{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T18:43:19Z","timestamp":1772822599106,"version":"3.50.1"},"reference-count":35,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2021,8,13]],"date-time":"2021-08-13T00:00:00Z","timestamp":1628812800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the National Key R&amp;D Program of China","award":["2018YFC0604001-3"],"award-info":[{"award-number":["2018YFC0604001-3"]}]},{"name":"B&amp;R Team of Chinese Academy of Sciences","award":["2017-XBZG-BR-002"],"award-info":[{"award-number":["2017-XBZG-BR-002"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["No.U1803117"],"award-info":[{"award-number":["No.U1803117"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["No.U1803241"],"award-info":[{"award-number":["No.U1803241"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Chinese Academy of Sciences President's International Fellowship Initiative","award":["PIFI Grant No. 2017VCA0002"],"award-info":[{"award-number":["PIFI Grant No. 2017VCA0002"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The spatial calculation of vector data is crucial for geochemical analysis in geological big data. However, large volumes of geochemical data make for inefficient management. Therefore, this study proposed a shapefile storage method based on MongoDB in GeoJSON form (SSMG) and a shapefile storage method based on PostgreSQL with open location code (OLC) geocoding (SSPOG) to solve the problem of low efficiency of electronic form management. The SSMG method consists of a JSONification tier and a cloud storage tier, while the SSPOG method consists of a geocoding tier, an extension tier, and a storage tier. Using MongoDB and PostgreSQL as databases, this study achieved two different types of high-throughput and high-efficiency methods for geochemical data storage and retrieval. Xinjiang, the largest province in China, was selected as the study area in which to test the proposed methods. Using geochemical data from shapefile as a data source, several experiments were performed to improve geochemical data storage efficiency and achieve efficient retrieval. The SSMG and SSPOG methods can be applied to improve geochemical data storage using different architectures, so as to achieve management of geochemical data organization in an efficient way, through time consumed and data compression ratio (DCR), in order to better support geological big data. The purpose of this study was to find ways to build a storage method that can improve the speed of geochemical data insertion and retrieval by using excellent big data technology to help us efficiently solve problem of geochemical data preprocessing and provide support for geochemical analysis.<\/jats:p>","DOI":"10.3390\/rs13163208","type":"journal-article","created":{"date-parts":[[2021,8,13]],"date-time":"2021-08-13T05:34:46Z","timestamp":1628832886000},"page":"3208","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["A Comprehensive Study of Geochemical Data Storage Performance Based on Different Management Methods"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7454-1374","authenticated-orcid":false,"given":"Yinyi","family":"Cheng","sequence":"first","affiliation":[{"name":"State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China"},{"name":"Xinjiang Key Laboratory of Mineral Resources and Digital Geology, Urumqi 830011, China"},{"name":"Xinjiang Research Center for Mineral Resources, Chinese Academy of Sciences, Urumqi 830011, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"Department of Geography, Ghent University, 9000 Ghent, Belgium"},{"name":"Sino-Belgian Joint Laboratory for Geo-Information, Urumqi 830011, China"},{"name":"Sino-Belgian Joint Laboratory for Geo-Information, 9000 Ghent, Belgium"}]},{"given":"Kefa","family":"Zhou","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China"},{"name":"Xinjiang Key Laboratory of Mineral Resources and Digital Geology, Urumqi 830011, China"},{"name":"Xinjiang Research Center for Mineral Resources, Chinese Academy of Sciences, Urumqi 830011, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"given":"Jinlin","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China"},{"name":"Xinjiang Key Laboratory of Mineral Resources and Digital Geology, Urumqi 830011, China"},{"name":"Xinjiang Research Center for Mineral Resources, Chinese Academy of Sciences, Urumqi 830011, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8902-3855","authenticated-orcid":false,"given":"Philippe De","family":"Maeyer","sequence":"additional","affiliation":[{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"Department of Geography, Ghent University, 9000 Ghent, Belgium"},{"name":"Sino-Belgian Joint Laboratory for Geo-Information, Urumqi 830011, China"},{"name":"Sino-Belgian Joint Laboratory for Geo-Information, 9000 Ghent, Belgium"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9324-5087","authenticated-orcid":false,"given":"Tim Van de","family":"Voorde","sequence":"additional","affiliation":[{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"Department of Geography, Ghent University, 9000 Ghent, Belgium"},{"name":"Sino-Belgian Joint Laboratory for Geo-Information, Urumqi 830011, China"},{"name":"Sino-Belgian Joint Laboratory for Geo-Information, 9000 Ghent, Belgium"}]},{"given":"Jining","family":"Yan","sequence":"additional","affiliation":[{"name":"School of Computer Science, China University of Geosciences, Wuhan 430074, China"}]},{"given":"Shichao","family":"Cui","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China"},{"name":"Xinjiang Key Laboratory of Mineral Resources and Digital Geology, Urumqi 830011, China"},{"name":"Xinjiang Research Center for Mineral Resources, Chinese Academy of Sciences, Urumqi 830011, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}]}],"member":"1968","published-online":{"date-parts":[[2021,8,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"357","DOI":"10.1016\/j.gexplo.2011.11.001","article-title":"Exploring the effects of cell size in geochemical mapping","volume":"112","author":"Zuo","year":"2012","journal-title":"J Geochem. 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