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http://dx.doi.org/10.7780/kjrs.2017.33.5.2.2

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

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)
Publication Information
Korean Journal of Remote Sensing / v.33, no.5_2, 2017 , pp. 621-630 More about this Journal
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.
Keywords
Field crop; Garlic; Onion; Classification; Multi-temporal satellite imagery;
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