Urban Tree Crown Detection based on Deep Learning and High-Resolution Aerial Imagery: PTCNet for Pullman, WA, USA

O. M. Alegbeleye; A. J. H. Meddens; Y. O. Rotimi; K. G. Ibeh

doi:10.1016/j.rsase.2025.101818

Publication details

Authors: O. M. Alegbeleye, A. J. H. Meddens, Y. O. Rotimi, K. G. Ibeh

Venue: Remote Sensing Applications: Society and Environment

Volume/issue: 41

Article number: 101818

DOI: 10.1016/j.rsase.2025.101818

Summary

A comparison of deep-learning detectors using high-resolution aerial imagery, culminating in PTCNet and an urban tree inventory for Pullman, Washington.

remote sensingdeep learningurban forestrytree crown detectionaerial imagerygeospatial analysis

Research themes

Remote sensingUrban forestryOpen science

Methods

Deep learningYOLOv3Mask R-CNNRetinaNetFaster R-CNNHigh-resolution aerial imageryLiDAR

Study area

Pullman, Washington, USA

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