Automated Segmentation and Classification of Aerial Forest Imagery

Pichai, Kieran; Park, Benjamin; Bao, Aaron; Yin, Yiqiao

doi:10.3390/analytics1020010

Open AccessArticle

Automated Segmentation and Classification of Aerial Forest Imagery

by

Kieran Pichai

,

Benjamin Park

,

Aaron Bao

and

Yiqiao Yin

^*

Department of Statistics, Columbia University, New York, NY 10027, USA

^*

Author to whom correspondence should be addressed.

Analytics 2022, 1(2), 135-143; https://doi.org/10.3390/analytics1020010

Submission received: 29 September 2022 / Revised: 31 October 2022 / Accepted: 10 November 2022 / Published: 14 November 2022

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Abstract

Monitoring the health and safety of forests has become a rising problem with the advent of global wildfires, rampant logging, and reforestation efforts. This paper proposes a model for the automatic segmentation and classification of aerial forest imagery. The model is based on U-net architecture and relies on dice coefficients, binary cross-entropy, and accuracy as loss functions. While models without autoencoder-based structures can only reach a dice coefficient of 45%, the proposed model can achieve a dice coefficient of 79.85%. In addition, for barren adn dense forestry image classification, the proposed model can achieve 82.51%. This paper demonstrates how complex convolutional neural networks can be applied to aerial forest images to help preserve and save the forest environment.

Keywords: artificial neural network; image classification; image segmentation; satellite forest imagery

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MDPI and ACS Style

Pichai, K.; Park, B.; Bao, A.; Yin, Y. Automated Segmentation and Classification of Aerial Forest Imagery. Analytics 2022, 1, 135-143. https://doi.org/10.3390/analytics1020010

AMA Style

Pichai K, Park B, Bao A, Yin Y. Automated Segmentation and Classification of Aerial Forest Imagery. Analytics. 2022; 1(2):135-143. https://doi.org/10.3390/analytics1020010

Chicago/Turabian Style

Pichai, Kieran, Benjamin Park, Aaron Bao, and Yiqiao Yin. 2022. "Automated Segmentation and Classification of Aerial Forest Imagery" Analytics 1, no. 2: 135-143. https://doi.org/10.3390/analytics1020010

APA Style

Pichai, K., Park, B., Bao, A., & Yin, Y. (2022). Automated Segmentation and Classification of Aerial Forest Imagery. Analytics, 1(2), 135-143. https://doi.org/10.3390/analytics1020010

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Automated Segmentation and Classification of Aerial Forest Imagery

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