期刊
REMOTE SENSING
卷 11, 期 7, 页码 -出版社
MDPI
DOI: 10.3390/rs11070855
关键词
unmanned aerial vehicles; remote sensing; automatic plantation monitoring; chestnut trees; image processing; photogrammetric processing; multi-temporal analysis
类别
资金
- European Regional Development Fund (ERDF) through the Operational Programme for Competitiveness and Internationalisation-COMPETE 2020 under the PORTUGAL 2020 Partnership Agreement
- European Regional Development Fund (ERDF) through the Portuguese National Innovation Agency (ANI) as a part of project PARRA-Plataforma integrAda de monitoRizacao e avaliacao da doenca da flavescencia douRada na vinhA [3447]
Unmanned aerial vehicles have become a popular remote sensing platform for agricultural applications, with an emphasis on crop monitoring. Although there are several methods to detect vegetation through aerial imagery, these remain dependent of manual extraction of vegetation parameters. This article presents an automatic method that allows for individual tree detection and multi-temporal analysis, which is crucial in the detection of missing and new trees and monitoring their health conditions over time. The proposed method is based on the computation of vegetation indices (VIs), while using visible (RGB) and near-infrared (NIR) domain combination bands combined with the canopy height model. An overall segmentation accuracy above 95% was reached, even when RGB-based VIs were used. The proposed method is divided in three major steps: (1) segmentation and first clustering; (2) cluster isolation; and (3) feature extraction. This approach was applied to several chestnut plantations and some parameterssuch as the number of trees present in a plantation (accuracy above 97%), the canopy coverage (93% to 99% accuracy), the tree height (RMSE of 0.33 m and R-2 = 0.86), and the crown diameter (RMSE of 0.44 m and R-2 = 0.96)were automatically extracted. Therefore, by enabling the substitution of time-consuming and costly field campaigns, the proposed method represents a good contribution in managing chestnut plantations in a quicker and more sustainable way.
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