Titlebook: Semantic Kriging for Spatio-temporal Prediction; Shrutilipi Bhattacharjee,Soumya Kanti Ghosh,Jia Ch Book 2019 Springer Nature Singapore Pt

Influx

爆炸

brachial-plexus

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1860-949X semantic analysis (ontology-based reasoning) of the terrain, and improving predictions using auxiliary knowledge of the terrain..978-981-13-8666-4978-981-13-8664-0Series ISSN 1860-949X Series E-ISSN 1860-9503

和平

Summary and Future Research,ported to be the most efficient choice in many literature. This monograph attempts to incorporate the LULC-based contextual knowledge of the terrain for the interpolation process of the meteorological parameters.

Headstrong

Spatial Interpolation,pular, moderately popular, least popular groups of spatial interpolation methods. The most popular group members can further be chosen for the empirical comparison with the proposed approach. A brief description of each of those methods (of the most popular group) is also presented here.

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Introduction,nt of research challenges. It facilitates enormous availability of spatial data (both in the form of raster and vector) from different sources. This monograph primarily focuses to deal with the incomplete raster satellite imagery of the meteorological parameters and the geostatistical spatial interp

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LOPE

Spatial Semantic Kriging,results. The . considers the semantic properties of the terrain, which is influential to the meteorological parameters and incorporates into the prediction process. One such property is the terrestrial land-use/land-cover (.) distribution. An ontology hierarchy is built with the available . classes

消瘦

Fuzzy Bayesian Semantic Kriging,cover (.) information for the land–atmospheric interaction modeling to achieve better prediction outcome. However, the correlation study between every pair of . classes in . is a-priori, which is not a pragmatic approach. In this a-priori process, the influences of other nearby . classes is ignored