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      Tree-based approach for exploring marine spatial patterns with raster datasets

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      PLoS ONE
      Public Library of Science

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          Abstract

          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.

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          Most cited references27

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          The Definition of El Niño

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            ENSO as an integrating concept in earth science.

            The El Niño-Southern Oscillation (ENSO) cycle of alternating warm El Niño and cold La Niña events is the dominant year-to-year climate signal on Earth. ENSO originates in the tropical Pacific through interactions between the ocean and the atmosphere, but its environmental and socioeconomic impacts are felt worldwide. Spurred on by the powerful 1997-1998 El Niño, efforts to understand the causes and consequences of ENSO have greatly expanded in the past few years. These efforts reveal the breadth of ENSO's influence on the Earth system and the potential to exploit its predictability for societal benefit. However, many intertwined issues regarding ENSO dynamics, impacts, forecasting, and applications remain unresolved. Research to address these issues will not only lead to progress across a broad range of scientific disciplines but also provide an opportunity to educate the public and policy makers about the importance of climate variability and change in the modern world.
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              The role of satellite remote sensing in climate change studies

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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                16 May 2017
                2017
                : 12
                : 5
                : e0177438
                Affiliations
                [1 ]Institute of Geographical Science and Natural Resources Research, Chinese Academy of Sciences, Beijing, P.R. China
                [2 ]Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, P.R. China
                [3 ]Key Laboratory of the Earth Observation, Sanya, Hainan Province, P.R. China
                Centro de Investigacion Cientifica y de Educacion Superior de Ensenada Division de Fisica Aplicada, MEXICO
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                • Conceptualization: XL CX.

                • Formal analysis: CX.

                • Funding acquisition: CX.

                • Investigation: CX.

                • Methodology: FS CX.

                • Project administration: CX.

                • Resources: CX.

                • Software: CX.

                • Supervision: CX.

                • Validation: CX.

                • Writing – original draft: CX XL.

                • Writing – review & editing: XL FS.

                Author information
                http://orcid.org/0000-0003-3605-6578
                Article
                PONE-D-16-29968
                10.1371/journal.pone.0177438
                5433720
                28510602
                13bcc8cf-2e6b-4d35-ae32-ff823903fb3f
                © 2017 Liao et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 9 August 2016
                : 27 April 2017
                Page count
                Figures: 9, Tables: 6, Pages: 19
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 41371385 41671401
                Award Recipient :
                Funded by: State Key Laboratory of Resources and Environmental Information System
                Award Recipient :
                Funded by: National key research and development program of China
                Award ID: 2016YFA0600304
                Award Recipient :
                This study has been funded by National Natural Science Foundation of China with No.41671401 and No. 41371385, by Youth Innovation Promotion Association of Chinese Academy of Science with No.2013113, and by National key research and development program of China with No. 2016YFA0600304. CX received all funding. There was no additional external funding received for this study.
                Categories
                Research Article
                Ecology and Environmental Sciences
                Aquatic Environments
                Marine Environments
                Earth Sciences
                Marine and Aquatic Sciences
                Aquatic Environments
                Marine Environments
                Earth sciences
                Marine and aquatic sciences
                Bodies of water
                Oceans
                Pacific Ocean
                Computer and Information Sciences
                Information Technology
                Data Mining
                Engineering and Technology
                Remote Sensing
                Earth sciences
                Atmospheric science
                Climatology
                El Ni単o-Southern Oscillation
                Earth sciences
                Marine and aquatic sciences
                Oceanography
                El Ni単o-Southern Oscillation
                Computer and Information Sciences
                Geoinformatics
                Remote Sensing Imagery
                Earth Sciences
                Geography
                Geoinformatics
                Remote Sensing Imagery
                Research and Analysis Methods
                Imaging Techniques
                Remote Sensing Imagery
                Engineering and Technology
                Remote Sensing
                Remote Sensing Imagery
                People and Places
                Population Groupings
                Professions
                Scientists
                Earth Sciences
                Marine and Aquatic Sciences
                Oceanography
                Ocean Temperature
                Custom metadata
                All relevant data are within the paper and its Supporting Information files, uploaded as " S1S4 Dataset", and to a stable, public repository Figshare. The relevant DOI is 10.6084/m9.figshare.4275812 [ https://figshare.com/s/e7543298bf406fa3c2b3].

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