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Journal of Applied Remote Sensing

Cultivated land information extraction from high-resolution unmanned aerial vehicle imagery data
Author(s): Lei Ma; Liang Cheng; Wenquan Han; Lishan Zhong; Manchun Li
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Paper Abstract

The development of precision agriculture demands high accuracy and efficiency of cultivated land information extraction. Simultaneously, unmanned aerial vehicles (UAVs) have been increasingly used for natural resource applications in recent years as a result of their greater availability, the miniaturization of sensors, and the ability to deploy UAVs relatively quickly and repeatedly at low altitudes. We examine the potential of utilizing a small UAV for the characterization, assessment, and monitoring of cultivated land. Because most UAV images lack spectral information, we propose a novel cultivated land information extraction method based on a triangulation for cultivated land information extraction (TCLE) method. Thus, the information on more spatial properties of a region is incorporated into the classification process. The TCLE comprises three main steps: image segmentation, triangulation construction, and triangulation clustering using AUTOCLUST. Experiments were conducted on three UAV images in Deyang, China, using TCLE and eCognition for cultivated land information extraction (ECLE). Experimental results show that TCLE, which does not require training samples and has a much higher level of automation, can obtain accuracies equivalent to ECLE. Comparing with ECLE, TCLE also extracts coherent cultivated land with much less noise. As such, cultivated land information extraction based on high-resolution UAV images can be effectively and efficiently conducted using the proposed method.

Paper Details

Date Published: 20 February 2014
PDF: 26 pages
J. Appl. Remote Sens. 8(1) 083673 doi: 10.1117/1.JRS.8.083673
Published in: Journal of Applied Remote Sensing Volume 8, Issue 1
Show Author Affiliations
Lei Ma, Nanjing Univ. (China)
Liang Cheng, Nanjing Univ. (China)
Wenquan Han, Nanjing Univ. (China)
Lishan Zhong, Nanjing Univ. (China)
Manchun Li, Nanjing Univ. (China)


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