Open AccessTree-based approach for exploring marine spatial patterns with raster datasets
Author(s) -
Xiaohan Liu,
Xue Chen,
Fenzhen Su
Publication year - 2017
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0177438
Subject(s) - raster graphics , raster data , spatial analysis , spatial ecology , computer science , table (database) , tree (set theory) , node (physics) , common spatial pattern , data mining , matching (statistics) , a priori and a posteriori , remote sensing , geography , artificial intelligence , ecology , mathematics , statistics , biology , mathematical analysis , philosophy , structural engineering , epistemology , engineering
From multiple raster datasets to spatial association patterns, the data-mining technique is divided into three subtasks, i.e., raster dataset pretreatment, mining algorithm design, and spatial pattern exploration from the mining results. Comparison with the former two subtasks reveals that the latter remains unresolved. Confronted with the interrelated marine environmental parameters, we propose a T ree-based A pproach for e X ploring M arine S patial P atterns with multiple raster datasets called TAXMarSP, which includes two models. One is the T ree-based C ascading O rganization M odel (TCOM), and the other is the S patial N eighborhood-based CA lculation M odel (SNCAM). TCOM designs the “Spatial node→Pattern node” from top to bottom layers to store the table-formatted frequent patterns. Together with TCOM, SNCAM considers the spatial neighborhood contributions to calculate the pattern-matching degree between the specified marine parameters and the table-formatted frequent patterns and then explores the marine spatial patterns. Using the prevalent quantification Apriori algorithm and a real remote sensing dataset from January 1998 to December 2014, a successful application of TAXMarSP to marine spatial patterns in the Pacific Ocean is described, and the obtained marine spatial patterns present not only the well-known but also new patterns to Earth scientists.