TY - JOUR A1 - Dech, Stefan A1 - Holzwarth, Stefanie A1 - Asam, Sarah A1 - Andresen, Thorsten A1 - Bachmann, Martin A1 - Boettcher, Martin A1 - Dietz, Andreas A1 - Eisfelder, Christina A1 - Frey, Corinne A1 - Gesell, Gerhard A1 - Gessner, Ursula A1 - Hirner, Andreas A1 - Hofmann, Matthias A1 - Kirches, Grit A1 - Klein, Doris A1 - Klein, Igor A1 - Kraus, Tanja A1 - Krause, Detmar A1 - Plank, Simon A1 - Popp, Thomas A1 - Reinermann, Sophie A1 - Reiners, Philipp A1 - Roessler, Sebastian A1 - Ruppert, Thomas A1 - Scherbachenko, Alexander A1 - Vignesh, Ranjitha A1 - Wolfmueller, Meinhard A1 - Zwenzner, Hendrik A1 - Kuenzer, Claudia T1 - Potential and challenges of harmonizing 40 years of AVHRR data: the TIMELINE experience JF - Remote Sensing N2 - Earth Observation satellite data allows for the monitoring of the surface of our planet at predefined intervals covering large areas. However, there is only one medium resolution sensor family in orbit that enables an observation time span of 40 and more years at a daily repeat interval. This is the AVHRR sensor family. If we want to investigate the long-term impacts of climate change on our environment, we can only do so based on data that remains available for several decades. If we then want to investigate processes with respect to climate change, we need very high temporal resolution enabling the generation of long-term time series and the derivation of related statistical parameters such as mean, variability, anomalies, and trends. The challenges to generating a well calibrated and harmonized 40-year-long time series based on AVHRR sensor data flown on 14 different platforms are enormous. However, only extremely thorough pre-processing and harmonization ensures that trends found in the data are real trends and not sensor-related (or other) artefacts. The generation of European-wide time series as a basis for the derivation of a multitude of parameters is therefore an extremely challenging task, the details of which are presented in this paper. KW - AVHRR KW - Earth Observation KW - harmonization KW - time series analysis KW - climate related trends KW - automatic processing KW - Europe KW - TIMELINE Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-246134 SN - 2072-4292 VL - 13 IS - 18 ER - TY - JOUR A1 - Reiners, Philipp A1 - Asam, Sarah A1 - Frey, Corinne A1 - Holzwarth, Stefanie A1 - Bachmann, Martin A1 - Sobrino, Jose A1 - Göttsche, Frank-M. A1 - Bendix, Jörg A1 - Kuenzer, Claudia T1 - Validation of AVHRR Land Surface Temperature with MODIS and in situ LST — a TIMELINE thematic processor JF - Remote Sensing N2 - Land Surface Temperature (LST) is an important parameter for tracing the impact of changing climatic conditions on our environment. Describing the interface between long- and shortwave radiation fluxes, as well as between turbulent heat fluxes and the ground heat flux, LST plays a crucial role in the global heat balance. Satellite-derived LST is an indispensable tool for monitoring these changes consistently over large areas and for long time periods. Data from the AVHRR (Advanced Very High-Resolution Radiometer) sensors have been available since the early 1980s. In the TIMELINE project, LST is derived for the entire operating period of AVHRR sensors over Europe at a 1 km spatial resolution. In this study, we present the validation results for the TIMELINE AVHRR daytime LST. The validation approach consists of an assessment of the temporal consistency of the AVHRR LST time series, an inter-comparison between AVHRR LST and in situ LST, and a comparison of the AVHRR LST product with concurrent MODIS (Moderate Resolution Imaging Spectroradiometer) LST. The results indicate the successful derivation of stable LST time series from multi-decadal AVHRR data. The validation results were investigated regarding different LST, TCWV and VA, as well as land cover classes. The comparisons between the TIMELINE LST product and the reference datasets show seasonal and land cover-related patterns. The LST level was found to be the most determinative factor of the error. On average, an absolute deviation of the AVHRR LST by 1.83 K from in situ LST, as well as a difference of 2.34 K from the MODIS product, was observed. KW - Land Surface Temperature KW - AVHRR KW - MODIS KW - time series KW - Europe KW - validation KW - TIMELINE Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-246051 SN - 2072-4292 VL - 13 IS - 17 ER - TY - JOUR A1 - Dietz, Andreas J. A1 - Conrad, Christopher A1 - Kuenzer, Claudia A1 - Gesell, Gerhard A1 - Dech, Stefan T1 - Identifying Changing Snow Cover Characteristics in Central Asia between 1986 and 2014 from Remote Sensing Data JF - Remote Sensing N2 - Central Asia consists of the five former Soviet States Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, and Uzbekistan, therefore comprising an area of similar to 4 Mio km(2). The continental climate is characterized by hot and dry summer months and cold winter seasons with most precipitation occurring as snowfall. Accordingly, freshwater supply is strongly depending on the amount of accumulated snow as well as the moment of its release after snowmelt. The aim of the presented study is to identify possible changes in snow cover characteristics, consisting of snow cover duration, onset and offset of snow cover season within the last 28 years. Relying on remotely sensed data originating from medium resolution imagers, these snow cover characteristics are extracted on a daily basis. The resolution of 500-1000 m allows for a subsequent analysis of changes on the scale of hydrological sub-catchments. Long-term changes are identified from this unique dataset, revealing an ongoing shift towards earlier snowmelt within the Central Asian Mountains. This shift can be observed in most upstream hydro catchments within Pamir and Tian Shan Mountains and it leads to a potential change of freshwater availability in the downstream regions, exerting additional pressure on the already tensed situation. KW - AVHRR data KW - satellite KW - Northern Xinjiang KW - cloud KW - products KW - Central Asia KW - climate change KW - Amu Darya KW - Syr Darya KW - Tian Shan KW - snow KW - snow cover KW - snow cover duration KW - Pamir KW - AVHRR KW - MODIS KW - algorithm KW - validation Y1 - 2014 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-114470 SN - 2072-4292 VL - 6 IS - 12 ER - TY - THES A1 - Dietz, Andreas T1 - Central Asian Snow Cover Characteristics between 1986 and 2012 derived from Time Series of Medium Resolution Remote Sensing Data T1 - Charakteristik der Schneebedeckung in Zentralasien zwischen 1986 und 2012 abgeleitet von Zeitreihen mittelaufgelöster Fernerkundungsdaten N2 - The eminent importance of snow cover for climatic, hydrologic, anthropogenic, and economic reasons has been widely discussed in scientific literature. Up to 50% of the Northern Hemisphere is covered by snow at least temporarily, turning snow to the most prevalent land cover types at all. Depending on regular precipitation and temperatures below freezing point it is obvious that a changing climate effects snow cover characteristics fundamentally. Such changes can have severe impacts on local, national, and even global scale. The region of Central Asia is not an exception from this general rule, but are the consequences accompanying past, present, and possible future changes in snow cover parameters of particular importance. Being characterized by continental climate with hot and dry summers most precipitation accumulates during winter and spring months in the form of snow. The population in this 4,000,000 km² vast area is strongly depending on irrigation to facilitate agriculture. Additionally, electricity is often generated by hydroelectric power stations. A large proportion of the employed water originates from snow melt during spring months, implying that changes in snow cover characteristics will automatically affect both the total amount of obtainable water and the time when this water becomes available. The presented thesis explores the question how the spatial extent of snow covered surface has evolved since the year 1986. This investigation is based on the processing of medium resolution remote sensing data originating from daily MODIS and AVHRR sensors, thus forming a unique approach of snow cover analysis in terms of temporal and spatial resolution. Not only duration but also onset and melt of snow coverage are tracked over time, analyzing for systematic changes within this 26 years lasting time span. AVHRR data are processed from raw Level 1B orbit data to Level 3 thematic snow cover products. Both, AVHRR and MODIS snow maps undergo a further post-processing, producing daily full-area mosaics while completely eliminating inherent cloud cover. Snow cover parameters are derived based on these daily and cloud-free time series, allowing for a detailed analysis of current status and changes. The results confirm the predictions made by coarse resolution predictions from climate models: Central Asian snow cover is changing, posing new challenges for the ecosystem and future water supply. The changes, however, are not aimed at only one direction. Regions with decreasing snow cover exist as well as those where the duration of snow cover increases. A shift towards earlier snow cover start and melt can be observed, posing a serious challenge to water management authorities due to a changed runoff regime. N2 - Die Bedeutung von Schneebedeckung hinsichtlich klimatischer, hydrologischer, anthropogener und ökonomischer Gesichtspunkte wurde in der wissenschaftlichen Literatur bereits umfassend diskutiert. Bis zu 50% der Nördlichen Hemisphäre sind zeitweise schneebedeckt. Abhängig von Niederschlag und Temperaturen unter dem Gefrierpunkt beeinflussen Veränderungen des Klimas zwangsläufig die Charakteristik der Schneeverteilung. Solche Veränderungen können weitreichende Folgen auf lokalem, nationalem und sogar globalem Maßstab haben. Zentralasien stellt in diesem Zusammenhang keine Ausnahme dar, denn die Konsequenzen vergangener, aktueller und möglicher zukünftiger Schneebedeckungsveränderungen sind hier besonders gravierend: Wegen des kontinentalen Klimas und den damit verbundenen trocken-heißen Sommern fällt der Hauptteil des verfügbaren Niederschlages in den Winter- und Frühlingsmonaten in Form von Schnee. Die Bevölkerung in der etwa 4.000.000 km² großen Region ist in besonderem Maße von Bewässerungslandwirtschaft abhängig. Darüber hinaus wird ein Großteil der Elektrizität durch Wasserkraftwerke erzeugt. Das für diese Zwecke verwendete Wasser generiert sich hauptsächlich durch Schneeschmelze im Frühling. Veränderungen im Schneehaushalt haben unmittelbare Auswirkungen auf die Menge des zur Verfügung stehenden Wassers sowie den Zeitpunkt, zu dem dieses frei wird. Die vorgestellte Arbeit wird der Frage nachgehen, wie sich die räumliche Ausdehnung schneebedeckter Flächen seit dem Jahr 1986 entwickelt hat. Diese Untersuchung basiert auf der Analyse mittelaufgelöster Fernerkundungsdaten der Sensoren MODIS und AVHRR, die mit der verbundenen zeitlichen und räumlichen Auflösung einen einmaligen Ansatz darstellen. Nicht nur die Schneebedeckungsdauer, sondern auch Beginn und Ende der Schneesaison werden über die Zeit hinweg verfolgt, um systematische Veränderungen innerhalb der 26 Jahre andauernden Zeitreihe analysieren zu können. Rohe AVHRR Daten werden in thematische Produkte überführt, die dann zusammen mit den MODIS Schneeprodukten prozessiert werden um tägliche, wolkenfreie Mosaike der kompletten Region zu erzeugen. Die Ergebnisse bestätigen Vorhersagen grob aufgelöster Klimamodelle: Die Schneebedeckung in Zentralasien verändert sich und stellt damit die Ökosysteme und Wasserplanungsbehörden vor neue Herausforderungen. Die Änderungen sind jedoch nicht ausschließlich negativ: Regionen mit reduzierte verringerter Schneebedeckung existieren neben solchen, in denen die Bedeckung zunimmt. Eine generelle Verschiebung der Schneebedeckung hin zu früherem Beginn und früherem Ende der Saison kann ebenfalls beobachtet werden. Gerade diese Verschiebung stellt die Behörden und Wasserplaner vor deutliche Herausforderungen, da mit diesen Verschiebungen auch eine Änderung des zugrundeliegenden Abflussregimes einhergeht. N2 - Значение снежного покрова с климатической, гидрологической, антропогенной и экономической точки зрения в научной литературе широко обсуждалось. До 50% северное полушарие временами покрытa снегом. Поэтому снег являетса, по крайней мере временно самым распространенным покрытием земли. В замисимости от осадков и температур ниже градуса звмерзения, изменения климата воздействуют на характеристику распределения снега. Такие изменения могут иметь далеко идущие последствия местного, регионального и дaже глобального масштаба. Центральная Азия в данном моменте не являетса исключенная, потому что последствия прошлых, настояших, и возможных будушщих изменений покрова снега значительны серьезные: из-за континентального климата и связанного с этим сухого жаркого лета, основная часть осадков падает на зимние и весенние месяцы в виде снега. Жители этого примерно 4.000.000 км² региона, в большой степени зависят от оросительной системы. Кроме того, большая часть электричества производится с помощью электростанций. Использумая для этого вода образуется от тайния снега весной. Изменение количества снега оказывает непосредственное влияние на каличество готовой для использования воды и на время её образования. Представленная работа рассматривает вопрос как развивалось пространственное расширение снежного покрова площадей с 1986 года. Эти иследования базироваться на процессиворании данных сеисоров MODIS и AVHRR которые представляют связанные временем и пространством показыват беспримерную методику. Не только время снежного покрова, но и начало и конец снежного сезана наблюдались в течение продолжительного времене, чтобы анализировать систематические изменения произошедшие в течение 26 лет. Результаты подтверждают предсказание модель климата с низким разрешением: снежный покров Центральной Азии изменяетса и ставит экологическую систему и управление водных планирования перед новыми задачами. Однако изменения направленн не только в одну сторону: регионы с уменьшением снежного покрова существовать рядом с такими, в которых величена снежного покрова увеличивается. Всеобщим сдвиг снежного покрова в сторону раннего начала и раннего окончания сезона так же наблюдается. Как раз эти сдвиги ставят а власти и хозяйства вода планирования перед сложные задачи, так как с этими сдвигами связаны и изменения в системе сточных вод. KW - Zentralasien KW - Satellitenfernerkundung KW - Schnee KW - Snow cover KW - MODIS KW - AVHRR KW - snow cover duration KW - Remote sensing of snow KW - Gletscherschwankung KW - Geschichte 1986 - 2012 Y1 - 2013 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-101221 ER -