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Role of LiDAR remote sensing in identifying physiognomic traits of alpine treeline: a global review

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Abstract

Alpine treeline ecotones act as early warning systems for detecting the impact of climate change on terrestrial ecosystems. The physiognomic traits of the treeline ecotones, such as tree height, canopy cover, and leaf area, are expected to change in response to ongoing climate warming. These traits contain valuable information about the processes that govern treeline dynamics, and thus, it is important to describe them consistently along ecologically meaningful dimensions. However, conventional approaches to evaluating vegetation structure, such as those that rely on optical and synthetic aperture radar (SAR) imaging satellites, have significant limitations that limit their utility in mountainous terrain. The use of SAR imagery is constrained by shadowing and geometric distortion caused by steep terrain, while optical imaging systems are insensitive to changes in vegetation vertical structure. In contrast, Light Detection and Ranging (LiDAR) technology, offers an accurate means of estimating the three-dimensional physiognomic traits of vegetation in a mountainous alpine environment. Due to the obvious advantages of LiDAR over conventional multi-spectral imaging and radar imaging sensors, the number of LiDAR-based treeline studies has increased in recent years. In this review, we examined how LiDAR remote sensing is utilized in the alpine treeline research and evaluated the associated challenges and opportunities. Further, this study concludes by discussing the promising future of LiDAR technology, and accordingly, some recommendations are put forward.

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Acknowledgements

The first author is thankful to UGC, New Delhi, for the UGC junior research fellowship (JRF). The authors are thankful to Shri. N.M. Desai, Director, Space Applications Centre (SAC), ISRO for his constant encouragement and guidance.

Funding

This work was funded by UGC NET (Grant no. 190520399476) (CSIR-UGC NET /date 08/01/2020) by Jincy Rachel Mathew.

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  1. Department of Environmental Science, Gujarat University, Ahmedabad, Gujarat, India

    Jincy Rachel Mathew, Hitesh Solanki & Dhruvi Sedha

  2. EPSA, Space Applications Centre (SAC), ISRO, Ahmedabad, Gujarat, India

    Jincy Rachel Mathew, Chandra Prakash Singh, Dhruvi Sedha, Mehul R. Pandya & Bimal K. Bhattacharya

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  1. Jincy Rachel Mathew
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Correspondence to Jincy Rachel Mathew.

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Mathew, J.R., Singh, C.P., Solanki, H. et al. Role of LiDAR remote sensing in identifying physiognomic traits of alpine treeline: a global review. Trop Ecol (2023). https://doi.org/10.1007/s42965-023-00317-6

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