Research Papers

Cultivated land information extraction from high-resolution unmanned aerial vehicle imagery data

[+] Author Affiliations
Lei Ma, Liang Cheng, Lishan Zhong, Manchun Li

Nanjing University, Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, 22 Hankou Road, Nanjing 210097, China

Nanjing University, Collaborative Innovation Center for the South China Sea Studies, 22 Hankou Road, Nanjing 210097, China

Wenquan Han

Nanjing University, Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, 22 Hankou Road, Nanjing 210097, China

Nanjing Institute of Surveying, Mapping & Geotechnical Investigation, Co. Ltd, 88 ChuangYi Road, Nanjing 210019, China

J. Appl. Remote Sens. 8(1), 083673 (Feb 20, 2014). doi:10.1117/1.JRS.8.083673
History: Received August 9, 2013; Revised January 23, 2014; Accepted January 27, 2014
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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.

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Citation

Lei Ma ; Liang Cheng ; Wenquan Han ; Lishan Zhong and Manchun Li
"Cultivated land information extraction from high-resolution unmanned aerial vehicle imagery data", J. Appl. Remote Sens. 8(1), 083673 (Feb 20, 2014). ; http://dx.doi.org/10.1117/1.JRS.8.083673


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