Aerolaserskaneerimise kasutamine metsakorralduse alusena

Author:

Arumäe Tauri12,Lang Mait13

Affiliation:

1. Institute of Forestry and Rural Engineering , Estonian University of Life Sciences , Kreutzwaldi 5 , Tartu , Estonia

2. State Forest Management Centre , Sagadi Village, EE-45403 Haljala , Estonia

3. Tartu Observatory , University of Tartu , Tõravere , Tartumaa , Estonia

Abstract

Abstract In this summary, we give an overview of the application of airborne laser scanning (ALS) data for predicting the main forest inventory variables in Estonia. When Estonia being one of the few countries with wall-to-wall ALS availability, the need for applicable models for Estonian forests was imminent. Over the past decade, different studies have been carried out to develop models for standing wood volume, forest height, canopy cover, canopy base height, and methods for monitoring height growth and detect small-scale harvests. The main findings showed strong correlations for all the studied parameters and different methods utilizing low-density lidar data for practical forest inventory purposes. Options for using repea ted ALS measurements for continuous forest inventory are discussed.

Publisher

Walter de Gruyter GmbH

Subject

Forestry

Reference37 articles.

1. Adermann, V. 2010. Development of Estonian National Forest Inventory. – Tomppo, E., Gschwantner, T., Lawrence, M., McRoberts, R.E. (eds.). National Forest Inventories: Pathways for Common Reporting. Heidelberg, Springer, 171–184.

2. Arumäe, T. 2020. Estimating forest variables using airborne lidar measurements in hemi-boreal forests. – Doctoral thesis. Tartu, Estonian University of Life Sciences. 195 pp. http://dspace.emu.ee/xmlui/handle/10492/5764.

3. Arumäe, T., Lang, M. 2013. A simple model to estimate forest canopy base height from airborne lidar data. – Forestry Studies / Metsanduslikud Uurimused, 58, 46–56. (In Estonian with English summary).

4. Arumäe, T., Lang, M. 2016. ALS-based wood volume models of forest stands and comparison with forest inventory data. – Forestry Studies / Metsanduslikud Uurimused, 64, 5–16. https://doi.org/10.1515/fsmu-2016-0001. (In Estonian with English summary).

5. Arumäe, T., Lang, M. 2018. Estimation of canopy cover in dense mixed-species forests using airborne lidar data. – European Journal of Remote Sensing, 51(1), 132–141. https://doi.org/10.1080/22797254.2017.1411169.

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