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http://dx.doi.org/10.7780/kjrs.2017.33.5.2.7

Satellite Imagery based Winter Crop Classification Mapping using Hierarchica Classification  

Na, Sang-il (National Institute of Agricultural Sciences, Rural Development Administration)
Park, Chan-won (National Institute of Agricultural Sciences, Rural Development Administration)
So, Kyu-ho (National Institute of Agricultural Sciences, Rural Development Administration)
Park, Jae-moon (National Institute of Agricultural Sciences, Rural Development Administration)
Lee, Kyung-do (National Institute of Agricultural Sciences, Rural Development Administration)
Publication Information
Korean Journal of Remote Sensing / v.33, no.5_2, 2017 , pp. 677-687 More about this Journal
Abstract
In this paper, we propose the use of hierarchical classification for winter crop mapping based on satellite imagery. A hierarchical classification is a classifier that maps input data into defined subsumptive output categories. This classification method can reduce mixed pixel effects and improve classification performance. The methodology are illustrated focus on winter cropsin Gimje city, Jeonbuk with Landsat-8 imagery. First, agriculture fields were extracted from Landsat-8 imagery using Smart Farm Map. And then winter crop fields were extracted from agriculture fields using temporal Normalized Difference Vegetation Index (NDVI). Finally, winter crop fields were then classified into wheat, barley, IRG, whole crop barley and mixed crop fields using signature from Unmanned Aerial Vehicle (UAV). The results indicate that hierarchical classifier could effectively identify winter crop fields with an overall classification accuracy of 98.99%. Thus, it is expected that the proposed classification method would be effectively used for crop mapping.
Keywords
hierarchical classification; winter crop; Landsat-8; crop mapping;
Citations & Related Records
Times Cited By KSCI : 5  (Citation Analysis)
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