The Algorithmic Complexity of Landscapes

Papadimitriou, Fivos

doi:10.1080/01426397.2011.650628

Cited by 45 publications

(12 citation statements)

References 36 publications

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“…In the case of route finding, this algorithm also reflects the minimal distance traveled. This is an interesting theoretical problem which refers to the "traveling salesman" problem (that has been proven to be very hard to solve), and to newer approaches dealing with complexity in geographical studies [16,17].…”

Section: Discussionmentioning

confidence: 99%

Using GIS for Determining Variations in Health Access in Jeddah City, Saudi Arabia

Murad

2018

IJGI

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Abstract:The main objective of this paper is to use Geographical Information Systems (GIS) for identifying spatial accessibility to health centers in Jeddah City, Saudi Arabia based on the drive-time analysis technique. A geo-database was created that includes the location of health centers, population distribution, and road networks. ArcGIS Network Analyst and overlay analyses were selected as the analysis tools for this paper. The results of the paper indicate that health centers that are located in the northern districts of Jeddah City have fewer registered patients. There are several areas of Jeddah City that have low accessibility to health centers because they fall outside the 30 min drive-time service area. These are located mainly in western, central, and northern city districts. Local health planners in Jeddah City can use the created application to allocate additional health centers in these less-served districts.

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Section: Discussionmentioning

confidence: 99%

Using GIS for Determining Variations in Health Access in Jeddah City, Saudi Arabia

Murad

2018

IJGI

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“…For the assessment of spatially enabled RDF stores, in which an even higher level of complexity arises [40,41], Kolas [42] proposed and performed a benchmark for the geospatial query capacity of RDF stores; however, since it was proposed before the standardization of GeoSPARQL, not much from that work can be applied to today's developments. Battle and Kolas [43] demonstrated the geospatial capacity of Parliament and successfully ran a number of GeoSPARQL-compliant queries.…”

Section: Assessment and Benchmarking Of Spatially Enabled Rdf Storesmentioning

confidence: 99%

Assessment and Benchmarking of Spatially Enabled RDF Stores for the Next Generation of Spatial Data Infrastructure

Huang

Raza

Mirzov

et al. 2019

IJGI

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Geospatial information is indispensable for various real-world applications and is thus a prominent part of today’s data science landscape. Geospatial data is primarily maintained and disseminated through spatial data infrastructures (SDIs). However, current SDIs are facing challenges in terms of data integration and semantic heterogeneity because of their partially siloed data organization. In this context, linked data provides a promising means to unravel these challenges, and it is seen as one of the key factors moving SDIs toward the next generation. In this study, we investigate the technical environment of the support for geospatial linked data by assessing and benchmarking some popular and well-known spatially enabled RDF stores (RDF4J, GeoSPARQL-Jena, Virtuoso, Stardog, and GraphDB), with a focus on GeoSPARQL compliance and query performance. The tests were performed in two different scenarios. In the first scenario, geospatial data forms a part of a large-scale data infrastructure and is integrated with other types of data. In this scenario, we used ICOS Carbon Portal’s metadata—a real-world Earth Science linked data infrastructure. In the second scenario, we benchmarked the RDF stores in a dedicated SDI environment that contains purely geospatial data, and we used geospatial datasets with both crowd-sourced and authoritative data (the same test data used in a previous benchmark study, the Geographica benchmark). The assessment and benchmarking results demonstrate that the GeoSPARQL compliance of the RDF stores has encouragingly advanced in the last several years. The query performances are generally acceptable, and spatial indexing is imperative when handling a large number of geospatial objects. Nevertheless, query correctness remains a challenge for cross-database interoperability. In conclusion, the results indicate that the spatial capacity of the RDF stores has become increasingly mature, which could benefit the development of future SDIs.

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“…Additionally, a structurally more complex field will naturally lead to more complex membership functions, so that an extracted ECO from this field may have holes and inner boundaries [44]. is a large lake.…”

Section: Element-clustering Objectsmentioning

confidence: 99%

Modeling the Vagueness of Areal Geographic Objects: A Categorization System

Liu

Yuan

Gao

2019

IJGI

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Modeling vague objects with indeterminate boundaries has drawn much attention in geographic information science. Because fields and objects are two perspectives in modeling geographic phenomena, this paper investigates the characteristics of vague regions from the perspective of the field/object dichotomy. Based on the assumption that a vague object can be viewed as the conceptualization of a field, we defined five categories of vague objects: direct field-cutting objects, focal operation-based field-cutting objects, element-clustering objects, object-referenced objects, and dynamic boundary objects. We then established a categorization system to formalize the semantic differences between vague objects using the fuzzy set theory. The proposed framework provides valuable input for the conceptualization, interpretation, and modeling of vague geographical objects.

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The Algorithmic Complexity of Landscapes

Cited by 45 publications

References 36 publications

Using GIS for Determining Variations in Health Access in Jeddah City, Saudi Arabia

Using GIS for Determining Variations in Health Access in Jeddah City, Saudi Arabia

Assessment and Benchmarking of Spatially Enabled RDF Stores for the Next Generation of Spatial Data Infrastructure

Modeling the Vagueness of Areal Geographic Objects: A Categorization System

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