Spark-based Spatial Association Mining

2018 ◽  
Author(s):  
Kanika Binzani ◽  
Jin Soung Yoo
Keyword(s):  
Spatial Association ◽  
Association Mining

scholarly journals Discovering spatial interaction patterns of near repeat crime by spatial association rules mining

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Zhanjun He ◽  
Liufeng Tao ◽  
Zhong Xie ◽  
Chong Xu
Keyword(s):  
Pattern Mining ◽  
Spatial Interaction ◽  
Spatial Association ◽  
Association Mining ◽  
Interaction Patterns ◽  
Spatio Temporal ◽  
Temporal Interaction ◽  
Near Repeat ◽  
Temporal Interactions ◽  
Spatial Transmission

Abstract Urban crime incidents always exhibit a structure of spatio-temporal dependence. Exploration of the spatio-temporal interactions of crime incidents is critical to understanding the occurrence mechanism and spatial transmission characteristics of crime occurrences, therefore facilitating the determination of policing practices. Although previous researches have repeatedly demonstrated that the crime incidents are spatially clustered, the anisotropic characteristics of spatial interaction has not been fully considered and the detailed spatial transmission of crime incidents has rarely been explored. To better understand the spatio-temporal interaction patterns of crime occurrence, this study proposes a new spatial association mining approach to discover significant spatial transmission routes and related high flow regions. First, all near repeat crime pairs are identified based on spatio-temporal proximity. Then, these links between close pairs are simplified by spatial aggregation on spatial grids. Based on that, measures of the spatio-temporal interactions are defined and a spatial association pattern mining approach is developed to discover significant spatial interaction patterns. Finally, the relationship between significant spatial transmission patterns and road network structure is analyzed. The experimental results demonstrate that our approach is able to effectively discover spatial transmission patterns from massive crime incidents data. Our results are expected to provide effective guidance for crime pattern analysis and even crime prevention.

LISA (Local Indicators of Spatial Association)

2007 ◽  
Vol 36 (3) ◽  
pp. 157-162 ◽  
Author(s):  
Reinhold Kosfeld ◽  
Hans-Friedrich Eckey ◽  
Matthias Türck
Keyword(s):  
Spatial Association

scholarly journals An analysis of the spatial association between deforestation and agricultural field sizes in the tropics and subtropics

PLoS ONE ◽  
2019 ◽  
Vol 14 (1) ◽  
pp. e0209918 ◽  
Author(s):  
Doan K. D. Dang ◽  
Amy C. Patterson ◽  
Luis R. Carrasco
Keyword(s):  
Spatial Association ◽  
Agricultural Field ◽  
The Tropics

scholarly journals Forest Land Quality Evaluation and the Protection Zoning of Subtropical Humid Evergreen Broadleaf Forest Region Based on the PSO-TOPSIS Model and the Local Indicator of Spatial Association: A Case Study of Hefeng County, Hubei Province, China

Forests ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 325
Author(s):  
Li Wang ◽  
Yong Zhou ◽  
Qing Li ◽  
Qian Zuo ◽  
Haoran Gao ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Quality Evaluation ◽  
Spatial Association ◽  
Forest Land ◽  
Mountain Regions ◽  
Land Quality ◽  
Land Protection ◽  
Protection Zones ◽  
Forest Region ◽  
Topsis Model

Forest land is the carrier for growing forests. It is of great significance to evaluate the forest land quality scientifically and delineate forestland protection zones reasonably for realizing better forest land management, promoting ecological civilization construction, and coping with global climate change. In this study, taking Hefeng County, Hubei Province, a subtropical humid evergreen broad-leaved forest region in China, as the study area, 14 indicators were selected from four dimensions—climatic conditions, terrain, soil conditions, and socioeconomics—to construct a forest land quality evaluation index system. Based on the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) model, we introduced the Particle Swarm Optimization (PSO) algorithm to design the evaluation model to evaluate the forest land quality and analyze the distribution of forest land quality in Hefeng. Further, we used the Local Indicator of Spatial Association (LISA) to explore the spatial distribution of forest land quality and delineate the forest land protection zones. The results showed the following: (1) the overall quality of forest land was high, with some variability between regions. The range of Forest Land Quality Index (FLQI) in Hefeng was 0.4091–0.8601, with a mean value of 0.6337. The forest land quality grades were mainly first and second grade, with the higher-grade forest land mainly distributed in the central and southeastern low mountain regions of Zouma, Wuli, and Yanzi. The lower-grade forest land was mainly distributed in the northwestern middle and high mountain regions of Zhongying, Taiping, and Rongmei. (2) The global spatial autocorrelation index of forest land quality in Hefeng County was 0.7562, indicating that the forest land quality in the county had a strong spatial similarity. The spatial distribution of similarity types high-high (HH) and low-low (LL) was more clustered, while the spatial distribution of dissimilarity types high-low (HL) and low-high (LH) was generally dispersed. (3) Based on the LISA of forest land quality, forest land protection zones were divided into three types: key protection zones (KPZs), active protection zones (APZs), and general protection zones (GPZs). The forest land protection zoning basically coincided with the forest land quality. Combining the characteristics of self-correlated types in different forestland protection zones, corresponding management and protection measures were proposed. This showed that the PSO-TOPSIS model can be effectively used for forest land quality evaluation. At the same time, the spatial attributes of forest land were incorporated into the development of forest land protection zoning scheme, which expands the method of forest land protection zoning, and can provide a scientific basis and methodological reference for the reasonable formulation of forest land use planning in Hefeng County, while also serving as a reference for similar regions and countries.

Improved Diagnosis-Medication Association Mining to Reduce Pseudo-associations

2021 ◽  
pp. 106181
Author(s):  
Ching-Huan Wang ◽  
Phung Anh Nguyen ◽  
Yu Chuan (Jack) Li ◽  
Md. Mohaimenul Islam ◽  
Tahmina Nasrin Poly ◽  
...  
Keyword(s):  
Association Mining
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