Imaging Using Unmanned Aerial Vehicles for Agriculture Land Use Classification

Pei-Chun Chen, Yen-Cheng Chiang and Pei-Yi Weng
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Pei-Chun Chen: Department of Landscape Architecture, National Chiayi University, Chiayi 60004, Taiwan
Yen-Cheng Chiang: Department of Landscape Architecture, National Chiayi University, Chiayi 60004, Taiwan
Pei-Yi Weng: Department of Plant Industry, National Pingtung University of Science and Technology, Pingtung 91201, Taiwan

Agriculture, 2020, vol. 10, issue 9, 1-14

Abstract: An unmanned aerial vehicle (UAV) was used to capture high-resolution aerial images of crop fields. Software-based image analysis was performed to classify land uses. The purpose was to help relevant agencies use aerial imaging in managing agricultural production. This study involves five townships in the Chianan Plain of Chiayi County, Taiwan. About 100 ha of farmland in each township was selected as a sample area, and a quadcopter and a handheld fixed-wing drone were used to capture visible-light images and multispectral images. The survey was carried out from August to October 2018 and aerial photographs were captured in clear and dry weather. This study used high-resolution images captured from a UAV to classify the uses of agricultural land, and then employed information from multispectral images and elevation data from a digital surface model. The results revealed that visible-light images led to low interpretation accuracy. However, multispectral images and elevation data increased the accuracy rate to nearly 90%. Accordingly, such images and data can effectively enhance the accuracy of land use classification. The technology can reduce costs that are associated with labor and time and can facilitate the establishment of a real-time mapping database.

Keywords: unmanned aerial vehicle; agricultural survey; land use (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2020
References: View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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