J 2023

Benchmark for Automatic Clear-Cut Morphology Detection Methods Derived from Airborne Lidar Data

MELICHOVA, Zlatica, Stanislav PEKÁR and Peter SUROVY

Basic information

Original name

Benchmark for Automatic Clear-Cut Morphology Detection Methods Derived from Airborne Lidar Data

Authors

MELICHOVA, Zlatica (guarantor), Stanislav PEKÁR (703 Slovakia, belonging to the institution) and Peter SUROVY

Edition

Forests, MDPI, 2023, 1999-4907

Other information

Language

English

Type of outcome

Článek v odborném periodiku

Field of Study

40102 Forestry

Country of publisher

Switzerland

Confidentiality degree

není předmětem státního či obchodního tajemství

References:

URL

Impact factor

Impact factor: 2.900 in 2022

RIV identification code

RIV/00216224:14310/23:00133014

Organization unit

Faculty of Science

DOI

http://dx.doi.org/10.3390/f14122408

UT WoS

001131325900001

Keywords in English

multitemporal laser scanning data; harvest detection; simplification polygons; clear-cut areas

Tags

rivok

Tags

International impact, Reviewed
Změněno: 8/3/2024 15:12, Mgr. Marie Šípková, DiS.

Abstract

V originále

Forest harvest detection techniques have recently gained increased attention due to the varied results they provide. Correctly determining the acreage of clear-cut areas is crucial for carbon sequestration. Detecting clear-cut areas using airborne laser scanning (ALS) could be an accurate method for determining the extent of clear-cut areas and their subsequent map display in forest management plans. The shapes of ALS-detected clear-cut areas have uneven edges with protrusions that might not be readable when displayed correctly. Therefore, it is necessary to simplify these shapes for better comprehension. To simplify the shapes of ALS-scanned clear-cut areas, we tested four simplification algorithms using ArcGIS Pro 3.0.0 software: the retain critical points (Douglas-Peucker), retain critical bends (Wang-Muller), retain weighted effective areas (Zhou-Jones), and retain effective areas (Visvalingam-Whyatt) algorithms. Ground-truth data were obtained from clear-cut areas plotted in the forest management plan. Results showed that the Wang-Muller algorithm was the best of the four ALS algorithms at simplifying the shapes of detected clear-cut areas. Using the simplification algorithm reduced the time required to edit polygons to less than 1% of the time required for manual delineation.
Displayed: 10/11/2024 23:01