogram model parameters confirmed that the posterior distribution of the nugget parameter was effectively the same as its prior distribution; for the other parameters, the uncertainty was substantially decreased when BSO were introduced to the Bayesian ATP estimator. This confirmed that expert knowledge brought new information to infer the nugget effect at PoS while BSO only brought new information to infer the other parameters. Bayesian ATP conditional simulations provided a satisfactory way to quantify parameters and model uncertainty propagation through spatial disaggregation.