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Field Crop Classification Using Multi-Temporal High-Resolution Satellite Imagery: A Case Study on Garlic/Onion Field

고해상도 다중시기 위성영상을 이용한 밭작물 분류: 마늘/양파 재배지 사례연구

  • Yoo, Hee Young (Geoinformatic Engineering Research Institute, Inha University) ;
  • Lee, Kyung-Do (National Institute of Agricultural Sciences, Rural Development Administration) ;
  • Na, Sang-Il (National Institute of Agricultural Sciences, Rural Development Administration) ;
  • Park, Chan-Won (National Institute of Agricultural Sciences, Rural Development Administration) ;
  • Park, No-Wook (Department of Geoinformatic Engineering, Inha University)
  • 유희영 (인하대학교 공간정보공학연구소) ;
  • 이경도 (농촌진흥청 국립농업과학원) ;
  • 나상일 (농촌진흥청 국립농업과학원) ;
  • 박찬원 (농촌진흥청 국립농업과학원) ;
  • 박노욱 (인하대학교 공간정보공학과)
  • Received : 2017.07.14
  • Accepted : 2017.08.22
  • Published : 2017.10.30

Abstract

In this paper, a study on classification targeting a main production area of garlic and onion was carried out in order to figure out the applicability of multi-temporal high-resolution satellite imagery for field crop classification. After collecting satellite imagery in accordance with the growth cycle of garlic and onion, classifications using each sing date imagery and various combinations of multi-temporal dataset were conducted. In the case of single date imagery, high classification accuracy was obtained in December when the planting was completed and March when garlic and onion started to grow vigorously. Meanwhile, higher classification accuracy was obtained when using multi-temporal dataset rather than single date imagery. However, more images did not guarantee higher classification accuracy. Rather, the imagery at the planting season or right after planting reduced classification accuracy. The highest classification accuracy was obtained when using the combination of March, April and May data corresponding the growth season of garlic and onion. Therefore, it is recommended to secure imagery at main growth season in order to classify garlic and onion field using multi-temporal satellite imagery.

이 논문에서는 고해상도 다중시기 위성영상을 이용한 밭작물 재배지 분류 가능성을 확인하기 위해 마늘과 양파 주산지를 대상으로 분류를 수행하였다. 마늘과 양파의 생육주기에 맞춰 영상을 수집하고 단일시기와 다양한 다중시기 자료의 조합으로 분류를 시도하였다. 단일시기 자료의 경우 파종이 모두 끝난 시기인 12월과 작물이 활발히 자라기 시작하는 3월 영상을 이용하였을 때 높은 분류 정확도를 보였다. 한편, 단일시기 자료 보다는 다중시기 자료를 이용하였을 때 더 높은 분류 정확도를 보였는데 자료의 수가 많은 것이 무조건 높은 분류 정확도를 반영하지는 않았다. 오히려 파종 시기 또는 파종 직후의 영상은 분류 정확도를 떨어뜨리는 역할을 하였고 마늘과 양파의 성장기인 3, 4, 5월 영상을 동시에 이용하여 분류하였을 때 가장 높은 분류 정확도를 얻었다. 따라서, 다중시기 위성영상을 이용하여 마늘과 양파를 분류하기 위해서는 작물 주요 성장기의 영상 확보가 매우 중요하다는 것을 확인할 수 있었다.

Keywords

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