TY  - JOUR
A1  - Ghasemi, Marziye
A1  - Latifi, Hooman
A1  - Pourhashemi, Mehdi
T1  - A novel method for detecting and delineating coppice trees in UAV images to monitor tree decline
JF  - Remote Sensing
N2  - Monitoring tree decline in arid and semi-arid zones requires methods that can provide up-to-date and accurate information on the health status of the trees at single-tree and sample plot levels. Unmanned Aerial Vehicles (UAVs) are considered as cost-effective and efficient tools to study tree structure and health at small scale, on which detecting and delineating tree crowns is the first step to extracting varied subsequent information. However, one of the major challenges in broadleaved tree cover is still detecting and delineating tree crowns in images. The frequent dominance of coppice structure in degraded semi-arid vegetation exacerbates this problem. Here, we present a new method based on edge detection for delineating tree crowns based on the features of oak trees in semi-arid coppice structures. The decline severity in individual stands can be analyzed by extracting relevant information such as texture from the crown area. Although the method presented in this study is not fully automated, it returned high performances including an F-score = 0.91. Associating the texture indices calculated in the canopy area with the phenotypic decline index suggested higher correlations of the GLCM texture indices with tree decline at the tree level and hence a high potential to be used for subsequent remote-sensing-assisted tree decline studies.
KW  - UAV
KW  - crown delineation
KW  - coppice
KW  - Zagros oak forests
KW  - edge detection
KW  - decline
KW  - texture analysis
Y1  - 2022
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-297258
SN  - 2072-4292
VL  - 14
IS  - 23
ER  -