Forest Structure Characterization in Germany: Novel Products and Analysis Based on GEDI, Sentinel-1 and Sentinel-2 Data

Monitoring forest conditions is an essential task in the context of global climate change to preserve biodiversity, protect carbon sinks and foster future forest resilience. Severe impacts of heatwaves and droughts triggering cascading effects such as insect infestation are challenging the semi-natu...

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Main Authors: Patrick Kacic, Frank Thonfeld, Ursula Gessner, Claudia Kuenzer
Format: Article
Language:English
Published: MDPI AG 2023-04-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/15/8/1969
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author Patrick Kacic
Frank Thonfeld
Ursula Gessner
Claudia Kuenzer
author_facet Patrick Kacic
Frank Thonfeld
Ursula Gessner
Claudia Kuenzer
author_sort Patrick Kacic
collection DOAJ
description Monitoring forest conditions is an essential task in the context of global climate change to preserve biodiversity, protect carbon sinks and foster future forest resilience. Severe impacts of heatwaves and droughts triggering cascading effects such as insect infestation are challenging the semi-natural forests in Germany. As a consequence of repeated drought years since 2018, large-scale canopy cover loss has occurred calling for an improved disturbance monitoring and assessment of forest structure conditions. The present study demonstrates the potential of complementary remote sensing sensors to generate wall-to-wall products of forest structure for Germany. The combination of high spatial and temporal resolution imagery from Sentinel-1 (Synthetic Aperture Radar, SAR) and Sentinel-2 (multispectral) with novel samples on forest structure from the Global Ecosystem Dynamics Investigation (GEDI, LiDAR, Light detection and ranging) enables the analysis of forest structure dynamics. Modeling the three-dimensional structure of forests from GEDI samples in machine learning models reveals the recent changes in German forests due to disturbances (e.g., canopy cover degradation, salvage logging). This first consistent data set on forest structure for Germany from 2017 to 2022 provides information of forest canopy height, forest canopy cover and forest biomass and allows estimating recent forest conditions at 10 m spatial resolution. The wall-to-wall maps of the forest structure support a better understanding of post-disturbance forest structure and forest resilience.
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spelling doaj.art-8fe06b51b67e4b43b837d852620d996c2023-11-17T21:10:10ZengMDPI AGRemote Sensing2072-42922023-04-01158196910.3390/rs15081969Forest Structure Characterization in Germany: Novel Products and Analysis Based on GEDI, Sentinel-1 and Sentinel-2 DataPatrick Kacic0Frank Thonfeld1Ursula Gessner2Claudia Kuenzer3Department of Remote Sensing, Institute of Geography and Geology, University of Würzburg, 97074 Würzburg, GermanyGerman Remote Sensing Data Center (DFD), German Aerospace Center (DLR), 82234 Wessling, GermanyGerman Remote Sensing Data Center (DFD), German Aerospace Center (DLR), 82234 Wessling, GermanyDepartment of Remote Sensing, Institute of Geography and Geology, University of Würzburg, 97074 Würzburg, GermanyMonitoring forest conditions is an essential task in the context of global climate change to preserve biodiversity, protect carbon sinks and foster future forest resilience. Severe impacts of heatwaves and droughts triggering cascading effects such as insect infestation are challenging the semi-natural forests in Germany. As a consequence of repeated drought years since 2018, large-scale canopy cover loss has occurred calling for an improved disturbance monitoring and assessment of forest structure conditions. The present study demonstrates the potential of complementary remote sensing sensors to generate wall-to-wall products of forest structure for Germany. The combination of high spatial and temporal resolution imagery from Sentinel-1 (Synthetic Aperture Radar, SAR) and Sentinel-2 (multispectral) with novel samples on forest structure from the Global Ecosystem Dynamics Investigation (GEDI, LiDAR, Light detection and ranging) enables the analysis of forest structure dynamics. Modeling the three-dimensional structure of forests from GEDI samples in machine learning models reveals the recent changes in German forests due to disturbances (e.g., canopy cover degradation, salvage logging). This first consistent data set on forest structure for Germany from 2017 to 2022 provides information of forest canopy height, forest canopy cover and forest biomass and allows estimating recent forest conditions at 10 m spatial resolution. The wall-to-wall maps of the forest structure support a better understanding of post-disturbance forest structure and forest resilience.https://www.mdpi.com/2072-4292/15/8/1969forestforest structure Germanycanopy heightGlobal Ecosystem Dynamics InvestigationGEDISentinel-1
spellingShingle Patrick Kacic
Frank Thonfeld
Ursula Gessner
Claudia Kuenzer
Forest Structure Characterization in Germany: Novel Products and Analysis Based on GEDI, Sentinel-1 and Sentinel-2 Data
Remote Sensing
forest
forest structure Germany
canopy height
Global Ecosystem Dynamics Investigation
GEDI
Sentinel-1
title Forest Structure Characterization in Germany: Novel Products and Analysis Based on GEDI, Sentinel-1 and Sentinel-2 Data
title_full Forest Structure Characterization in Germany: Novel Products and Analysis Based on GEDI, Sentinel-1 and Sentinel-2 Data
title_fullStr Forest Structure Characterization in Germany: Novel Products and Analysis Based on GEDI, Sentinel-1 and Sentinel-2 Data
title_full_unstemmed Forest Structure Characterization in Germany: Novel Products and Analysis Based on GEDI, Sentinel-1 and Sentinel-2 Data
title_short Forest Structure Characterization in Germany: Novel Products and Analysis Based on GEDI, Sentinel-1 and Sentinel-2 Data
title_sort forest structure characterization in germany novel products and analysis based on gedi sentinel 1 and sentinel 2 data
topic forest
forest structure Germany
canopy height
Global Ecosystem Dynamics Investigation
GEDI
Sentinel-1
url https://www.mdpi.com/2072-4292/15/8/1969
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