基于受限汉语的GIS路径重建研究

主要研究基于自然语言 (汉语 )的GIS路径重建问题 ,通过分析带有路径表述信息的汉语文本 ,建立了汉语的NLRP句法模型 ,它是由带有空间语义的动作以及作为动作对象的地理要素构成的集合。考虑到自然语言理解实现的需求 ,论文基于NLRP句法模型定义了受限汉语的NLRP文法 ,在此基础上 ,描述了路径重建算法PRA ,并探讨了算法实现中由于空间认知原因带来的不确定性问题以及其解决方案。最后 ,基于该算法进行了相关实例研究 ,从而验证了该算法的正确性     

Geography Education: The Glass Is Half Full and It's Getting Fuller

This article examines the recent progress of geography education as an academic subfield of geography and as an area of activity in K–12 education. Challenges to both endeavors are described. A restructuring of geography education's research program that focuses on spatial thinking and reasoning and merges applied and theoretical research is proposed.     

A variable precision rough set approach to knowledge discovery in land cover classification

This paper presents a granular computing approach to spatial classification and prediction of land cover classes using rough set variable precision methods. In particular, it presents an approach to characterizing large spatially clustered data sets to discover knowledge in multi-source supervised classification. The evidential structure of spatial classification is founded on the notions of equivalence relations of rough set theory. It allows expressing spatial concepts in terms of approximation space wherein a decision class can be approximated through the partition of boundary regions. The paper also identifies how approximate reasoning can be introduced by using variable precision rough sets in the context of land cover characterization. The rough set theory is applied to demonstrate an empirical application and the predictive performance is compared with popular baseline machine learning algorithms. A comparison shows that the predictive performance of the rough set rule induction is slightly higher than the decision tree and significantly outperforms the baseline models such as neural network, naïve Bayesian and support vector machine methods.     

Identifying geospatial services across heterogeneous taxonomies

Geospatial services with different functions are assembled together to solve complex problems. Different taxonomies are developed to categorize these services into classes. As differences in granularity and semantics exist among these taxonomies, the identification of services across different taxonomies has become a challenge. In this paper, an approach to identify geospatial services across heterogeneous taxonomies is proposed. Using formal concept analysis, existing heterogeneous taxonomies are decomposed into semantic factors and their various combinations. With these semantic factors, a super taxonomy is established to integrate the original heterogeneous taxonomies. Finally, with the super taxonomy as a cross-referencing system, geospatial services with classes in original taxonomies are identifiable across taxonomies. Experiments in service registries and a social media-based spatial-temporal analysis project are presented to illustrate the effectiveness of this approach.     

Modelling tropical cyclone risks for present and future climate change scenarios using geospatial techniques

Tropical cyclones and their devastating impacts are of great concern to coastal communities globally. An appropriate approach integrating climate change scenarios at local scales is essential for producing detailed risk models to support cyclone mitigation measures. This study developed a simple cyclone risk-modelling approach under present and future climate change scenarios using geospatial techniques at local scales, and tested using a case study in Sarankhola Upazila from coastal Bangladesh. Linear storm-surge models were developed up to 100-year return periods. A local sea level rise scenario of 0.34?m for the year 2050 was integrated with surge models to assess the climate change impact. The resultant storm-surge models were used in the risk-modelling procedures. The developed risk models successfully identified the spatial extent and levels of risk that match with actual extent and levels within an acceptable limit of deviation. The result showed that cyclone risk areas increased with the increase of return period. The study also revealed that climate change scenario intensified the cyclone risk area by 5–10% in every return period. The findings indicate this approach has the potential to model cyclone risk in other similar coastal environments for developing mitigation plans and strategies.     

A novel approach to leveraging social media for rapid flood mapping: a case study of the 2015 South Carolina floods

Rapid flood mapping is critical for local authorities and emergency responders to identify areas in need of immediate attention. However, traditional data collection practices such as remote sensing and field surveying often fail to offer timely information during or right after a flooding event. Social media such as Twitter have emerged as a new data source for disaster management and flood mapping. Using the 2015 South Carolina floods as the study case, this paper introduces a novel approach to mapping the flood in near real time by leveraging Twitter data in geospatial processes. Specifically, in this study, we first analyzed the spatiotemporal patterns of flood-related tweets using quantitative methods to better understand how Twitter activity is related to flood phenomena. Then, a kernel-based flood mapping model was developed to map the flooding possibility for the study area based on the water height points derived from tweets and stream gauges. The identified patterns of Twitter activity were used to assign the weights of flood model parameters. The feasibility and accuracy of the model was evaluated by comparing the model output with official inundation maps. Results show that the proposed approach could provide a consistent and comparable estimation of the flood situation in near real time, which is essential for improving the situational awareness during a flooding event to support decision-making.     

Fostering Environmental Sensitivity by Observing Everyday Environments

This study examined the effects of observing and reflecting on everyday environments in the development of environmental sensitivity, defined as a holistic capability composed of predisposition, knowledge, and behavior subdimensions. We encouraged participants to use diverse sources, such as texts, photographs, and animation, to record their observations and thinking. As a result, the activity in this study was beneficial in enhancing students’ environmental sensitivity. Students’ mean scores on the environmental sensitivity questionnaire improved, and their reflective journals reported increased interest in everyday environments, enhanced knowledge about diverse environmental elements, and strengthened will to act pro-environmentally. The usefulness of the geospatial platform was also reported.     

生态地理学概念界定及其经典案例分析

对生态地理学的概念进行了详细讨论和辨析,并将它与相近学科如生物地理学、生态地理区划、宏生态学等进行了比较分析,界定了生态地理学的概念。研究认为：生态地理学是生态学和地理学的交叉学科,是研究生态系统各组分关系和生态过程的地理空间分布格局或/和时间演变规律及其与地理环境耦合机制的学科。生态地理学的目的是揭示不同环境梯度下或不同时间尺度上生态系统各组分关系和生态过程的普适性规律及其成因。同时,结合国内外野外实验平台介绍,在全球变化等研究领域列举了经典案例进行分析：① 全球不同气候带森林凋落物分解和碳汇功能的研究;② 中国不同陆地生态系统碳通量和碳汇功能研究;③ 中国东北样带和南北样带陆地生态系统的脆弱性与适应性研究;④ 中国北方草地样带尺度的生态系统生态学研究。主要目的是在辨析生态地理学概念的基础上指出未来发展方向,推动生态地理学的发展。     

A spatiotemporal calculus for reasoning about land-use trajectories

Earth observation images are a powerful source of data about changes in our planet. Given the magnitude of global environmental changes taking place, it is important that Earth Science researchers have access to spatiotemporal reasoning tools. One area of particular interest is land-use change. Using data obtained from images, researchers would like to express abstractions such as ‘land abandonment’, ‘forest regrowth’, and ‘agricultural intensification’. These abstractions are specific types of land-use trajectories, defined as multi-year paths from one land cover into another. Given this need, this paper introduces a spatiotemporal calculus for reasoning about land-use trajectories. Using Allen’s interval logic as a basis, we introduce new predicates that express cases of recurrence, conversion and evolution in land-use change. The proposed predicates are sufficient and necessary to express different kinds of land-use trajectories. Users can build expressions that describe how humans modify Earth’s terrestrial surface. In this way, scientists can better understand the environmental and economic effects of land-use change.