scholarly journals MINING CO-LOCATION PATTERNS FROM SPATIAL DATA

Author(s):  
C. Zhou ◽  
W. D. Xiao ◽  
D. Q. Tang

Due to the widespread application of geographic information systems (GIS) and GPS technology and the increasingly mature infrastructure for data collection, sharing, and integration, more and more research domains have gained access to high-quality geographic data and created new ways to incorporate spatial information and analysis in various studies. There is an urgent need for effective and efficient methods to extract unknown and unexpected information, e.g., co-location patterns, from spatial datasets of high dimensionality and complexity. A co-location pattern is defined as a subset of spatial items whose instances are often located together in spatial proximity. Current co-location mining algorithms are unable to quantify the spatial proximity of a co-location pattern. We propose a co-location pattern miner aiming to discover co-location patterns in a multidimensional spatial data by measuring the cohesion of a pattern. We present a model to measure the cohesion in an attempt to improve the efficiency of existing methods. The usefulness of our method is demonstrated by applying them on the publicly available spatial data of the city of Antwerp in Belgium. The experimental results show that our method is more efficient than existing methods.

Author(s):  
C. Zhou ◽  
W. D. Xiao ◽  
D. Q. Tang

Due to the widespread application of geographic information systems (GIS) and GPS technology and the increasingly mature infrastructure for data collection, sharing, and integration, more and more research domains have gained access to high-quality geographic data and created new ways to incorporate spatial information and analysis in various studies. There is an urgent need for effective and efficient methods to extract unknown and unexpected information, e.g., co-location patterns, from spatial datasets of high dimensionality and complexity. A co-location pattern is defined as a subset of spatial items whose instances are often located together in spatial proximity. Current co-location mining algorithms are unable to quantify the spatial proximity of a co-location pattern. We propose a co-location pattern miner aiming to discover co-location patterns in a multidimensional spatial data by measuring the cohesion of a pattern. We present a model to measure the cohesion in an attempt to improve the efficiency of existing methods. The usefulness of our method is demonstrated by applying them on the publicly available spatial data of the city of Antwerp in Belgium. The experimental results show that our method is more efficient than existing methods.


2008 ◽  
Vol 17 (01) ◽  
pp. 55-70 ◽  
Author(s):  
YAN HUANG ◽  
PUSHENG ZHANG ◽  
CHENGYANG ZHANG

The goal of spatial co-location pattern mining is to find subsets of spatial features frequently located together in spatial proximity. Example co-location patterns include services requested frequently and located together from mobile devices (e.g., PDAs and cellular phones) and symbiotic species in ecology (e.g., Nile crocodile and Egyptian plover). Spatial clustering groups similar spatial objects together. Reusing research results in clustering, e.g. algorithms and visualization techniques, by mapping co-location mining problem into a clustering problem would be very useful. However, directly clustering spatial objects from various spatial features may not yield well-defined co-location patterns. Clustering spatial objects in each layer followed by overlaying the layers of clusters may not applicable to many application domains where the spatial objects in some layers are not clustered. In this paper, we propose a new approach to the problem of mining co-location patterns using clustering techniques. First, we propose a novel framework for co-location mining using clustering techniques. We show that the proximity of two spatial features can be captured by summarizing their spatial objects embedded in a continuous space via various techniques. We define the desired properties of proximity functions compared to similarity functions in clustering. Furthermore, we summarize the properties of a list of popular spatial statistical measures as the proximity functions. Finally, we show that clustering techniques can be applied to reveal the rich structure formed by co-located spatial features. A case study on real datasets shows that our method is effective for mining co-locations from large spatial datasets.


Author(s):  
Z. W. Liu ◽  
B. Wei ◽  
C. L. Kang ◽  
J. W. Jiang

Abstract. As one of the important research directions in the spatial data mining, spatial co-location pattern mining aimed at finding the spatial features whose the instances are frequent co-locate in neighbouring domain. With the introduction of fuzzy sets into traditional spatial co-location pattern mining, the research on fuzzy spatial co-location pattern mining has been deepened continuously, which extends traditional spatial co-location pattern mining to deal with fuzzy spatial objects and discover their laws of spatial symbiosis. In this paper, the operation principle of a classical join-based algorithm for mining spatial co-location patterns is briefly described firstly. Then, combining with the definition of classical participation rate and participation degree, a novel hesitant fuzzy spatial co-location pattern mining algorithm is proposed based on the establishment of the hesitant fuzzy participation rate and hesitant fuzzy participation formula according to the characteristics in fusion of hesitant fuzzy set theory, the score function and spatial co-location pattern mining. Finally, the proposed algorithm is written and implemented based on Python language, which uses a NumPy system to the expansion of the open source numerical calculation. The Python program of the proposed algorithm includes the method of computing hesitant fuzzy membership based on score function, the implementation of generating k-order candidate patterns, k-order frequent patterns and k-order table instances. A hesitant fuzzy spatial co-location pattern mining experiment is carried out and the experimental results show that the proposed and implemented algorithm is effective and feasible.


Author(s):  
G. Zhou ◽  
Q. Li ◽  
G. Deng ◽  
T. Yue ◽  
X. Zhou

The explosive growth of spatial data and widespread use of spatial databases emphasize the need for the spatial data mining. Co-location patterns discovery is an important branch in spatial data mining. Spatial co-locations represent the subsets of features which are frequently located together in geographic space. However, the appearance of a spatial feature C is often not determined by a single spatial feature A or B but by the two spatial features A and B, that is to say where A and B appear together, C often appears. We note that this co-location pattern is different from the traditional co-location pattern. Thus, this paper presents a new concept called clustering terms, and this co-location pattern is called co-location patterns with clustering items. And the traditional algorithm cannot mine this co-location pattern, so we introduce the related concept in detail and propose a novel algorithm. This algorithm is extended by join-based approach proposed by Huang. Finally, we evaluate the performance of this algorithm.


2021 ◽  
Vol 16 (2) ◽  
pp. 167-178
Author(s):  
Simon Pierre Petnga Nyamen

RésuméLe Décret N°2007/115 du 23 avril 2007 portant création de nouveaux Arrondissements au sein de certains Départements du Cameroun traduit a priori la volonté du Gouvernement d’insuffler une dynamique nouvelle à son processus de décentralisation. À partir du cas de la ville de Garoua, ce travail traite des défis et enjeux de la gouvernance locale dans un contexte d’accélération du processus de décentralisation en vue d’un développement maîtrisé. Pour ce faire, des échanges avec vingt-six informateurs issus de l’administration publique et privée, douze chefs de quartier et trente des plus anciens habitants de Garoua ont été mené. En plus, on a eu recours à une centaine d’informateurs et guides, qui ont permis de caractériser trois cent cinquante-cinq marqueurs spatiaux de la dynamique urbaine de la localité. Les résultats de cette étude révèlent que les défis et enjeux actuels de la gouvernance locale sont de trois ordres : règlementaire, financier et fonctionnel. Pour ce qui est du premier ordre, le problème des villes camerounaises, est le non-respect de la règlementation en vigueur, et surtout l’omniprésence de la corruption. Le deuxième ordre est celui de l’incapacité des municipalités à collecter les recettes ce qui ne limite leur investissement qu’à des ouvrages de très faible impact social et économique. Sur le plan fonctionnel, la décentralisation a favorisé la multiplication d’acteurs aux aspirations très souvent divergentes, mais aussi une confusion voire une ignorance des rôles. Au terme de cette étude, avec l’adoption de comportements légaux, il est recommandé aux administrations locales de s’ouvrir au Système d’Information Géographique (SIG) qui dispose des méthodes, techniques et outils permettant de gérer efficacement la donnée spatiale et par conséquent le territoire. De plus, le processus de création de ce système utilisé pour la collecte, le stockage, l’analyse, la modélisation, la gestion, l’affichage et la représentation de l’information spatiale, est une excellente aubaine pour la mise en oeuvre d’un cadre de concertation qui intègre à différentes échelles, la représentativité, les compétences et les objectifs respectifs de toutes les parties prenantes à la gouvernance locale. AbstractDecree N°2007/115 of April 23, 2007 creating new subdivisions within some Divisions of Cameroon demonstrates the will of the Government to improve its decentralization process. Based on the case of the city of Garoua, this work deals with the challenges and issues of local governance, in a context of accelerating the decentralization process with a view to controlled development. To this end, exchanges with twenty-six informants from the public and private administration, twelve chiefdom leaders and thirty of the oldest inhabitants of Garoua were conducted. In addition, about one hundred informants and guides were used, who allowed to characterize three hundred and fifty-five spatial markers of the dynamics of the city. The results revealed that the current challenges and issues of local governance are threefold: regulatory, financial and functional. As for the first, the problem of Cameroonian cities is the non-compliance with the regulations in force, and especially the pervasiveness of corruption. The second order is the inability of municipalities to collect revenue, which limits their investment to works of very low social and economic impact. From a functional point of view, decentralization has favored the multiplication of actors with very divergent aspirations, but also confusion and ignorance of roles. Based on these results, we recommend that local governments open up to Geographic Information System (GIS), which has the methods, techniques and tools to effectively better manage the spatial data and consequently the territory. In addition, the process of creating this system, used for the collection, storage, analysis, modelling, management, display and representation of spatial information, is an important opportunity towards the implementation of a consultation framework that integrates, at different levels, the representativeness, skills and objectives of all stakeholders of local governance on the field.


Filomat ◽  
2018 ◽  
Vol 32 (5) ◽  
pp. 1491-1497 ◽  
Author(s):  
Jiangli Duan ◽  
Wang Lizhen ◽  
Xin Hu ◽  
Hongmei Chen

Spatial co-location pattern mining is an important part of spatial data mining, and its purpose is to discover the coexistence spatial feature sets whose instances are frequently located together in a geographic space. So far, many algorithms of mining spatial co-location pattern and their corresponding expansions have been proposed. However, dynamic co-location patterns have not received attention such as the real meaningful pattern {Ganoderma lucidum new, maple tree dead} means that ?Ganoderma lucidum? grows on the ?maple tree? which was already dead. Therefore, in this paper, we propose the concept of spatial dynamic co-location pattern that can reflect the dynamic relationships among spatial features and then propose an algorithm of mining these patterns from the dynamic dataset of spatial new/dead features. Finally, we conduct extensive experiments and the experimental results demonstrate that spatial dynamic co-location patterns are valuable and our algorithm is effective.


Author(s):  
Shiran Zhou ◽  
Lizhen Wang ◽  
Pingping Wu

There is a variety of interesting knowledge in spatial data sets. Spatial co-location pattern mining can discover sets of different features that are co-located. However, this type of pattern only lists the features that appear together without any consideration of the quantity ratio, which can cause confusion. For example, the co-location pattern church, restaurants shows that churches and restaurants are often close to each other, but information such as how many restaurants are near a church is usually not displayed. Also, in real spatial data sets, there is a mutual influence between spatial features, that is, a coupling relationship between different features or the same features. Thus, this paper proposes a novel spatial pattern called a coupling co-location pattern. First, we discuss the properties of the coupling phenomenon between spatial features, and then the concept of coupling co-location patterns is defined formally. Second, the measurement of support and mining framework for coupling co-location patterns are proposed. Finally, we conduct experiments on both real and synthetic data sets, and the results verify the practical significance of coupling co-location patterns.


2017 ◽  
Vol 9 (1) ◽  
pp. 63
Author(s):  
Kayembe Mpinguyabo ◽  
Kakese Kunyima ◽  
Kanda Nkula

This article presents spatial data related to the quality of school infrastructures in the city of Mbujimayi so as to bring out their characteristics and the typology of quarters which contain these infrastructures. The variables used are presented in the spatial information matrix. The principal components analysis and factorial analysis of correspondences helped make the description of associations based on these variables. The correlation matrix gave birth to channels of the strongest positive correlations (r ≥ 0.60) and resulted in the principal component analysis. The main results are:The cartography of quarters containing schools.The spatial disparity between the variables having degrees of affinity with the location and topography of adequate school site, sanitation, access to public services, and matching buildings. These variables are opposite to those related to unsanitary, localization and indecent topography of the site as well as non-school access to public services.A strong interaction between sanitation and access to public services, including running water and electricity, determining the quality of schools.


2020 ◽  
Vol 19 (33) ◽  
pp. 34-53
Author(s):  
Nives Škreblin

Spatial analyses for the City of Zagreb are mostly produced by the Department for Spatial Information and Research of the Zagreb City Office for Strategic Planning and Development, which is also the coordinator of Zagreb Infrastructure Spatial Data (Croatian acronym: ZIPP). Based on an extensive database, spatial research, analyses, indicators and analytical bases can be accessed for the needs of strategic planners and other users. Examples from practice are described which are publicly available on the web pages of the City of Zagreb, and which were produced at the request of city administrative bodies or private use, from analyses of population density, access to public transport, access to public green spaces, the network of preschool and primary school facilities, strategic city projects, capital investments in buildings for social activities, and public architecture-urbanism tenders, to registering damage after the earthquakes in Zagreb. Spatial analyses provide data which encourage the rational use of spatial resources and informed city administration. New features are interactive web applications with publicly available data which achieve transparency on the part of the city administration. One of the advantages is that they can be refreshed in real time.


Author(s):  
Rafael Sanzio Araújo dos Anjos ◽  
Jose Leandro de Araujo Conceição ◽  
Jõao Emanuel ◽  
Matheus Nunes

The spatial information regarding the use of territory is one of the many strategies used to answer and to inform about what happened, what is happening and what may happen in geographic space. Therefore, the mapping of land use as a communication tool for the spatial data made significant progress in improving sources of information, especially over the last few decades, with new generation remote sensing products for data manipulation.


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