Visualization of farm land use by classifying satellite images

Xiaojin Liao, Xiaodi Huang, Weidong Huang

Research output: Book chapter/Published conference paperConference paperpeer-review

4 Citations (Scopus)

Abstract

Land use mapping is becoming increasingly important in agriculture. Nowadays, satellite visualizations of farmland are available. On the other hand, the machine learning techniques have been advanced rapidly. This paper comprehensively investigates the use of the recently developed machine learning techniques to automatize land use mapping. Our comprehensive experiments are reported. The results of comparison experiments have demonstrated the performance of the algorithms on land use mapping.
Original languageEnglish
Title of host publicationCooperative Design, Visualization, and Engineering
Subtitle of host publication15th International Conference, CDVE 2018, Hangzhou, China, October 21–24, 2018, Proceedings
EditorsYuhua Luo
Place of PublicationSpringer Nature Switzerland AG 2018
PublisherSpringer
Pages287-290
Number of pages4
Volume11151
ISBN (Electronic)978-3-030-00560-3
ISBN (Print)978-3-030-00559-7
DOIs
Publication statusPublished - 12 Sep 2018
Event15th International Conference on Cooperative Design, Visualization, and Engineering, CDVE 2018 - Hangzhou Jinxi Hotel, Hangzhou, China
Duration: 21 Oct 201824 Oct 2018
http://www.cdve.org/cdve2018/ (Conference website)
https://www.springer.com/us/book/9783030005597 (Conference proceedings)

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11151 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference15th International Conference on Cooperative Design, Visualization, and Engineering, CDVE 2018
Country/TerritoryChina
CityHangzhou
Period21/10/1824/10/18
Internet address

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