Version 1
: Received: 27 October 2017 / Approved: 27 October 2017 / Online: 27 October 2017 (12:30:05 CEST)
How to cite:
Chemin, Y.H.; Beck, P.S. A Method to Count Olive Trees in Heterogenous Plantations from Aerial Photographs. Preprints2017, 2017100170. https://doi.org/10.20944/preprints201710.0170.v1
Chemin, Y.H.; Beck, P.S. A Method to Count Olive Trees in Heterogenous Plantations from Aerial Photographs. Preprints 2017, 2017100170. https://doi.org/10.20944/preprints201710.0170.v1
Chemin, Y.H.; Beck, P.S. A Method to Count Olive Trees in Heterogenous Plantations from Aerial Photographs. Preprints2017, 2017100170. https://doi.org/10.20944/preprints201710.0170.v1
APA Style
Chemin, Y.H., & Beck, P.S. (2017). A Method to Count Olive Trees in Heterogenous Plantations from Aerial Photographs. Preprints. https://doi.org/10.20944/preprints201710.0170.v1
Chicago/Turabian Style
Chemin, Y.H. and Pieter S.A. Beck. 2017 "A Method to Count Olive Trees in Heterogenous Plantations from Aerial Photographs" Preprints. https://doi.org/10.20944/preprints201710.0170.v1
Abstract
Olive trees have been of economic and cultural value since pre-Roman times, and continue to dominate landscapes and agriculture in many mediterranean regions. Recent mass losses of olive trees in Southern Italy due to an exotic plant pathogen highlight the need for methods that to monitor the olive trees in a landscape or region operationally. Here, we develop a method for counting olive trees from aerial photographs and test it in areas with a high diversity of olive tree ages, sizes, and shapes. This heterogeneity complicates tree counting as centennial trees often have crowns that are split into multiple segments, resembling multiple crowns, while nearby crowns often form a semi-closed canopy comprising multiple trees. Comparisons with reference counts in two 20 ha sites and over three different years indicate the automated counts tend to be reasonably accurate (median error 13%, n = 6), but heavily influenced by a few olive orchards with particularly high planting densities and a relatively closed canopy in which distinguishing individual trees is challenging. Overall, the algorithm estimated tree densities well (counting 82 to 109 trees/ha versus 87 to 104 trees/ha in the reference counts), indicating the method is suitable to track the number of olive trees over large areas.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
