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Development of a Web-Based Fire Danger Forecasting System For A FIRE DANGER FORECASTING PLATFORM FOR SARDINIA Development of a web-based Fire Danger Forecasting System for Mediterranean Landscapes using Open Source Software and crowd-sourced Weather Data - the Isle of Sardinia (Italy) as an Example Dissertation zur Erlangung des Doktorgrades der Mathematisch-Naturwissenschaftlichen Fakult¨atder Christian-Albrechts-Universit¨atzu Kiel vorgelegt von Dipl.-Geogr. Michael Nolde Kiel, 2013 Erster Gutachter: Prof. Dr. Rainer Duttmann Zweiter Gutachter: Prof. Dr. Athanasios Vafeidis Tag der m¨undlichen Pr¨ufung: 21. August 2013 Zum Druck genehmigt: 21. August 2013 gez. Prof. Dr. Wolfgang J. Duschl, Dekan Michael Nolde Blocksberg 11b, 24103 Kiel geboren am 9. Januar 1982 in Karlsruhe Staatsangeh¨origkeit: deutsch Studiengang: Diplom-Geographie Nebenf¨acher: Informatik und Ozeanographie, Politische Wissenschaft bis einschließlich Vordiplom Abschluss: Diplom Titel der Diplomarbeit: Development of an application for spatial and temporal analyses of wildfires using hot spot satellite data Wissenschaftlicher Werdegang: 10/2002 - 04/2009 Studium der Geographie an der Christian- Albrechts - Universit¨at zu Kiel (elf Studiensemester) ab 01/2008: Anstellung als studentische Hilfskraft am Lehrstuhl f¨ur Landschafts- ¨okologie und Geoinformation 07/2006 - 06/2007 Studium an der Naturwissenschaftlich- Technischen Universit¨at Trondheim, Norwegen (zwei Studiensemester) seit 06/2009 Wissenschaftlicher Mitarbeiter am Lehrstuhl f¨ur Landschafts¨okologie und Geoinformation der CAU Kiel Bibliographic Information Faculty: Faculty of Mathematics and Natural Sciences Department: Geography Author: Dipl.-Geogr. Michael Nolde Degree programm: Geography (Diploma) Student register: 685205 Work description: Doctoral thesis Title: Development of a web-based Fire Danger Forecasting System for Mediterranean Landscapes using Open Source Software and crowd sourced Weather Data - the Isle of Sardinia (Italy) as an Example Amount: 160 pages, 35 figures, 25 tables, 25 scripts Advisor: Prof. Dr. Rainer Duttmann Co-reviewer: Prof. Dr. Athanasios Vafeidis Closing date: Keywords: Wildfire Forecasting, Sardinia, FWI Minimal Abstract: This thesis covers the preparation and realisation of setting up a fire danger forecasting platform for the Isle of Sardinia. The system created uses, firstly, crowd sourced weather data as input for calculation of fire danger predictions and, secondly, only free and open source software for the actual implementation. The platform is meant to provide regional, daily fire danger forecasting maps. Its configuration is based on a ten-year study of fire occurrence on Sardinia and Crete. The Fire Weather Index (FWI) with threshold values adapted to Sardinia is used for the forecasts. meiner Familie, meinen Freunden, und Reidun im Besonderen Acknowledgements I would like to thank my doctoral thesis supervisor, Prof. Dr. Rainer Duttmann as well as my co-reviewer, Prof. Dr. Athanasios Vafeidis, for assistance and advice. Furthermore, many thanks to those who supported this work with additional suggestions and helpful informa- tion, including the staff of FIRMS, DWD, and EFFIS, as well as to my colleagues, friends and family. I express my deepest gratitude to Reidun for her constant motivational support and for the tremen- dous effort of proofreading this thesis. I also like to thank Lennart and Michael for final spell checking and feedback regarding statistics, respectively. Finally, I would like to acknowledge the software contrib- utors in the geospatial Open Source community, especially the ones concerned with the development of GDAL/OGR, GRASS, and GMT. Cover - Illustration: Adapted from: Turner, J.A. 1973. A Fire Load Index for British Columbia. Environment Canada, Canadian Forestry Service, Forest Research Lab. Information Report BC-X-80. "A little fire is quickly trodden out, Which being suffer'd, Rivers cannot quench." Shakespeare, Henry the Sixth. Part 3, Act 4, Scene 8 / Clarence Abstract This thesis aims at creating spatially and temporally differentiated wildfire danger forecasts for the Mediterranean area. It also intends to enhance the prediction quality of existing systems regarding reliability, spatial accuracy and prediction period. Exclusively freely available weather data serves as a base for the pre- dictions. This work further tries to illustrate the usability of this data as a replacement or supplement to proprietary data. The Isle of Sar- dinia is used as a region of study representative for Mediterranean conditions. Also, the Isle of Crete serves as a testing region to ensure the portability of the forecasting methodology to other regions in the Mediterranean. This methodology is further integrated into a web-based, autonomous platform for prediction purposes, providing daily maps of wildfire dan- ger for the region of study. The conception and realisation of this platform is explicitly described in this work. A long-term study of the occurrence of wildfire on the islands of Sar- dinia and Crete between 2001 and 2010 serves as a means of calibra- tion of the forecasting system. Additionally, historical weather data is used to retrospectively generate wildfire danger forecasting maps, which are then compared with the actual occurrence of fires. The Weather Underground network, which is supplied by crowd sourc- ing, serves as source of the required historical data. Information on wildfire occurrences are taken from MODIS hotspot data. Further datasets regarding land usage and burned areas are utilised to filter and validate the fire occurrence data. The Canadian Fire Weather Index (FWI) serves as a means of esti- mating actual fire danger based on weather data. It is widely used as a general indicator of probability of fire occurrence. Two different classification schemes are utilised to classify the FWI outputs into classes of fire danger, ranging from 'very low' to 'extreme': Firstly, the scheme of the European Forest Fire Information Systems (EFFIS), and, secondly, a scheme developed within this thesis, which is based on the findings of the long-term study and especially adjusted for usage on Sardinia. Both classifications are tested regarding the yielded results. Their ratio of false alarms as well as their recall ratio (type I and type II - error) serve as validation criteria. The testing results illustrate the superiority of the newly developed classification in respect to reduc- tion of false alarms: While these occur in only 14.8% of cases using the new scheme, the percentage is more than twice as high - 34.2% - when using the scheme of EFFIS. However, the EFFIS methodology exhibits a better recall ratio: Only in 2% of cases, fires occurred in areas classified as 'not endangered'. Using the scheme developed in this thesis, these cases amount to 13.3%. This result is mainly due to inadequate fuel moisture modelling. Therefore, this modelling pro- cedure should be optimised in order for the system to be capable of producing a more realistic picture of actual fire danger. The well-working system was tested against the forecasting results published by EFFIS during summer 2012. While the results generally tend to be more moderate in terms of fire danger compared to EFFIS, the prediction of fire danger is closer to real conditions. Daily forecasting results for the next ten days are available online via: http://www.sardinia-fireweather.org The fire danger maps can also be consumed in form of a Web Map Service (WMS) or as a mobile application. The implementation itself is free to download, use and modify under the terms of the GNU GPL. All scripts required for the operation of the forecasting platform are given in the appendix of this thesis. Zusammenfassung Die vorliegende Arbeit hat die Erstellung von r¨aumlich und zeitlich differenzierten Waldbrand-Gefahrenvorhersagen im Mittelmeerraum zum Ziel. Dabei soll die Vorhersagequalit¨atvon derzeit bestehenden Vorhersagesystemen bez¨uglich Verl¨asslichkeit, r¨aumlicher Genauigkeit und Vorhersagedauer verbessert werden. Als Datengrundlage f¨urdie Vorhersagen werden ausschließlich frei verf¨ugbareWetterdaten verwendet. Es ist ebenfalls ein Ziel dieser Ar- beit, die Verwendbarkeit dieser Daten als Ersatz oder Erg¨anzung zu propriet¨arenDaten aufzuzeigen. Die Mittelmeerinsel Sardinien wird als repr¨asentatives Untersuchungsgebiet verwendet. Weiterhin dient die Insel Kreta als Testanwendungsgebiet, um die Ubertragbarkeit¨ der Vorhersagemethodik auf andere Mittelmeerregionen zu gew¨ahrleisten. Diese Methodik wird im Weiteren in eine autonom funktionierende, web-basierte Vorhersageplattform implementiert, die t¨agliche Wald- brand-Gefahrenlandkarten f¨urdas Untersuchungsgebiet bereitstellt. Die Konzeption und Realisierung dieser Plattform wird in dieser Ar- beit detailliert beschrieben. Um das Vorhersagesystem zu kalibrieren, wird in einer Langzeit-Studie das Vorkommen von Waldbr¨andenauf Sardinien und Kreta f¨urden Zeitraum von 2001 bis 2010 untersucht. Parallel werden f¨urjeden Tag in diesem Zeitraum aus archivierten Wetterdaten r¨uckblickend Waldbrand-Gefahrenkarten erstellt, die dann mit den tats¨achlich einge- tretenen Brandereignissen verglichen werden. Als Datengrundlage f¨ur die historischen Wetterbedingungen dienen Daten aus dem Weather Underground - Netzwerk, die von Privatpersonen bereitgestellt wer- den. Als Informationsquelle f¨uraufgetretene Br¨andewerden MODIS Hotspot - Daten verwendet. Diese wurden zuvor mit Hilfe weiterer Datens¨atzezu Landnutzung und verbrannten Gebieten validiert und gefiltert. Die Absch¨atzungtats¨achlicher Waldbrandgefahr auf der Basis von Wetterinformationen
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