{"id":"https://openalex.org/W2985213746","doi":"https://doi.org/10.3390/ijgi8110512","title":"An Adaptive Construction Method of Hierarchical Spatio-Temporal Index for Vector Data under Peer-to-Peer Networks","display_name":"An Adaptive Construction Method of Hierarchical Spatio-Temporal Index for Vector Data under Peer-to-Peer Networks","publication_year":2019,"publication_date":"2019-11-12","ids":{"openalex":"https://openalex.org/W2985213746","doi":"https://doi.org/10.3390/ijgi8110512","mag":"2985213746"},"language":"en","primary_location":{"id":"doi:10.3390/ijgi8110512","is_oa":true,"landing_page_url":"https://doi.org/10.3390/ijgi8110512","pdf_url":"https://www.mdpi.com/2220-9964/8/11/512/pdf?version=1574249528","source":{"id":"https://openalex.org/S2764431341","display_name":"ISPRS International Journal of Geo-Information","issn_l":"2220-9964","issn":["2220-9964"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ISPRS International Journal of Geo-Information","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2220-9964/8/11/512/pdf?version=1574249528","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101808664","display_name":"Chengming Li","orcid":"https://orcid.org/0000-0002-9438-4871"},"institutions":[{"id":"https://openalex.org/I4210114963","display_name":"Chinese Academy of Surveying and Mapping","ror":"https://ror.org/02j693n47","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114963"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chengming Li","raw_affiliation_strings":["Chinese Academy of Surveying and Mapping, Beijing 100830, China","National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology, Xi\u2019an 710072, China","National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology, Xi'an 710072, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Surveying and Mapping, Beijing 100830, China","institution_ids":["https://openalex.org/I4210114963"]},{"raw_affiliation_string":"National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology, Xi\u2019an 710072, China","institution_ids":[]},{"raw_affiliation_string":"National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology, Xi'an 710072, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101590596","display_name":"Zheng Wu","orcid":"https://orcid.org/0000-0001-7545-5593"},"institutions":[{"id":"https://openalex.org/I4210114963","display_name":"Chinese Academy of Surveying and Mapping","ror":"https://ror.org/02j693n47","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114963"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zheng Wu","raw_affiliation_strings":["Chinese Academy of Surveying and Mapping, Beijing 100830, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Surveying and Mapping, Beijing 100830, China","institution_ids":["https://openalex.org/I4210114963"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031649840","display_name":"Pengda Wu","orcid":"https://orcid.org/0000-0001-5498-1949"},"institutions":[{"id":"https://openalex.org/I4210114963","display_name":"Chinese Academy of Surveying and Mapping","ror":"https://ror.org/02j693n47","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114963"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Pengda Wu","raw_affiliation_strings":["Chinese Academy of Surveying and Mapping, Beijing 100830, China","National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology, Xi\u2019an 710072, China","National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology, Xi'an 710072, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Surveying and Mapping, Beijing 100830, China","institution_ids":["https://openalex.org/I4210114963"]},{"raw_affiliation_string":"National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology, Xi\u2019an 710072, China","institution_ids":[]},{"raw_affiliation_string":"National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology, Xi'an 710072, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100945011","display_name":"Zhanjie Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I4210114963","display_name":"Chinese Academy of Surveying and Mapping","ror":"https://ror.org/02j693n47","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114963"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhanjie Zhao","raw_affiliation_strings":["Chinese Academy of Surveying and Mapping, Beijing 100830, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Surveying and Mapping, Beijing 100830, China","institution_ids":["https://openalex.org/I4210114963"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5031649840"],"corresponding_institution_ids":["https://openalex.org/I4210114963"],"apc_list":{"value":1000,"currency":"CHF","value_usd":1013},"apc_paid":{"value":1000,"currency":"CHF","value_usd":1013},"fwci":0.9373,"has_fulltext":true,"cited_by_count":9,"citation_normalized_percentile":{"value":0.76740079,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":97},"biblio":{"volume":"8","issue":"11","first_page":"512","last_page":"512"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9954000115394592,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10317","display_name":"Advanced Database Systems and Queries","score":0.9922999739646912,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/search-engine-indexing","display_name":"Search engine indexing","score":0.7978842854499817},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7263590693473816},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6522067785263062},{"id":"https://openalex.org/keywords/temporal-database","display_name":"Temporal database","score":0.5605745315551758},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.48946893215179443},{"id":"https://openalex.org/keywords/partition","display_name":"Partition (number theory)","score":0.459676057100296},{"id":"https://openalex.org/keywords/data-structure","display_name":"Data structure","score":0.4516259729862213},{"id":"https://openalex.org/keywords/sort","display_name":"sort","score":0.45007187128067017},{"id":"https://openalex.org/keywords/index","display_name":"Index (typography)","score":0.4307094216346741},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.421161413192749},{"id":"https://openalex.org/keywords/nosql","display_name":"NoSQL","score":0.41875842213630676},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.22437360882759094},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.20277416706085205},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18102514743804932}],"concepts":[{"id":"https://openalex.org/C75165309","wikidata":"https://www.wikidata.org/wiki/Q2258979","display_name":"Search engine indexing","level":2,"score":0.7978842854499817},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7263590693473816},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6522067785263062},{"id":"https://openalex.org/C77277458","wikidata":"https://www.wikidata.org/wiki/Q1969246","display_name":"Temporal database","level":2,"score":0.5605745315551758},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.48946893215179443},{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.459676057100296},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.4516259729862213},{"id":"https://openalex.org/C88548561","wikidata":"https://www.wikidata.org/wiki/Q347599","display_name":"sort","level":2,"score":0.45007187128067017},{"id":"https://openalex.org/C2777382242","wikidata":"https://www.wikidata.org/wiki/Q6017816","display_name":"Index (typography)","level":2,"score":0.4307094216346741},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.421161413192749},{"id":"https://openalex.org/C2779599972","wikidata":"https://www.wikidata.org/wiki/Q82231","display_name":"NoSQL","level":3,"score":0.41875842213630676},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.22437360882759094},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.20277416706085205},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18102514743804932},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3390/ijgi8110512","is_oa":true,"landing_page_url":"https://doi.org/10.3390/ijgi8110512","pdf_url":"https://www.mdpi.com/2220-9964/8/11/512/pdf?version=1574249528","source":{"id":"https://openalex.org/S2764431341","display_name":"ISPRS International Journal of Geo-Information","issn_l":"2220-9964","issn":["2220-9964"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ISPRS International Journal of Geo-Information","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.3390/ijgi8110512","is_oa":true,"landing_page_url":"https://doi.org/10.3390/ijgi8110512","pdf_url":"https://www.mdpi.com/2220-9964/8/11/512/pdf?version=1574249528","source":{"id":"https://openalex.org/S2764431341","display_name":"ISPRS International Journal of Geo-Information","issn_l":"2220-9964","issn":["2220-9964"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ISPRS International Journal of Geo-Information","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1118587163","display_name":"\u90bb\u8fd1\u573a\u7a7a\u95f4\u5173\u7cfb\u7ea6\u675f\u4e0b\u7ebf\u8981\u7d20\u5316\u7b80\u65b9\u6cd5\u7814\u7a76","funder_award_id":"41871375","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2602864607","display_name":null,"funder_award_id":"2018YFB2100700","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2985213746.pdf","grobid_xml":"https://content.openalex.org/works/W2985213746.grobid-xml"},"referenced_works_count":39,"referenced_works":["https://openalex.org/W126394981","https://openalex.org/W220519675","https://openalex.org/W1159236152","https://openalex.org/W1485347932","https://openalex.org/W1545785301","https://openalex.org/W1568832590","https://openalex.org/W1966802228","https://openalex.org/W1967419472","https://openalex.org/W1979919780","https://openalex.org/W1989750313","https://openalex.org/W1990080756","https://openalex.org/W2026532078","https://openalex.org/W2031674781","https://openalex.org/W2055773827","https://openalex.org/W2056521113","https://openalex.org/W2065820792","https://openalex.org/W2087946700","https://openalex.org/W2118744608","https://openalex.org/W2160282283","https://openalex.org/W2165329839","https://openalex.org/W2172041433","https://openalex.org/W2185668855","https://openalex.org/W2197411628","https://openalex.org/W2284646714","https://openalex.org/W2333527583","https://openalex.org/W2389913524","https://openalex.org/W2468622900","https://openalex.org/W2505704932","https://openalex.org/W2509658398","https://openalex.org/W2756684404","https://openalex.org/W2783272959","https://openalex.org/W2882790908","https://openalex.org/W2897711619","https://openalex.org/W2901028997","https://openalex.org/W6676388037","https://openalex.org/W6719538508","https://openalex.org/W6744730832","https://openalex.org/W6818035965","https://openalex.org/W7001097059"],"related_works":["https://openalex.org/W2799973158","https://openalex.org/W2419153746","https://openalex.org/W2923327995","https://openalex.org/W3089119258","https://openalex.org/W2518340158","https://openalex.org/W2997849137","https://openalex.org/W841163430","https://openalex.org/W1756334","https://openalex.org/W2698961929","https://openalex.org/W1554228447"],"abstract_inverted_index":{"Spatio-temporal":[0],"indexing":[1,26,171],"is":[2,111,131,139],"a":[3,95],"key":[4,109],"technique":[5],"in":[6,21,30,127],"spatio-temporal":[7,25,89,97,119,144,153,178,196],"data":[8,29],"storage":[9,192],"and":[10,55,64,107,124,183],"management.":[11],"Indexing":[12],"methods":[13,39],"based":[14,100,150],"on":[15,23,42,101,151],"spatial":[16,43],"filling":[17],"curves":[18],"are":[19],"popular":[20],"research":[22],"the":[24,31,37,51,72,102,105,114,128,143,152,160,169,177],"of":[27,53,87,104,118,122,155,180],"vector":[28,92],"Not":[32],"Relational":[33],"(NoSQL)":[34],"database.":[35],"However,":[36],"existing":[38],"mostly":[40],"focus":[41],"indexing,":[44],"which":[45],"makes":[46],"it":[47,67],"difficult":[48,69],"to":[49,70,141],"balance":[50],"efficiencies":[52],"time":[54],"space":[56],"queries.":[57],"In":[58],"addition,":[59],"for":[60,91],"non-point":[61,125,181],"elements":[62,120,126,182],"(line":[63],"polygon":[65],"elements),":[66],"remains":[68],"determine":[71],"optimal":[73,186],"index":[74,90,137,145,162,187],"level.":[75],"To":[76],"address":[77],"these":[78],"issues,":[79],"this":[80],"paper":[81],"proposes":[82],"an":[83,134],"adaptive":[84,135],"construction":[85],"method":[86,172],"hierarchical":[88],"data.":[93],"Firstly,":[94],"joint":[96,129],"information":[98],"coding":[99,130],"combination":[103],"partition":[106],"sort":[108],"strategies":[110],"presented.":[112],"Secondly,":[113],"multilevel":[115],"expression":[116],"structure":[117],"consisting":[121],"point":[123],"given.":[132],"Finally,":[133],"multi-level":[136],"tree":[138],"proposed":[140,164],"realize":[142],"(Multi-level":[146],"Sphere":[147],"3,":[148],"MLS3)":[149],"characteristics":[154],"geographical":[156],"entities.":[157],"Comparison":[158],"with":[159,198],"XZ3":[161],"algorithm":[163],"by":[165],"GeoMesa":[166],"proved":[167],"that":[168],"MLS3":[170],"not":[173],"only":[174],"reasonably":[175],"expresses":[176],"features":[179],"determines":[184],"their":[185],"level,":[188],"but":[189],"also":[190],"avoids":[191],"hotspots":[193],"while":[194],"achieving":[195],"retrieval":[197],"high":[199],"efficiency.":[200]},"counts_by_year":[{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2020,"cited_by_count":3}],"updated_date":"2026-08-28T12:50:07.497085","created_date":"2025-10-10T00:00:00"}
