Automatic localization of phoenix by satellite image analysis
Other Title(s)
التحديد التلقائي لموقع أشجار النخيل بتحليل الصور الفضائية
Joint Authors
Source
Arab Journal of Plant Protection
Issue
Vol. 37, Issue 2 (31 Aug. 2019), pp.83-88, 6 p.
Publisher
Arab Society for Plant Protection
Publication Date
2019-08-31
Country of Publication
Lebanon
No. of Pages
6
Main Subjects
Topics
Abstract EN
The Red palm weevil (RPW) Rhynchophorus ferrugineus is becoming one of the deadliest pests of the palms in the world.
In order to effectively implement a RPW control programme to achieve rapid regression of this pest, it is necessary to have GPS coordinates of each palm present on the control perimeter.
This location makes it possible to establish maps and databases which are essential for organizing, at the local and national level, the implementation and permanent monitoring of control measures.
It is difficult, time-consuming and expensive to locate palms by visually exploring the entire perimeter from the ground.
In the zone of regular plantations, this work can be processed but it becomes extremely heavy in the traditional oasis like in urban environment where the distribution of the palms is very irregular.
With advances in satellite imagery, it is possible to acquire high quality images at very short intervals of time from a standard format for a large part of the earth.
Combined with the progress of machine learning, particularly deep learning, this amount of data is able to feed a robust model.
It would allow to automate the detection of palms at large scale and monitor their evolution at very short intervals, which in the fight against RPW is valuable information.
This first work wants to test the interest in this solution.
We build and train a convolution neural network in order to find two species of palms Phoenix canariensis and Phoenix dactylifera (C&D) in a very heterogeneous area of 100 km².
Our model evaluation shows that 1/5 of the objects found are false positive and more than 2/3 of C&D are perfectly localized.
These first results could be improved greatly by implementing a more robust algorithm using more data and using larger colour spectrum (as near infra-red).
The question of the infested palms detection using satellite imagery and machine learning stays open.
American Psychological Association (APA)
Cousin, Rafael& Ferry, Michel. 2019. Automatic localization of phoenix by satellite image analysis. Arab Journal of Plant Protection،Vol. 37, no. 2, pp.83-88.
https://search.emarefa.net/detail/BIM-888115
Modern Language Association (MLA)
Cousin, Rafael& Ferry, Michel. Automatic localization of phoenix by satellite image analysis. Arab Journal of Plant Protection Vol. 37, no. 2 (2019), pp.83-88.
https://search.emarefa.net/detail/BIM-888115
American Medical Association (AMA)
Cousin, Rafael& Ferry, Michel. Automatic localization of phoenix by satellite image analysis. Arab Journal of Plant Protection. 2019. Vol. 37, no. 2, pp.83-88.
https://search.emarefa.net/detail/BIM-888115
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 88
Record ID
BIM-888115