An earth observation based service for the monitoring ... - RESA Web

An earth observation based service for the 

monitoring of large-scale damages in forestry 

Matthias Dees 

Abteilung Fernerkundung und Landschaftsinformationssysteme 

Albert-Ludwigs Universität Freiburg 

4th User Workshop 

RESA – Data for science „From algorithm to product“ 

Neustrelitz, Germany, 21-22 of March 2012 

Prepared by 

Matthias Dees1 , Gernot Ramminger2 , Herbert Sagischevski3 , 

Sergej Chmara3 , Jörg Ermert 1 , Barbara Koch1 1 Department of Remote Sensing and Landscape Information Systems, Albert-Ludwigs Universität Freiburg, 

79085 Freiburg, Germany. Email: matthias.dees@felis.uni-freiburg.de 

2 GAF AG, Munich, Germany 

3 Service und-Kompetenzzentrum, ThüringenForst – Anstalt öffentlichen Rechts, Gotha, Thuringa, Germany

EUFODOS & RESA Proposal No. 460 

RESA Proposal No. 460 

Monitoring von forstlichen 

Großschadensereignissen 

in Rahmen des GMES 

„Downstream“ Projekts 

„European Forest 

Downstream Services - 

Improved Information on 

Forest Structure and 

Damages (EUFODOS)” 

Design, Development and 

Implementation of Downstream Services 

in the field of forest damages and forest 

parameters on sub-national, regional 

level. 

15 partners (incl. 7 users) 

Lead: Joanneum Research (Austria) 

Focus: Utilisation of Rapid Eye for large 

scale damages in forests 

biotic damages 

bark beetle 

Ips typographus / Spruce 

…. 

…. 

abiotic damages 

storm 

snow 

… 

University of Freiburg in cooperation with 

GAF AG & Service und- 

Kompetenzzentrum, ThüringenForst 

An earth observation based service for the monitoring of large-scale damages in forestry Matthias.Dees@felis.uni-freiburg.de 

01/2011 

03/2012 

12/2013 

Project duration 

& 

status

Relevance of damages in the forest sector 

• Due to climate change, growth conditions will change and disturbances will 

increase (Seppälä et al. 2009, Thompson 2009). 

• The changes in climate are expected to increase droughts (Allen et al. 

2010) and storm damages (Gardiner et al. 2010). 

• According to a recently conducted enquiry among the Members of Standing 

Forestry Committee on behalf of Directorate General (DG) Environment on 

the major threats to European forests, insects and storm/windfall have 

been identified as the most important damaging agents (Requardt et al. 

2007) 

• From 1950 to 2000 the annual average timber volume damaged by 

disturbances in European forests was 35 million m³, caused 53% by 

storms, 16% by fire, 8% by bark beetles and 8% by other biotic factors 

(Schelhaas 2008). 

• Forest damage from storms for example can cause large economic losses 

to a country such as Germany, which experienced a storm in 2007 that 

affected approximately 20 million m3, and cost the country’s forestry 

industry about EURO 1 billion in lost revenue and damages (MCPFE 2007). 

(References: see extended Abstract) 

An earth observation based service for the monitoring of large-scale damages in forestry Matthias.Dees@felis.uni-freiburg.de

Need & opportunity & challenges for EO 

based operational services 

• New data EO options 

• Rapid Eye 

• Sentinels 

• TerrraSAR , 

• TADENM X 

• …. 

• GMES data services (Image 2006, image 2009, …) 

• GMES land area related data and product services planed within GMES that are 

expected to be fully operationally available from 2013 on (EEA, 2011) 

• INSPIRE implementation 

Better data quality 

Better timely coverage, faster delivery 

Improved accessibility & affordability 

Improved analysis options 

Increased accuracy of mapping options 

Cheaper services 

Need to develop, improve 

and demonstrate service 

options to users to 

prepare the demand side 


Role of Service und-Kompetenzzentrum, 

ThüringenForst 

SUK ThüringenForst is responsible for the analysis 

of the user needs, reference data, product and 

service evaluation and in close cooperation with 

ALU-FR and GAF for planning of data acquisition 

timing and for an optimisation and testing of the 

integration of the offered service into the 

operational workflow. 

Major elements needed for the data acquisition planning 

Bark beetle population dynamic prediction 

- trap based 

- weather data based 

- field inspection based 

Storm & snow & bark beetle damage occurrence / 

Harvesting operations recording 

- field inspection based 

- recorded in stand based GIS on 




Trap based 

prediction of the 

population dynamic 

of bark beetles 




Weather data 

based prediction of 

the population 

dynamic of bark 

beetles 


Role of GAF AG 

© G. Ramminger, GAF AG 

© ALU-FR 

GAF responsible for the Development and 

Implementation of EO based systems for the 

assessment of forest storm damaged areas 

as well as the monitoring of bark beetle 

damages (Research component together with 

University of) 

Assessment of storm damaged areas based on EO Satellite Data 

in the absence of a storm in 2011 in Thuringia the scope of work was expanded to 

mapping of snow damages from winter 2010/11 


4m Ikonos multispectral Storm damaged area after Storm Lothar 1999 


Role of University of Freiburg 

© J.Ermert ALU-Fr - FELIS 

University of Freiburg 

responsible for 

research component 

& support of GAF in 

the Development and 

Implementation of EO 

based systems for the 

assessment of forest 

storm damaged 

areas 

Assessment of storm damaged areas, snow damaged areas, bark beetle damages 

in the absence of a storm & bark beetle damages in 2011 in Thuringia 

The scope of work was expanded to 

• the assessment of operational harvesting in Thuringia 

• Storm damage in Poland: forest district of Bogdaniec, 11.09.2011 

• Bark beetle damages in a protected forest in the Black Forest, Germany, where harvesting is 

banned (Bannwald Wilder See) 


EUFODOS – Overview about Services 

Fast Storm Damage 

Assessment 

• provision of results 

within 1 to 2 weeks 

after storm event 

• MMU < 3ha 

• Accuracy > 90% 

IKONOS fused image (Pan+ms) 


Detailed Assessment 

of Storm Damages 

• provision of results 

within 2 to 3 months 

after storm event 

• MMU < 0.3 ha 


IKONOS multispectral 

© J. Ermert, FeLis, Univ. Freiburg 

Assessment of Insect 

Infested Damages 

• regular updates during 

bark beetle season 

(May to August) 

• bark beetle infected 

trees or a collective of 

infected trees 


CIR-Photo, © NW-FVA 

© FeLIS, Univ. Freiburg 


EO Data availability for Core product 

simulation & product generation 

Image 

2009 

20m multispectral (NIR + SWIR) HR scenes 

from Image 2009 dataset 

- 3x SPOT-4 (Acq. Date: summer 2008/09) 

- 3x SPOT-5 (Acq. Date: 05.08.2010) 

- 2x IRS LISS-III (Acq. Date: 04.10.2010) 

RapidEye scenes mainly from 2011 (RESA 

and GSCDA) for Damage Assessment 

(Snow, Storm, Bark Beetle) based on 

Change Detection 


EO Data availability for Core product 

simulation & product generation 

RapidEye scenes mainly from 2009 & 2011 (RESA and GSCDA) for 

Damage Assessment (Snow, Storm, Bark Beetle) based on Change 

Detection 


HR Forest Core Layer (e.g. Tree Cover Density) 

Processing Steps Tree Cover Density 

- Pre-Processing of EO data 

(not relevant for Image 2006, 

Image 2009) 

- Simulation/Classification of 

HR Forest Core Layer (test 

site was not a demonstration 

site in geoland2) based on 

Image 2009 

© GAF AG 

© GAF AG 

per Pixel [0-100%] 

Spatial Resolution: 20m 


Processing Line Development 

Processing Steps 

Segment based 

approach for change 

detection tailored for 

the specific damage or 

change type using 

simulated CORE Forest 

Layer, Image 2009 and 

Rapideye data from 

2011 

GAF AG 


Processing Line Development 

This is pre-operational 

standard approach that 

will be applied for all 

products. 

It will be accompanied by 

testing of a variety of 

change detection options. 

For fast processing, a prerequisite 

for the 

necessary fast product 

delivery a processing line 

based on a tool box will 

be implemented. 

GAF AG 


Snow damage assessment 

Generation of reference 

data using visual 

interpretation and 

harvesting recordings, 

partly assisted by field 

inspections 

© J. Ermert, FeLis, Univ. Freiburg 

© RapidEye AG 



Operational harvesting 



© RapidEye AG

Assessment of operational harvesting 




Outlook: Work envisaged for a site in Poland 

Storm damage in Poland on 11.09.2011 

in the forest district of Bogdaniec, forest directorate of Szczecin 



Storm damage mapping 

Zdj. 1: Powierzchnia objęta zdjęciami 

Rapid Eye (przykład). Żόłty kwadrat 

oznacza wycinek obszaru 

badań, ktόry jest rόwnież pokazany w 

powiększeniu na zdjęciach poniżej. 

Location of storm damages 

within the forest district 






Storm damages 

Rapid eye, June 2011 Sept 2011 



Operational harvesting mapping feasibility assessment 


© RapidEye AG

Overall Outlook 


post event demonstration example is secured 

readiness for “real case” demonstration example 

ensuring fast delivery 

• linkage of user networks and EO data providers 

• production line ensuring fast delivery 

Bark beetle mapping 

trying to reduce the gap between user needs and EO capabilities 

Operational harvesting 

feasibility assessment to interest users outside the project user group

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