Spatial Data Mining
نویسنده
چکیده
Spatial Data Mining is the process of finding hidden patterns in a large spatial data set. It can be defined as the nontrivial extraction of implicit, previously unknown, and potentially useful information from data . Spatial data refers to the data that pertains location and spatial dimensions of geographical entities. Some objects have spatial attributes such as positions or areas. An example can be weather data collected for a variety of locations or census data.
منابع مشابه
Assessment of uncertainty for coal quality-tonnage curves through minimum spatial cross-correlation simulation
Coal quality-tonnage curves are helpful tools in optimum mine planning and can be estimated using geostatistical simulation methods. In the presence of spatially cross-correlated variables, traditional co-simulation methods are impractical and time consuming. This paper investigates a factor simulation approach based on minimization of spatial cross-correlations with the objective of modeling s...
متن کاملExploring the Relationships between Spatial and Demographic Parameters and Urban Water Consumption in Esfahan Using Association Rule Mining
In recent years, Iran has faced serious water scarcity and excessive use of water resources. Therefore, exploring the pattern of urban water consumption and the relationships between geographic and demographic parameters and water usage is an important requirement for effective management of water resources. In this study, association rule mining has been used to analyze the data of municipal w...
متن کاملModeling the Prevalence of Avian Influenza in Guilan Province Using Data Mining Models and Spatial Information System in 2016: An Ecological Study
Background and Objectives: Infection of birds to Highly Pathogenic Avian Influenza (HPAI) and their extinction impose heavily losses on the livestock and poultry industry along with public health. Nowadays, due to the volume and variety of data, the need of using location-based technologies and data mining sciences has become inevitable. This study aims to model the prevalence of avian influenz...
متن کاملSpatial modelling of zonality elements based on compositional nature of geochemical data using geostatistical approach: a case study of Baghqloom area, Iran
Due to the existence of a constant sum of constraints, the geochemical data is presented as the compositional data that has a closed number system. A closed number system is a dataset that includes several variables. The summation value of variables is constant, being equal to one. By calculating the correlation coefficient of a closed number system and comparing it with an open number system, ...
متن کاملA Survey on Spatial Association Rule Mining Technique and Algorithms for mining spatial data
spatial association rule mining is an important technique of spatial data mining. Mining spatial association rule is one of the most important branches in the field of spatial data, spatial data mining can extract the spatial patterns and characteristics, general relations of spatial and non spatial data and other data features in common that hidden in spatial database. This paper describes and...
متن کاملA Recent Survey on Knowledge Discovery in Spatial Data Mining
Spatial data mining is the process of discovering, motivating and previously unknown, but potentially helpful patterns from large spatial datasets. Extracting interesting and useful patterns from spatial datasets is more tricky than extracting the parallel patterns from established numeric and definite data due to the complexity of spatial data types, spatial relationships, and spatial autocorr...
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