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Mapping of spruce and pine fractional coverage at 1 ha resolution for entire Bavaria

Atzberger, Clement and Immitzer, Markus and Einzmann, Kathrin and Mattiuzzi, Matteo and Ng, Wai Tim and Pinnel, Nicole and Reichmuth, Anne and Wallner, Adelheid and Frost, Matthias and Seitz, Rudolf (2014) Mapping of spruce and pine fractional coverage at 1 ha resolution for entire Bavaria. ForestSAT 2014, 5.-7. Nov 2014, Riva del Garda, Italy.

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Abstract

In Central Europe spruce and pine are severely affected by the impacts of climate change. In several regions a significant decline in their distribution is observed. To cope with this threat, the Bavarian State Institute of Forestry produces climate risk maps for the next decades. To be effective however, locational information of the two tree species is required. Such basic information is not yet available at the necessary spatial resolution. The aim of this study is to generate distribution maps for spruce and pine for entire Bavaria (70.500 km2) at a resolution of about one hectare. For each hectare cell, the fraction coverage of the two tree species is to be specified as well as associated uncertainties. In order to meet these user-defined requirements, a two-step methodology combining satellite imagery at metric to deca-metric resolution was developed. In a first step, tree species maps with a high level of detail were generated from 8-band multispectral WorldView-2 data with 0.5 to 2.0 m spatial resolution. As reference, inventory data from the Bavaria State Forest enterprise was used. Where necessary, additional reference samples were derived from stereo interpretation of aerial images. From this data, detailed tree species maps were generated for roughly 40 sites (each about 100 km2 large) well distributed across Bavaria. For the object-based mapping, spectral information and textural indices were used. The textural measures were generated at several scales with a discrete stationary wavelet transformation (using Red, Near Infrared and NDVI as inputs). The classification itself was performed using Random Forest (RF). Features used in the classification were selected by means of RF’s importance measures. The generated tree species maps were used in a second step as reference information (targets) to generate the fractional coverage maps for the entire country using neural nets. For the upscaling, Landsat multi-temporal data complemented by high resolution RapidEye imagery was used as predictor variables. From the sites with detailed tree species maps, data from these two satellite sensors were extracted and used to train a neural network for estimating the fractional coverage of the two tree species. After network training, the models were applied to the entire area.

Item URL in elib:https://elib.dlr.de/103121/
Document Type:Conference or Workshop Item (Speech)
Additional Information:LWF Projekte
Title:Mapping of spruce and pine fractional coverage at 1 ha resolution for entire Bavaria
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Atzberger, ClementBoKu WienUNSPECIFIED
Immitzer, MarkusBoKu WienUNSPECIFIED
Einzmann, KathrinBoKu WienUNSPECIFIED
Mattiuzzi, MatteoBoKu WienUNSPECIFIED
Ng, Wai TimBoKu WienUNSPECIFIED
Pinnel, Nicolenicole.pinnel (at) dlr.deUNSPECIFIED
Reichmuth, Anneanne.reichmuth (at) dlr.deUNSPECIFIED
Wallner, AdelheidBayerische Landesanstalt für Wald und ForstUNSPECIFIED
Frost, MatthiasBayerische Staatsforsten AöR (BaySf)UNSPECIFIED
Seitz, RudolfBayerische Landesanstalt für Wald und ForstUNSPECIFIED
Date:2014
Refereed publication:No
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:Published
Keywords:RapidEye, spruce, Random Forest, Bavaria, remote sensing, climate change
Event Title:ForestSAT 2014
Event Location:Riva del Garda, Italy
Event Type:international Conference
Event Dates:5.-7. Nov 2014
Organizer:Fondazione Edmund Mach, Italy
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Vorhaben Fernerkundung der Landoberfläche (old)
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center > Land Surface
Deposited By: Pinnel, Dr.rer.nat Nicole
Deposited On:22 Feb 2016 09:54
Last Modified:10 May 2016 23:45

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