Remote sensing intelligent extraction method for disturbance range of large-scale artificial water and soil loss

The invention discloses a large-scale artificial water and soil loss disturbance range remote sensing intelligent extraction method, which comprises the following steps of: firstly, acquiring time sequence multi-mode remote sensing image data before and after artificial water and soil loss disturban...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: WEN QINGKE, CHOI SHI-AE, ZHANG XIAOXUE, TAN JIEJUN, WANG JINGLANG, JIANG WEI, PANG ZHIGUO, AVANGLIE, LIU SHUO, LIU CHANGJUN
Format: Patent
Sprache:chi ; eng
Schlagworte:
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 WEN QINGKE
CHOI SHI-AE
ZHANG XIAOXUE
TAN JIEJUN
WANG JINGLANG
JIANG WEI
PANG ZHIGUO
AVANGLIE
LIU SHUO
LIU CHANGJUN
description The invention discloses a large-scale artificial water and soil loss disturbance range remote sensing intelligent extraction method, which comprises the following steps of: firstly, acquiring time sequence multi-mode remote sensing image data before and after artificial water and soil loss disturbance in a supervision range, and performing high-precision registration on the time sequence multi-mode remote sensing image data to obtain a time sequence remote sensing image set; then constructing an artificial water and soil loss multi-modal remote sensing optimization feature set fused with a visual attention mechanism according to the time sequence remote sensing image set; and finally, performing remote sensing intelligent extraction on an artificial water and soil loss disturbance range in a supervision range based on an LSP graph convolutional neural network according to the artificial water and soil loss multi-mode remote sensing optimization feature set. The invention provides an artificial water and soil
format Patent
fullrecord <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_CN116580320A</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>CN116580320A</sourcerecordid><originalsourceid>FETCH-epo_espacenet_CN116580320A3</originalsourceid><addsrcrecordid>eNqNyjEKwkAQBdA0FqLeYTxAIBoUWwmKlYXYh3HzEwc2s2FnRI9v4wGsXvPmxXTDmBxkUBMdSNQRowxQJ3w8c3BJSiP8mTrqU6ZOzF_5wRpAmXUApZ4i5wGlBY4gzi69BOFIb3ZkYu3IkkSKyWxZzHqOhtXPRbE-n-7NpcSUWtjEAQpvm-tms98dqnpbHet_zhesVUOy</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>Remote sensing intelligent extraction method for disturbance range of large-scale artificial water and soil loss</title><source>esp@cenet</source><creator>WEN QINGKE ; CHOI SHI-AE ; ZHANG XIAOXUE ; TAN JIEJUN ; WANG JINGLANG ; JIANG WEI ; PANG ZHIGUO ; AVANGLIE ; LIU SHUO ; LIU CHANGJUN</creator><creatorcontrib>WEN QINGKE ; CHOI SHI-AE ; ZHANG XIAOXUE ; TAN JIEJUN ; WANG JINGLANG ; JIANG WEI ; PANG ZHIGUO ; AVANGLIE ; LIU SHUO ; LIU CHANGJUN</creatorcontrib><description>The invention discloses a large-scale artificial water and soil loss disturbance range remote sensing intelligent extraction method, which comprises the following steps of: firstly, acquiring time sequence multi-mode remote sensing image data before and after artificial water and soil loss disturbance in a supervision range, and performing high-precision registration on the time sequence multi-mode remote sensing image data to obtain a time sequence remote sensing image set; then constructing an artificial water and soil loss multi-modal remote sensing optimization feature set fused with a visual attention mechanism according to the time sequence remote sensing image set; and finally, performing remote sensing intelligent extraction on an artificial water and soil loss disturbance range in a supervision range based on an LSP graph convolutional neural network according to the artificial water and soil loss multi-mode remote sensing optimization feature set. The invention provides an artificial water and soil</description><language>chi ; eng</language><subject>CALCULATING ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; 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=20230811&amp;DB=EPODOC&amp;CC=CN&amp;NR=116580320A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,776,881,25542,76290</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&amp;date=20230811&amp;DB=EPODOC&amp;CC=CN&amp;NR=116580320A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>WEN QINGKE</creatorcontrib><creatorcontrib>CHOI SHI-AE</creatorcontrib><creatorcontrib>ZHANG XIAOXUE</creatorcontrib><creatorcontrib>TAN JIEJUN</creatorcontrib><creatorcontrib>WANG JINGLANG</creatorcontrib><creatorcontrib>JIANG WEI</creatorcontrib><creatorcontrib>PANG ZHIGUO</creatorcontrib><creatorcontrib>AVANGLIE</creatorcontrib><creatorcontrib>LIU SHUO</creatorcontrib><creatorcontrib>LIU CHANGJUN</creatorcontrib><title>Remote sensing intelligent extraction method for disturbance range of large-scale artificial water and soil loss</title><description>The invention discloses a large-scale artificial water and soil loss disturbance range remote sensing intelligent extraction method, which comprises the following steps of: firstly, acquiring time sequence multi-mode remote sensing image data before and after artificial water and soil loss disturbance in a supervision range, and performing high-precision registration on the time sequence multi-mode remote sensing image data to obtain a time sequence remote sensing image set; then constructing an artificial water and soil loss multi-modal remote sensing optimization feature set fused with a visual attention mechanism according to the time sequence remote sensing image set; and finally, performing remote sensing intelligent extraction on an artificial water and soil loss disturbance range in a supervision range based on an LSP graph convolutional neural network according to the artificial water and soil loss multi-mode remote sensing optimization feature set. The invention provides an artificial water and soil</description><subject>CALCULATING</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</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>eNqNyjEKwkAQBdA0FqLeYTxAIBoUWwmKlYXYh3HzEwc2s2FnRI9v4wGsXvPmxXTDmBxkUBMdSNQRowxQJ3w8c3BJSiP8mTrqU6ZOzF_5wRpAmXUApZ4i5wGlBY4gzi69BOFIb3ZkYu3IkkSKyWxZzHqOhtXPRbE-n-7NpcSUWtjEAQpvm-tms98dqnpbHet_zhesVUOy</recordid><startdate>20230811</startdate><enddate>20230811</enddate><creator>WEN QINGKE</creator><creator>CHOI SHI-AE</creator><creator>ZHANG XIAOXUE</creator><creator>TAN JIEJUN</creator><creator>WANG JINGLANG</creator><creator>JIANG WEI</creator><creator>PANG ZHIGUO</creator><creator>AVANGLIE</creator><creator>LIU SHUO</creator><creator>LIU CHANGJUN</creator><scope>EVB</scope></search><sort><creationdate>20230811</creationdate><title>Remote sensing intelligent extraction method for disturbance range of large-scale artificial water and soil loss</title><author>WEN QINGKE ; CHOI SHI-AE ; ZHANG XIAOXUE ; TAN JIEJUN ; WANG JINGLANG ; JIANG WEI ; PANG ZHIGUO ; AVANGLIE ; LIU SHUO ; LIU CHANGJUN</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN116580320A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2023</creationdate><topic>CALCULATING</topic><topic>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>PHYSICS</topic><toplevel>online_resources</toplevel><creatorcontrib>WEN QINGKE</creatorcontrib><creatorcontrib>CHOI SHI-AE</creatorcontrib><creatorcontrib>ZHANG XIAOXUE</creatorcontrib><creatorcontrib>TAN JIEJUN</creatorcontrib><creatorcontrib>WANG JINGLANG</creatorcontrib><creatorcontrib>JIANG WEI</creatorcontrib><creatorcontrib>PANG ZHIGUO</creatorcontrib><creatorcontrib>AVANGLIE</creatorcontrib><creatorcontrib>LIU SHUO</creatorcontrib><creatorcontrib>LIU CHANGJUN</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>WEN QINGKE</au><au>CHOI SHI-AE</au><au>ZHANG XIAOXUE</au><au>TAN JIEJUN</au><au>WANG JINGLANG</au><au>JIANG WEI</au><au>PANG ZHIGUO</au><au>AVANGLIE</au><au>LIU SHUO</au><au>LIU CHANGJUN</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Remote sensing intelligent extraction method for disturbance range of large-scale artificial water and soil loss</title><date>2023-08-11</date><risdate>2023</risdate><abstract>The invention discloses a large-scale artificial water and soil loss disturbance range remote sensing intelligent extraction method, which comprises the following steps of: firstly, acquiring time sequence multi-mode remote sensing image data before and after artificial water and soil loss disturbance in a supervision range, and performing high-precision registration on the time sequence multi-mode remote sensing image data to obtain a time sequence remote sensing image set; then constructing an artificial water and soil loss multi-modal remote sensing optimization feature set fused with a visual attention mechanism according to the time sequence remote sensing image set; and finally, performing remote sensing intelligent extraction on an artificial water and soil loss disturbance range in a supervision range based on an LSP graph convolutional neural network according to the artificial water and soil loss multi-mode remote sensing optimization feature set. The invention provides an artificial water and soil</abstract><oa>free_for_read</oa></addata></record>
fulltext fulltext_linktorsrc
identifier
ispartof
issn
language chi ; eng
recordid cdi_epo_espacenet_CN116580320A
source esp@cenet
subjects CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
PHYSICS
title Remote sensing intelligent extraction method for disturbance range of large-scale artificial water and soil loss
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-28T13%3A43%3A28IST&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=WEN%20QINGKE&rft.date=2023-08-11&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3ECN116580320A%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