A comparison of longitude–latitude and Euclidean distance shape descriptors for determining tree crown shapes derived from LiDAR data. Issue 22 (17th November 2019)

• Record Type: Journal Article
• Authors: Sadeghinaeenifard, Fariba; Dong, Pinliang
• Is Part Of: International journal of remote sensing. Volume 40:Issue 22(2019)
• Page Start: 8432
• Page End: 8449
• Publication Date: 2019-11-17
• Subjects: Remote sensing -- Periodicals; Télédétection -- Périodiques; 621.3678
• DOI: 10.1080/01431161.2019.1610986
• Languages: English
• ISSNs: 0143-1161

Abstract

ABSTRACT: Previous studies demonstrate the effectiveness of the Euclidean distance shape descriptor for characterizing individual tree crowns derived from Light Detection and Ranging (LiDAR) data. This paper evaluates the effectiveness of the longitude–latitude shape descriptor for tree crown shape characterization in comparison with the Euclidean distance descriptor using LiDAR data for 43 individual tree crowns. The three-dimensional (3D) shape signatures obtained from longitude–latitude and Euclidean distance measures of the tree crowns are compared with 3D shape signatures of simulated ellipsoid and hemisphere tree crowns. Kolmogorov–Smirnov test (K–S test) and Mean Square Error (MSE) are used to measure the similarity of longitude–latitude and Euclidean distance signatures. The experimental results from all 43 examined trees suggest that the longitude–latitude shape descriptor can determine tree crown shapes with different leaf traits, while Euclidean distance is only able to characterize the shape of evergreen trees. Furthermore, the longitude–latitude shape descriptor, unlike the Euclidean distance shape descriptor, is not sensitive to the number of LiDAR points from the tree crown.