Estimating Chicago's tree cover and canopy height using multi-spectral satellite imagery

• URL: http://arxiv.org/abs/2212.05061v1
• Date: Fri, 9 Dec 2022 10:12:34 GMT
• Title: Estimating Chicago's tree cover and canopy height using multi-spectral satellite imagery
• Authors: John Francis and Stephen Law
• Abstract summary: Urban tree planting initiatives face a lack of up-to-date data about the horizontal and vertical dimensions of the tree canopy in cities. We present a pipeline that utilizes LiDAR data as ground-truth and then trains a multi-task machine learning model to generate reliable estimates of tree cover and canopy height.
• Score: 2.538209532048867
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Information on urban tree canopies is fundamental to mitigating climate change [1] as well as improving quality of life [2]. Urban tree planting initiatives face a lack of up-to-date data about the horizontal and vertical dimensions of the tree canopy in cities. We present a pipeline that utilizes LiDAR data as ground-truth and then trains a multi-task machine learning model to generate reliable estimates of tree cover and canopy height in urban areas using multi-source multi-spectral satellite imagery for the case study of Chicago.

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