Typical resource element interpretation method jointly driven by remote sensing big data and geoscience knowledge

Typical resource element interpretation method jointly driven by remote sensing big data and geoscience knowledge

The invention discloses a typical resource element interpretation method jointly driven by remote sensing big data and geoscience knowledge, and the method comprises the steps: obtaining multi-dimensional remote sensing big data, and carrying out the data processing of the multi-dimensional remote s...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: WANG WEI, XIAO RANG, DING CAIZHOU, YANG ZHIBO, CAI LING, HUANG YONG, ZHANG NAN, YU XINHUI
Format: Patent
Sprache:chi ; eng
Schlagworte:
CALCULATING
COMPUTING
COUNTING
PHYSICS
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page
container_issue
container_start_page
container_title
container_volume
creator WANG WEI
XIAO RANG
DING CAIZHOU
YANG ZHIBO
CAI LING
HUANG YONG
ZHANG NAN
YU XINHUI
description The invention discloses a typical resource element interpretation method jointly driven by remote sensing big data and geoscience knowledge, and the method comprises the steps: obtaining multi-dimensional remote sensing big data, and carrying out the data processing of the multi-dimensional remote sensing big data, and obtaining an analysis result; performing spatial data mining of element levels according to an analysis result, and extracting typical resource element attribute features; performing interpretation according to the typical resource element attribute features and a preset knowledge-driven model to obtain a typical resource element classification result, and processing the typical resource element classification result into vector pattern spot data; and comparing the vector pattern spot data with preset annual land change survey data to obtain a classification area accuracy index and an interpretation pattern spot accuracy index. The method can effectively extract remote sensing information in a
format Patent
fullrecord <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_CN117315349A</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>CN117315349A</sourcerecordid><originalsourceid>FETCH-epo_espacenet_CN117315349A3</originalsourceid><addsrcrecordid>eNqNjDEOwjAQBNNQIOAPxwMoooAQJYpAVFTpI2MvweDcGfsA5fek4AFUK41mdlo8myF6awIlZHklC0JAD1byrEgxQY16YeqhN3F0l5GHgVzybzBdhjHsRUEZnD13dPEdOaOGDDvqINl68Hj7YPkEuA7zYnI1IWPx21mxPB6a-rRClBY5GguGtvW5LLdVuanWu331j_MFK_VEgA</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>Typical resource element interpretation method jointly driven by remote sensing big data and geoscience knowledge</title><source>esp@cenet</source><creator>WANG WEI ; XIAO RANG ; DING CAIZHOU ; YANG ZHIBO ; CAI LING ; HUANG YONG ; ZHANG NAN ; YU XINHUI</creator><creatorcontrib>WANG WEI ; XIAO RANG ; DING CAIZHOU ; YANG ZHIBO ; CAI LING ; HUANG YONG ; ZHANG NAN ; YU XINHUI</creatorcontrib><description>The invention discloses a typical resource element interpretation method jointly driven by remote sensing big data and geoscience knowledge, and the method comprises the steps: obtaining multi-dimensional remote sensing big data, and carrying out the data processing of the multi-dimensional remote sensing big data, and obtaining an analysis result; performing spatial data mining of element levels according to an analysis result, and extracting typical resource element attribute features; performing interpretation according to the typical resource element attribute features and a preset knowledge-driven model to obtain a typical resource element classification result, and processing the typical resource element classification result into vector pattern spot data; and comparing the vector pattern spot data with preset annual land change survey data to obtain a classification area accuracy index and an interpretation pattern spot accuracy index. The method can effectively extract remote sensing information in a</description><language>chi ; eng</language><subject>CALCULATING ; COMPUTING ; COUNTING ; PHYSICS</subject><creationdate>2023</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&amp;date=20231229&amp;DB=EPODOC&amp;CC=CN&amp;NR=117315349A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25564,76547</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&amp;date=20231229&amp;DB=EPODOC&amp;CC=CN&amp;NR=117315349A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>WANG WEI</creatorcontrib><creatorcontrib>XIAO RANG</creatorcontrib><creatorcontrib>DING CAIZHOU</creatorcontrib><creatorcontrib>YANG ZHIBO</creatorcontrib><creatorcontrib>CAI LING</creatorcontrib><creatorcontrib>HUANG YONG</creatorcontrib><creatorcontrib>ZHANG NAN</creatorcontrib><creatorcontrib>YU XINHUI</creatorcontrib><title>Typical resource element interpretation method jointly driven by remote sensing big data and geoscience knowledge</title><description>The invention discloses a typical resource element interpretation method jointly driven by remote sensing big data and geoscience knowledge, and the method comprises the steps: obtaining multi-dimensional remote sensing big data, and carrying out the data processing of the multi-dimensional remote sensing big data, and obtaining an analysis result; performing spatial data mining of element levels according to an analysis result, and extracting typical resource element attribute features; performing interpretation according to the typical resource element attribute features and a preset knowledge-driven model to obtain a typical resource element classification result, and processing the typical resource element classification result into vector pattern spot data; and comparing the vector pattern spot data with preset annual land change survey data to obtain a classification area accuracy index and an interpretation pattern spot accuracy index. The method can effectively extract remote sensing information in a</description><subject>CALCULATING</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>PHYSICS</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2023</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNjDEOwjAQBNNQIOAPxwMoooAQJYpAVFTpI2MvweDcGfsA5fek4AFUK41mdlo8myF6awIlZHklC0JAD1byrEgxQY16YeqhN3F0l5GHgVzybzBdhjHsRUEZnD13dPEdOaOGDDvqINl68Hj7YPkEuA7zYnI1IWPx21mxPB6a-rRClBY5GguGtvW5LLdVuanWu331j_MFK_VEgA</recordid><startdate>20231229</startdate><enddate>20231229</enddate><creator>WANG WEI</creator><creator>XIAO RANG</creator><creator>DING CAIZHOU</creator><creator>YANG ZHIBO</creator><creator>CAI LING</creator><creator>HUANG YONG</creator><creator>ZHANG NAN</creator><creator>YU XINHUI</creator><scope>EVB</scope></search><sort><creationdate>20231229</creationdate><title>Typical resource element interpretation method jointly driven by remote sensing big data and geoscience knowledge</title><author>WANG WEI ; XIAO RANG ; DING CAIZHOU ; YANG ZHIBO ; CAI LING ; HUANG YONG ; ZHANG NAN ; YU XINHUI</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN117315349A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2023</creationdate><topic>CALCULATING</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>PHYSICS</topic><toplevel>online_resources</toplevel><creatorcontrib>WANG WEI</creatorcontrib><creatorcontrib>XIAO RANG</creatorcontrib><creatorcontrib>DING CAIZHOU</creatorcontrib><creatorcontrib>YANG ZHIBO</creatorcontrib><creatorcontrib>CAI LING</creatorcontrib><creatorcontrib>HUANG YONG</creatorcontrib><creatorcontrib>ZHANG NAN</creatorcontrib><creatorcontrib>YU XINHUI</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>WANG WEI</au><au>XIAO RANG</au><au>DING CAIZHOU</au><au>YANG ZHIBO</au><au>CAI LING</au><au>HUANG YONG</au><au>ZHANG NAN</au><au>YU XINHUI</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Typical resource element interpretation method jointly driven by remote sensing big data and geoscience knowledge</title><date>2023-12-29</date><risdate>2023</risdate><abstract>The invention discloses a typical resource element interpretation method jointly driven by remote sensing big data and geoscience knowledge, and the method comprises the steps: obtaining multi-dimensional remote sensing big data, and carrying out the data processing of the multi-dimensional remote sensing big data, and obtaining an analysis result; performing spatial data mining of element levels according to an analysis result, and extracting typical resource element attribute features; performing interpretation according to the typical resource element attribute features and a preset knowledge-driven model to obtain a typical resource element classification result, and processing the typical resource element classification result into vector pattern spot data; and comparing the vector pattern spot data with preset annual land change survey data to obtain a classification area accuracy index and an interpretation pattern spot accuracy index. The method can effectively extract remote sensing information in a</abstract><oa>free_for_read</oa></addata></record>
fulltext fulltext_linktorsrc
identifier
ispartof
issn
language chi ; eng
recordid cdi_epo_espacenet_CN117315349A
source esp@cenet
subjects CALCULATING
COMPUTING
COUNTING
PHYSICS
title Typical resource element interpretation method jointly driven by remote sensing big data and geoscience knowledge
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-28T10%3A21%3A43IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-epo_EVB&rft_val_fmt=info:ofi/fmt:kev:mtx:patent&rft.genre=patent&rft.au=WANG%20WEI&rft.date=2023-12-29&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3ECN117315349A%3C/epo_EVB%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true