Remote sensing big data utilization for paddy growth stages detection

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

Predicting and estimating the character of big data becomes paramount since it is laborious to deal with big data with conventional models and algorithms. Remote sensing big data from various satellites consist of many large-scale images that are exceptionally complex in terms of their structural, spectral, and textual features. Also, most of them are still in annotated form. Therefore, it is a challenge to explore them for detecting objects on the ground that are beneficial to humans using their sophisticated features. In this paper, we proposed a remote sensing big data for paddy growth stages detection, through multi-temporal analysis with a heuristic algorithm. Information derived from growth stages is very useful to know the needs of water, fertilizer, and crop planting calendar to increase productivity.

Original languageEnglish
Title of host publicationProceedings of the 2015 IEEE International Conference on Aerospace Electronics and Remote Sensing, ICARES 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781467377140
DOIs
Publication statusPublished - 9 Mar 2016
EventIEEE International Conference on Aerospace Electronics and Remote Sensing Technology, ICARES 2015 - Bali, Indonesia
Duration: 3 Dec 20155 Dec 2015

Publication series

NameProceedings of the 2015 IEEE International Conference on Aerospace Electronics and Remote Sensing, ICARES 2015

Conference

ConferenceIEEE International Conference on Aerospace Electronics and Remote Sensing Technology, ICARES 2015
Country/TerritoryIndonesia
CityBali
Period3/12/155/12/15

Keywords

  • growth stages
  • heuristic algorithm
  • paddy
  • remote sensing

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