File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: 智慧遥感制图(iMap)

Title智慧遥感制图(iMap)
Intelligent mapping with remote sensing, iMap
Authors
KeywordsAI and mapping
Big data
Cross-walkable classification system
Knowledge transfer
Issue Date25-Feb-2021
PublisherAmerican Association for the Advancement of Science
Citation
Journal of Remote Sensing, 2021, v. 25, n. 2, p. 527-529 How to Cite?
Abstract

本文基于地图制图发展趋势,提出智慧遥感制图的概念(iMap)。旨在梳理遥感制图未来的努力方向。iMap应从制图目的灵活性、制图知识可迁移性、数据多源性、多算法集成性和制图系统易用性等方面深入利用大数据和人工智能技术,创新遥感制图理论和技术。


Mapping as a human cognition behavior has experienced four stages: illustrative mapping, surveying and mapping, mapping with remote sensing, and now entering into intelligent mapping age - iMap. In this note, I argue that the next generation iMap needs at least five elements. These include flexible and cross-walkable purpose of mapping cutting across spatio-temporal scales, powerful knowledge transfer that harness digital library and knowledge extracted from the cyberspace, a diverse sources of data including social big data, an ensembled use of multiple algorithms for pattern recognition (i.e., Earth surface type labelling and target recognition), and a mapping platform that is easy to use by laypersons.
Persistent Identifierhttp://hdl.handle.net/10722/350351
ISSN
2023 SCImago Journal Rankings: 0.521

 

DC FieldValueLanguage
dc.contributor.authorGong, Peng-
dc.date.accessioned2024-10-29T00:31:04Z-
dc.date.available2024-10-29T00:31:04Z-
dc.date.issued2021-02-25-
dc.identifier.citationJournal of Remote Sensing, 2021, v. 25, n. 2, p. 527-529-
dc.identifier.issn1007-4619-
dc.identifier.urihttp://hdl.handle.net/10722/350351-
dc.description.abstract<p>本文基于地图制图发展趋势,提出智慧遥感制图的概念(iMap)。旨在梳理遥感制图未来的努力方向。iMap应从制图目的灵活性、制图知识可迁移性、数据多源性、多算法集成性和制图系统易用性等方面深入利用大数据和人工智能技术,创新遥感制图理论和技术。<br></p>-
dc.description.abstractMapping as a human cognition behavior has experienced four stages: illustrative mapping, surveying and mapping, mapping with remote sensing, and now entering into intelligent mapping age - iMap. In this note, I argue that the next generation iMap needs at least five elements. These include flexible and cross-walkable purpose of mapping cutting across spatio-temporal scales, powerful knowledge transfer that harness digital library and knowledge extracted from the cyberspace, a diverse sources of data including social big data, an ensembled use of multiple algorithms for pattern recognition (i.e., Earth surface type labelling and target recognition), and a mapping platform that is easy to use by laypersons.-
dc.languagechi-
dc.publisherAmerican Association for the Advancement of Science-
dc.relation.ispartofJournal of Remote Sensing-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectAI and mapping-
dc.subjectBig data-
dc.subjectCross-walkable classification system-
dc.subjectKnowledge transfer-
dc.title智慧遥感制图(iMap)-
dc.titleIntelligent mapping with remote sensing, iMap-
dc.typeArticle-
dc.identifier.doi10.11834/jrs.20211010-
dc.identifier.scopuseid_2-s2.0-85102270325-
dc.identifier.volume25-
dc.identifier.issue2-
dc.identifier.spage527-
dc.identifier.epage529-
dc.identifier.eissn2694-1589-
dc.identifier.issnl1007-4619-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats