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Remote Sensing of Boreal Forest Phenology: Methods and Applications

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Remote Sensing of Boreal Forest Phenology: Methods and Applications Remote sensing of boreal forest phenology: methods and applications Dissertation zur Erlangung des Doktorgrades der Naturwissenschaften (Dr. rer. nat.) Der Naturwissenschaftlichen Fakultät III Agrar- und Ernährungswissenschaften, Geowissenschaften und Informatik der Martin-Luther-Universität Halle-Wittenberg vorgelegt von Frau Kristin Böttcher Gutacher: Prof. Dr. Cornelia Gläßer Prof. Dr. Patrick Hostert Halle (Saale), 26.06.2019 (Tag der Verteidigung) Acknowledgements I am grateful to Prof. Dr. Cornelia Gläßer for her guidance and support and to Prof. Dr. Patrick Hostert for reviewing this dissertation. This work was carried out at the Finnish Environment Institute (SYKE) in Helsinki, Finland. I would like to thank my supervisors Yrjö Sucksdorff and Sampsa Koponen for providing excellent working conditions, a good spirit and for their support in writing the articles and the summary of this thesis. I would like to thank my colleagues from SYKE, especially the former snow team members: Sari Metsämäki, Olli-Pekka Mattila, Kirsikka Heinilä, Mia Salminen and Juha-Petri Kärnä for their help in many ways and for the good time we had working together on snow remote sensing. I would also like to thank Mikko Kervinen for his great help with programming and processing of MODIS data, Saku Anttila for his inspiring ideas for time series processing, as well as Kaisu Harju for publishing the vegetation phenology datasets. I am grateful to my co-authors at the Finnish Meteorological Institute: Mika Aurela, Tiina Markkanen, Tuula Aalto and Tea Thum, who helped to link remote sensing observations to CO2 flux measurements and carbon balance modelling. I would also like to thank Ali Nadir Arslan for great collaboration and support, Jouni Pulliainen for the highly valuable comments to the first articles, as well as Kimmo Rautiainen for introducing me to microwave observations and some very encouraging discussions in preparation of the defence. I am also deeply thankful for the collaboration with Juha Pöyry on insect phenology. Many thanks also to Annikki Mäkelä, Pasi Kolari, Stefan Fronzek, Maria Holmberg, Raimo Virkkala, Mikko Peltoniemi and Mikael Hildén for the very good cooperation, interesting discussions and support. Zusammenfassung Das Potential von Ökosystemen zur Bereitstellung von Leistungen, z.B. Kohlenstoff zu binden, wird vom phänologischen Zyklus der Vegetation stark beeinflusst. Informationen zum Zeitpunkt der Phänophasen werden daher benötigt, um den Einfluss des Klimawandels auf die boreale Nadelwaldzone, das größte Landökosystem der Erde, zu verstehen und vorherzusagen. Die meisten Fernerkundungsuntersuchungen zur Bestimmung von Phänophasen konzentrierten sich auf die Blattentfaltung und Blattverfärbung der laubabwerfenden Vegetation. Die entwickelten Verfahren beruhten zumeist auf der Nutzung von Vegetationsindizes, wie z.B. dem Normalised Difference Vegetation Index. Allerdings sind diese Verfahren zur Beobachtung des saisonalen Zyklus von Wachstum und Photosynthese in immergrünen Nadelwäldern der borealen Zone nur eingeschränkt nutzbar. Darüber hinaus sind optische Fernerkundungsverfahren bei zu geringem Sonnenstand im Herbst und Winter nicht anwendbar. Faktoren, die mit der Photosynthese korrelieren, wie Schneebedeckung und Bodenfrost, sind aus Fernerkundungsdaten ableitbar und könnten alternativ genutzt werden. Diese Arbeit zielte daher auf die Entwicklung von Methoden zur Bestimmung des Zeitpunktes des Beginns und der Einstellung der photosynthetischen Aktivität immergrüner Nadelwälder auf der Basis von Satellitendaten zur Schneebedeckung und zum Bodenfrost. Aus MODIS (Moderate Resolution Imaging Spectroradiometer)-Daten abgeleitete Zeitserien zur prozentualen Schneebedeckung und auf SMOS (Soil Moisture and Ocean Salinity)-Daten basierende Informationen zum Bodenfrost wurden dafür erstmals eingesetzt. Messungen des Kohlenstoffflusses an drei Standorten in Finnland dienten als Referenz. Zur Bestimmung des Zeitpunktes des Endes der photosynthetischen Aktivität wurden zusätzlich Daten von drei Standorten in Kanada genutzt. Zum Vergleich mit Satellitendaten zum Bodenfrost wurde der Zeitpunkt des Luftfrosts aus ERA-Interim Reanalyse Daten abgeleitet. Ein, auf dem NDWI (Normalised Difference Water Index) basierendes, Verfahren zur Bestimmung der Blattentfaltung der Laubwälder wurde für Finnland angepasst und mit phenologischen Beobachtungen der Blattentfaltung ausgewertet. Es wurde ein enger Zusammenhang des Beginns der photosynthetischen Aktivität mit der Schneeschmelze, und des Endes der photosynthetischen Aktivität mit dem Auftreten des ersten Luft-und Bodenfrostes festgestellt. Daher konnten diese Phänophasen aus den Zeitserien der prozentualen Schneebedeckung und des Bodenfrostes bestimmt werden. Im Vergleich zu den Satellitendaten zum Bodenfrost, wurde mit dem Tag des ersten Luftfrostes eine etwas höhere Genauigkeit für die Standorte erreicht. Der aus Satellitendaten abgeleitete Tag der Blattentfaltung zeigte eine gute Übereinstimmung mit den phänologischen Beobachtungen. Mit den Methoden konnten der Beginn und das Ende der photosynthetischen Aktivität über einen Zeitraum von 17, beziehungsweise, 6 Jahren in Finnland dargestellt werden. Die für die Nadelwälder entwickelten Methoden schließen Lücken in der Beobachtung der Phänologie der borealen Zone und ergänzen damit vorhandene Methoden für die laubabwerfende Vegetation. Die Daten sind wichtig für die Einschätzung von Ökosystemleistungen und die Beobachtung der Biodiversität. Dies wurde in dieser Arbeit mit zwei Anwendungsbeispielen gezeigt, in denen die Daten zur Bewertung modellierter Phänophasen eines Biosphärenmodells und zur Vorhersage der Phänologie von pflanzenfressenden Insekten genutzt wurden. Abstract The phenological cycle of vegetation strongly influences the potential of ecosystems to provide services, e.g. to sequester carbon. To understand and to predict the impact of climate change on the boreal forest zone, the largest terrestrial biome, information on the timing of phenological events is needed. Most remote sensing studies have focussed on the detection of vegetation greening-up and senescence. However, methods based on vegetation indices, such as the normalised difference vegetation index, have limited use for monitoring the phenology of photosynthesis and growth in the evergreen forest type. Low illumination poses an additional challenge to optical remote sensing in autumn and winter. Alternatively, environmental variables that are correlated with photosynthesis, such as snow cover and soil freeze, can be observed with remote sensing. Hence, this work focussed on the development of methods for the determination of the timing of recovery and cessation of photosynthesis in the evergreen boreal forest based on satellite observations of snow cover and soil freeze, respectively. For this, the applicability of the time series of fractional snow cover from the Moderate Resolution Imaging Spectroradiometer and soil freeze state from the Soil Moisture and Ocean Salinity mission were tested for the first time. The references for the start and end of the vegetation active period (VAPstart, VAPend) were obtained from three CO2 flux measurements sites in Finland. Additionally, three sites from Canada were employed in the development of indicators for the VAPend. The date of first autumnal freeze from a reanalysis of the air temperature was investigated in comparison to satellite obtained soil freeze data. For the detection of vegetation greening in the deciduous forest, a method based on the normalised difference water index was applied and evaluated with birch bud breaking observations in Finland. It was found that the recovery of photosynthesis in boreal evergreen forests is coupled with the timing of the snow melt. The VAPstart could be extracted from a snow cover time series with good accuracy on Finnish sites (R2=0.89, root mean squared error (RMSE)=5.3 days). In autumn, the observed strong relationship between autumn air and soil freeze with the VAPend can be utilised to determine this event from the satellite-observed date of partially frozen soil (R2=0.84, RMSE=7.5 days) but with lower accuracy than for the air temperature indicator (R2=0.92, RMSE=5.2 days). The satellite-observed vegetation greening date showed good agreement with the birch bud breaking (R2=0.75, RMSE=7.3 days). Methods were utilised to generate national- scale maps of the VAPstart and VAPend covering a period of 17 and 6 years, respectively. The developed methods for the evergreen forest fill observational gaps in the monitoring of the phenology of the boreal forest zone and complement existing ones, targeting deciduous vegetation. The maps provide relevant information for the assessment of ecosystem services and the monitoring of biodiversity. This was demonstrated in two applications, the evaluation of the phenology of a biosphere model and the prediction of the phenology of herbivorous insects. Contents List of original publications and author’s contribution ...................................................................... 5 List of acronyms and symbols ............................................................................................................ 6 1 Introduction ................................................................................................................................ 7 1.1 Phenology of boreal forests ................................................................................................ 7 1.2 Observation of vegetation phenology
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