Imaging Using Unmanned Aerial Vehicles for Agriculture Land Use Classification

Pei-Chun Chen,Yen-Cheng Chiang,Pei-Yi Weng

doi:10.3390/agriculture10090416

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.

Highlights

IntroductionRemote sensing technology, incorporating a geographical information system, is used globally for land management, agriculture, forestry, environmental protection, and the fishery industry [1,2]
Remote sensing technology, incorporating a geographical information system, is used globally for land management, agriculture, forestry, environmental protection, and the fishery industry [1,2].Economic development and social changes have led to increasingly complex land uses, increased damage to the natural environment, and the inappropriate use of land resources, including the unauthorized use of farmlands, inappropriate waste disposal, and the illegal construction of factories.Previous study used satellite imaging, which facilitates large-area detection, real-time monitoring, and the rapid depiction of current conditions and dynamic changes in national territories to obtain basic data for determining land uses
The results showed that the crop classification information that is captured from unmanned aerial vehicle (UAV) images was more accurate and widely applicable than that obtained using earlier investigative approaches [9]

Summary

Introduction

Remote sensing technology, incorporating a geographical information system, is used globally for land management, agriculture, forestry, environmental protection, and the fishery industry [1,2]. Previous study used satellite imaging, which facilitates large-area detection, real-time monitoring, and the rapid depiction of current conditions and dynamic changes in national territories to obtain basic data for determining land uses. The study collected satellite images of a particular area on appropriate scales and established a system for automatically interpreting them [3]. Surveys on agricultural land areas in Taiwan are mostly conducted manually or through telemetric imaging. Because telemetric imaging is expensive and cannot be used to acquire real-time images, such surveys often miss the growth period of crops. Investigators may have difficulty accessing locations on hillsides; their view may be obstructed, making the results of investigations of crops planted on hillsides less than reliable [4]

Methods

Results

Discussion

Conclusion