In the context of the Common Agricultural Policy (CAP) there is a strong interest of the European Commission for counting and individually locating fruit trees. An automatic counting algorithm developed by the JRC (OLICOUNT) was used in the past for olive trees only, on 1m black and white orthophotos but with limits in case of young trees or irregular groves. This study investigates the improvement of fruit tree identification using VHR images on a large set of data in three test sites, one in Creta (Greece) and one in the south-east of France with a majority of olive trees and associated fruit trees, and the last one in Florida on citrus trees. OLICOUNT was compared with two other automatic tree counting, applications, one using the CRISP software on citrus trees and the other completely automatic based on regional minima (morphological image analysis). Additional investigation was undertaken to refine the methods. This paper describes the automatic methods and presents the results derived from the tests.
Conference Committee Involvement (4)
Remote Sensing for Environmental Monitoring, GIS Applications, and Geology VIII
15 September 2008 | Cardiff, Wales, United Kingdom
Remote Sensing for Environmental Monitoring, GIS Applications, and Geology
17 September 2007 | Florence, Italy
Remote Sensing for Environmental Monitoring, GIS Applications, and Geology VI
13 September 2006 | Stockholm, Sweden
Remote Sensing for Environmental Monitoring, GIS Applications, and Geology V
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