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Letter

Remote Sensing of Coconut Trees in Tonga Using Very High Spatial Resolution WorldView-3 Data

1
NASA Goddard Space Flight Center Code 619, 8800 Greenbelt Road, Greenbelt, MD 20771, USA
2
Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA
3
World Bank Group, Global Facility for Disaster Reduction and Recovery, Washington, DC 20006, USA
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(19), 3113; https://doi.org/10.3390/rs12193113
Received: 28 July 2020 / Revised: 11 September 2020 / Accepted: 20 September 2020 / Published: 23 September 2020
This paper presents a simple and efficient image processing method for estimating the number of coconut trees in the Tonga region using very high spatial resolution data (30 cm) in the blue, green, red and near infrared spectral bands acquired by the WorldView-3 sensor. The method is based on the detection of tree shadows and the further analysis to reject false detection using geometrical properties of the derived segments. The algorithm is evaluated by comparing coconut tree counts derived by an expert through photo-interpretation over 57 randomly distributed (4% sampling rate) segments of 200 m × 200 m over the Vaini region of the Tongatapu island. The number of detected trees agreed within 5% versus validation data. The proposed method was also evaluated over the whole Tonga archipelago by comparing satellite-derived estimates to the 2015 agricultural census data—the total tree counts for both Tonga and Tongatapu agreed within 3%. View Full-Text
Keywords: coconut tree; tree counting; satellite imagery; very high spatial resolution; WorldView-3; tree shadow; image processing coconut tree; tree counting; satellite imagery; very high spatial resolution; WorldView-3; tree shadow; image processing
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MDPI and ACS Style

Vermote, E.F.; Skakun, S.; Becker-Reshef, I.; Saito, K. Remote Sensing of Coconut Trees in Tonga Using Very High Spatial Resolution WorldView-3 Data. Remote Sens. 2020, 12, 3113. https://doi.org/10.3390/rs12193113

AMA Style

Vermote EF, Skakun S, Becker-Reshef I, Saito K. Remote Sensing of Coconut Trees in Tonga Using Very High Spatial Resolution WorldView-3 Data. Remote Sensing. 2020; 12(19):3113. https://doi.org/10.3390/rs12193113

Chicago/Turabian Style

Vermote, Eric F., Sergii Skakun, Inbal Becker-Reshef, and Keiko Saito. 2020. "Remote Sensing of Coconut Trees in Tonga Using Very High Spatial Resolution WorldView-3 Data" Remote Sensing 12, no. 19: 3113. https://doi.org/10.3390/rs12193113

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