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An Overview of Tools and Algorithms Used to Classify, Detect, and Monitor Forest Area Using LiDAR Data

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Pattern Recognition, Computer Vision, and Image Processing. ICPR 2022 International Workshops and Challenges (ICPR 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13644))

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Abstract

LIght Detection and Ranging (LIDAR) is gaining popularity more and more among scientists for developing predictive models in forest areas. Lidar point cloud data has a strong potential for application to manage forest resources thanks to its high accuracy. Obviously, the forest should be given more concern, to not be destroyed, causing economic and ecological damage which affects human lives as well. Therefore, using the developed technologies to protect it is crucial. The Lidar technology is one of the most used recently to meet this requirement. To highlight the big interest of Lidar data in the forest monitoring issue, this article introduces a summary of Lidar data sources Airborne Laser scanning (ALS), Terrestrial Laser scanning (TLS) and mobile mapping system (MMS) algorithms and methods used to classify and filter the point cloud lidar data in forest areas.

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Acknowledgements

The authors would like to thank all the collaborators within this work, from the writing manuscript team. El Khalil Cherif would like to mention the financial support by FCT with the LARSyS—FCT project UIDB/50009/2020 and FCT project VOAMAIS (PTDC/EEIAUT/31172/2017, 02/SAICT/2017/31172).

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Authors and Affiliations

  1. GéoTéCa, FSTT, Abdelmalek Essaadi University, Km 10, Ziaten. BP: 416, Tetouan, Morocco

    Wijdan Amakhchan, Omar El Kharki, Miriam Wahbi, Otmane Yazidi Alaoui, Mustapha Maatouk & Hakim Boulaassal

  2. Institute for Systems and Robotics (ISR), Insituto Superior Technico, 1049-001, Lisbon, Portugal

    El Khalil Cherif

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  1. Wijdan Amakhchan
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Correspondence to Wijdan Amakhchan .

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  1. York University, Toronto, ON, Canada

    Jean-Jacques Rousseau

  2. Ontario Tech University, Oshawa, ON, Canada

    Bill Kapralos

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Amakhchan, W. et al. (2023). An Overview of Tools and Algorithms Used to Classify, Detect, and Monitor Forest Area Using LiDAR Data. In: Rousseau, JJ., Kapralos, B. (eds) Pattern Recognition, Computer Vision, and Image Processing. ICPR 2022 International Workshops and Challenges. ICPR 2022. Lecture Notes in Computer Science, vol 13644. Springer, Cham. https://doi.org/10.1007/978-3-031-37742-6_14

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