Automated Land Cover Change Detection and Forest Succession Monitoring Using LiDAR Point Clouds and GIS Analyses

Marta Szostak

doi:10.3390/geosciences10080321

Marta Szostak

Open Access

https://doi.org/10.3390/geosciences10080321

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Journal: Geosciences	Publication Date: Aug 17, 2020
Citations: 10	License type: CC BY 4.0

Affiliation: University of Agriculture in Krakow

Abstract

This paper investigates the possibility of applying light detection and ranging (LiDAR) point clouds and geographic information system (GIS) analyses for land use and land cover (LULC) change detection, mainly with a view to monitoring uncontrolled forest succession occurring on postagricultural lands. The research was conducted in a part of the administrative district of Milicz (in the central-west area of Poland). The areas of interest were parcels in which agricultural use has been abandoned and forest succession processes have progressed. The airborne laser scanning (ALS) data (acquired in 2007, 2012, and 2015) revealed detailed changes in land cover as a result of the progression in the forest succession process. Using the ALS data, the LULC changes and the progress of secondary forest succession are shown, and the vegetation parameters (LiDAR metrics) are presented.

Highlights

IntroductionThe introduction of light detection and ranging (LiDAR) technology in environmental management has enabled ground and vegetation cover models such as the digital surface model (DSM) and the normalized DSM (nDSM) to represent the relative height of trees and shrubs from the ground surface
The introduction of light detection and ranging (LiDAR) technology in environmental management has enabled ground and vegetation cover models such as the digital surface model (DSM) and the normalized DSM to represent the relative height of trees and shrubs from the ground surface.These are in addition to ground topography models such as the digital terrain model (DTM).Airborne laser scanning (ALS), a type of LiDAR, collects 2D and 3D information useful for the identification of the spatial characteristics of vegetation [1,2,3,4,5,6,7,8] and the assessment of forest succession areas, according to the National Program for Increasing Forest Cover
The semiautomated airborne laser scanning (ALS) point cloud processing method presented in this study demonstrates the possibility of detecting forest succession and provides an objective and relatively accurate assessment of the information about the total area of secondary forest succession

Summary

Introduction

The introduction of light detection and ranging (LiDAR) technology in environmental management has enabled ground and vegetation cover models such as the digital surface model (DSM) and the normalized DSM (nDSM) to represent the relative height of trees and shrubs from the ground surface. Airborne laser scanning (ALS), a type of LiDAR, collects 2D and 3D information useful for the identification of the spatial characteristics of vegetation [1,2,3,4,5,6,7,8] and the assessment of forest succession areas, according to the National Program for Increasing Forest Cover. The European Commission accepted new rules in 2018 that, for the first time, permitted the application of remote sensing technologies in the Geosciences 2020, 10, 321; doi:10.3390/geosciences10080321 www.mdpi.com/journal/geosciences

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