Journal article

Mapping Urban Tree Cover Changes Using Object-Based Convolution Neural Network (OB-CNN)

Shirisa Timilsina, Jagannath Aryal, Jamie B Kirkpatrick

Remote Sensing | MDPI AG | Published : 2020

Abstract

Urban trees provide social, economic, environmental and ecosystem services benefits that improve the liveability of cities and contribute to individual and community wellbeing. There is thus a need for effective mapping, monitoring and maintenance of urban trees. Remote sensing technologies can effectively map and monitor urban tree coverage and changes over time as an efficient and low-cost alternative to field-based measurements, which are time consuming and costly. Automatic extraction of urban land cover features with high accuracy is a challenging task, and it demands object based artificial intelligence workflows for efficiency and thematic accuracy. The aim of this research is to effe..

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University of Melbourne Researchers