Kai Sun

Kai Sun
University at Buffalo, The State University of New York | SUNY Buffalo · Department of Geography

Doctor of Philosophy

About

22
Publications
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253
Citations

Publications

Publications (22)
Article
Full-text available
The potential impacts of climate change on violent conflict are high on the agenda of scholars and policy makers. This article reviews existing literature to clarify the relationship between climate change and conflict risk, focusing on the roles of temperature and precipitation. While some debate remains, substantial evidence shows that climate ch...
Article
Full-text available
Geographical random forest (GRF) is a recently developed and spatially explicit machine learning model. With the ability to provide more accurate predictions and local interpretations, GRF has already been used in many studies. The current GRF model, however, has limitations in its determination of the local model weight and bandwidth hyperparamete...
Article
Place names play an important role in linking physical places to human perception and are highly frequently used in the daily lives of people to refer to places in natural language. However, many place names may not be recorded in typical gazetteers due to their new establishment, colloquial nature, and different concerns. These unrecorded toponyms...
Article
Full-text available
Geoscience knowledge graph (GKG) can organize various geoscience knowledge into a machine understandable and computable semantic network and is an effective way to organize geoscience knowledge and provide knowledge-related services. As a result, it has gained significant attention and become a frontier in geoscience. Geoscience knowledge is derive...
Chapter
Cross-validation (CV) has been widely used in GeoAI research to evaluate the performance of machine learning models. Often, a labeled data set is randomly split into training and validation data, and a machine learning model is trained on the training data and then evaluated on the validation data in an iterative manner. Such a random CV approach c...
Article
Geoscience knowledge graphs (GKGs) formally represent geoscience knowledge in a way of directed graph and have strong capabilities in knowledge representation, openness and interconnectivity, and reasoning and prediction. GKGs have been one of the important infrastructures for the development of combining geoscience and artificial intelligence, the...
Article
Point of interest (POI) data provide digital representations of places in the real world, and have been increasingly used to understand human-place interactions, support urban management, and build smart cities. Many POI datasets have been developed, which often have different geographic coverages, attribute focuses, and data quality. From time to...
Article
Full-text available
Landslide susceptibility assessment is an important means of helping to reduce and manage landslide risk. The existing studies, however, fail to examine the spatially varying relationships between landslide susceptibility and its explanatory factors. This paper investigates the spatial variation in such relationships in Liangshan, China, leveraging...
Article
Full-text available
Geo-parsing, one of the key components of geographical information retrieval, is a process to recognize and geo-locate toponyms mentioned in texts. Such a process can obtain locations contained in toponyms successfully with consistent updating of neural network models and multiple contextual features. The significant offset distance between the geo...
Article
Full-text available
African swine fever (ASF) has spread to many countries in Africa, Europe and Asia in the past decades. However, the potential geographic extent of ASF infection is unknown. Here we combined a modeling framework with the assembled contemporary records of ASF cases and multiple covariates to predict the risk distribution of ASF at a global scale. Loc...
Article
地球科学(以下简称地学)知识图谱具有强大的知识表示和语义推理能力,已成为地学大数据和地学人工智能发展必要的基础设施。然而,目前的地学知识图谱研究主要面向实验场景,缺乏面向实际应用的大规模地学知识图谱构建方法和共享应用框架研究,导致尚未真正在地学领域现实应用中得到使用。为此,本文面向地学大数据和人工智能研究与应用对地学知识图谱的迫切需求,首先研究了大规模地学知识图谱的构建技术,在此基础上,提出一种覆盖地学知识图谱构建、共享和应用全生命周期的总体框架。然后,以“深时数字地球(DDE)”国际大科学计划为例,开展了面向实际应用的知识图谱平台研发实践。最后,利用该平台,构建了DDE大规模地学知识图谱,开展了知识图谱开放共享,有效实现了知识图谱应用,证明本框架可有效支撑大规模地学知识图谱的构建与共享应用...
Article
Full-text available
Toponym recognition is used to extract toponyms from natural language texts, which is a fundamental task of ubiquitous geographic information applications. Existing toponym recognition methods with state‐of‐the‐art performance mainly leverage supervised learning (i.e., deep‐learning‐based approaches) with parameters learned from massive, labeled da...
Article
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In order to understand how related research are evolving to respond to COVID-19 and to facilitate the containment of COVID-19, this paper accurately extracted the spatial and topic information from the metadata of papers related to COVID-19 using text mining techniques, and with the extracted information, the research evolution was analyzed from th...
Article
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Historical maps contain rich geographic information about the past of a region. They are sometimes the only source of information before the availability of digital maps. Despite their valuable content, it is often challenging to access and use the information in historical maps, due to their forms of paper-based maps or scanned images. It is even...
Article
Full-text available
Effective integration and wide sharing of geospatial data is an important and basic premise to facilitate the research and applications of geographic information science. However, the semantic heterogeneity of geospatial data is a major problem that significantly hinders geospatial data integration and sharing. Ontologies are regarded as a promisin...
Article
Full-text available
Geographic knowledge bases (GKBs) with multiple sources and forms are of obvious heterogeneity, which hinders the integration of geographic knowledge. Entity alignment provides an effective way to find correspondences of entities by measuring the multidimensional similarity between entities from different GKBs, thereby overcoming the semantic gap....
Article
数据来源是数据可靠性评价的重要参考因素,是地理空间数据本体的重要研究内容。本文针对来源这一重要的地理空间数据研究对象,系统地分析了地理空间数据来源的涵义,建立了地理空间数据来源本体模型,在此基础上,提出了地理空间数据来源本体的概念体系和来源实体间关系及其实体属性的形式化表达方法,并构建出地理空间数据来源本体。最后以“科技基础性工作专项”项目数据资料为例,基于来源本体库,利用RDF从来源角度实现数据的语义关联,基于web前端框架D3.js技术实现数据与其来源信息的可视化。结果表明,基于来源本体的数据关联可以有效解决数据来源信息描述不规范的问题以及能够支持地学数据语义检索、智能推荐等应用,为促进地学数据共享和数据关联应用提供了一种新方法和新思路。
Article
Full-text available
The complexity of geographic modelling is increasing; hence, preparing data to drive geographic models is becoming a time-consuming and difficult task that may significantly hinder the application of such models. Meanwhile, a huge number of data sets have been shared and have become publicly accessible through the Internet. This study presents a da...
Article
Full-text available
Linked Data is known as one of the best solutions for multisource and heterogeneous web data integration and discovery in this era of Big Data. However, data interlinking, which is the most valuable contribution of Linked Data, remains incomplete and inaccurate. This study proposes a multidimensional and quantitative interlinking approach for Linke...
Article
The semantic heterogeneity of geospatial data is the main bottleneck for the realization of data association, the intelligent recommendation and the accurate discovery of data. Geospatial data ontology is known as an effective approach to solve the semantic heterogeneity of geospatial data. The morphological characteristic is an important feature o...
Conference Paper
Semantic heterogeneity of geospatial data is the main bottleneck for implementing linked data, intelligent recommendation and accurate discovery of data. The ontology theory is an effective way to solve the semantic heterogeneity of data. Morphological Characteristics is the important research content of Semantic heterogeneity of data. This paper m...

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