@phdthesis{Ring2018,
  author    = {Ring, Christoph},
  title     = {Entwicklung und Vergleich von Gewichtungsmetriken zur Analyse probabilistischer Klimaprojektionen aktueller Modellensembles},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-157294},
  school      = {Universit{\"a}t W{\"u}rzburg},
  pages     = {XII, 195},
  year      = {2018},
  abstract  = {Der anthropogene Klimawandel ist eine der gr{\"o}ßten Herausforderungen des 21. Jahrhunderts. Eine Hauptschwierigkeit liegt dabei in der Unsicherheit bez{\"u}glich der regionalen {\"A}nderung von Niederschlag und Temperatur. Hierdurch wird die Entwicklung geeigneter Anpassungsstrategien deutlich erschwert. In der vorliegenden Arbeit werden vier Evaluationsans{\"a}tze mit insgesamt 13 Metriken f{\"u}r aktuelle globale (zwei Generationen) und regionale Klimamodelle entwickelt und verglichen, um anschließend eine Analyse der Projektionsunsicherheit vorzunehmen. Basierend auf den erstellten Modellbewertungen werden durch Gewichtung Aussagen {\"u}ber den Unsicherheitsbereich des zuk{\"u}nftigen Klimas getroffen. Die Evaluation der Modelle wird im Mittelmeerraum sowie in acht Unterregionen durchgef{\"u}hrt. Dabei wird der saisonale Trend von Temperatur und Niederschlag im Evaluationszeitraum 1960-2009 ausgewertet. Zus{\"a}tzlich wird f{\"u}r bestimmte Metriken jeweils das klimatologische Mittel oder die harmonischen Zeitreiheneigenschaften evaluiert. Abschließend werden zum Test der {\"U}bertragbarkeit der Ergebnisse neben den Hauptuntersuchungsgebieten sechs global verteilte Regionen untersucht. Außerdem wird die zeitliche Konsistenz durch Analyse eines zweiten, leicht versetzten Evaluationszeitraums behandelt, sowie die Abh{\"a}ngigkeit der Modellbewertungen von verschiedenen Referenzdaten mit Hilfe von insgesamt drei Referenzdatens{\"a}tzen untersucht. Die Ergebnisse legen nahe, dass nahezu alle Metriken zur Modellevaluierung geeignet sind. Die Auswertung unterschiedlicher Variablen und Regionen erzeugt Modellbewertungen, die sich in den Kontext aktueller Forschungsergebnisse einf{\"u}gen. So wurde die Leistung der globalen Klimamodelle der neusten Generation (2013) im Vergleich zur Vorg{\"a}ngergeneration (2007) im Schnitt {\"a}hnlich hoch bzw. in vielen Situationen auch st{\"a}rker eingeordnet. Ein durchweg bestes Modell konnte nicht festgestellt werden. Der Großteil der entwickelten Metriken zeigt f{\"u}r {\"a}hnliche Situationen {\"u}bereinstimmende Modellbewertungen. Bei der Gewichtung hat sich der Niederschlag als besonders geeignet herausgestellt. Grund hierf{\"u}r sind die im Schnitt deutlichen Unterschiede der Modellleistungen in Zusammenhang mit einer geringeren Simulationsg{\"u}te. Umgekehrt zeigen die Metriken f{\"u}r die Modelle der Temperatur allgemein {\"u}berwiegend hohe Evaluationsergebnisse, wodurch nur wenig Informationsgewinn durch Gewichtung erreicht werden kann. W{\"a}hrend die Metriken gut f{\"u}r unterschiedliche Regionen und Skalenniveaus verwendet werden Evaluationszeitr{\"a}ume nicht grunds{\"a}tzlich gegeben. Zus{\"a}tzlich zeigen die Modellranglisten unterschiedlicher Regionen und Jahreszeiten h{\"a}ufig nur geringe Korrelationen. Dies gilt besonders f{\"u}r den Niederschlag. Bei der Temperatur sind hingegen leichte {\"U}bereinstimmungen auszumachen. Beim Vergleich der mittleren Ranglisten {\"u}ber alle Modellbewertungen und Situationen der Hauptregionen des Mittelmeerraums mit den Globalregionen besteht eine signifikante Korrelation von 0,39 f{\"u}r Temperatur, w{\"a}hrend sie f{\"u}r Niederschlag um null liegt. Dieses Ergebnis ist f{\"u}r alle drei verwendeten Referenzdatens{\"a}tze im Mittelmeerraum g{\"u}ltig. So schwankt die Korrelation der Modellbewertungen des Niederschlags f{\"u}r unterschiedliche Referenzdatens{\"a}tze immer um Null und die der Temperaturranglisten zwischen 0,36 und 0,44. Generell werden die Metriken als geeignete Evaluationswerkzeuge f{\"u}r Klimamodelle eingestuft. Daher k{\"o}nnen sie einen Beitrag zur {\"A}nderung des Unsicherheitsbereichs und damit zur St{\"a}rkung des Vertrauens in Klimaprojektionen leisten. Die Abh{\"a}ngigkeit der Modellbewertungen von Region und Untersuchungszeitraum muss dabei jedoch ber{\"u}cksichtigt werden. So besitzt die Analyse der Konsistenz von Modellbewertungen sowie der St{\"a}rken und Schw{\"a}chen der Klimamodelle großes Potential f{\"u}r folgende Studien, um das Vertrauen in Modellprojektionen weiter zu steigern.},
  subject      = {Anthropogene Klima{\"a}nderung},
  language  = {de}
}
@phdthesis{Wohlfart2018,
  author    = {Wohlfart, Christian},
  title     = {The Yellow River Basin in Transition - Multi-faceted Land Cover Change Analysis in the Yellow River Basin in the Context of Global Change Using Multi-sensor Remote Sensing Imagery},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-163724},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2018},
  abstract  = {As a cradle of ancient Chinese civilization, the Yellow River Basin has a very long human-environment interrelationship, where early anthropogenic activities re- sulted in large scale landscape modifications. Today, the impact of this relationship has intensified further as the basin plays a vital role for China's continued economic development. It is one of the most densely-populated, fastest growing, and most dynamic regions of China with abundant natural and environmental resources providing a livelihood for almost 190 million people. Triggered by fundamental economic reforms, the basin has witnessed a spectacular economic boom during the last decades and can be considered as an exemplary blueprint region for contemporary dynamic Global Change processes occurring throughout the country, which is currently transitioning from an agrarian-dominated economy into a modern urbanized society. However, this resourcesdemanding growth has led to profound land use changes with adverse effects on the Yellow River social-ecological systems, where complex challenges arise threatening a long-term sustainable development. Consistent and continuous remote sensing-based monitoring of recent and past land cover and land use change is a fundamental requirement to mitigate the adverse impacts of Global Change processes. Nowadays, technical advancement and the multitude of available satellite sensors, in combination with the opening of data archives, allow the creation of new research perspectives in regional land cover applications over heterogeneous landscapes at large spatial scales. Despite the urgent need to better understand the prevailing dynamics and underlying factors influencing the current processes, detailed regional specific land cover data and change information are surprisingly absent for this region. In view of the noted research gaps and contemporary developments, three major objectives are defined in this thesis. First (i), the current and most pressing social-ecological challenges are elaborated and policy and management instruments towards more sustainability are discussed. Second (ii), this thesis provides new and improved insights on the current land cover state and dynamics of the entire Yellow River Basin. Finally (iii), the most dominant processes related to mining, agriculture, forest, and urban dynamics are determined on finer spatial and temporal scales. The complex and manifold problems and challenges that result from long-term abuse of the water and land resources in the basin have been underpinned by policy choices, cultural attitude, and institutions that have evolved over centuries in China. The tremendous economic growth that has been mainly achieved by extracting water and exploiting land resources in a rigorous, but unsustainable manner, might not only offset the economic benefits, but could also foster social unrest. Since the early emergence of the first Chinese dynasties, flooding was considered historically as a primary issue in river management and major achievements have been made to tame the wild nature of the Yellow River. Whereas flooding is therefore largely now under control, new environmental and social problems have evolved, including soil and water pollution, ecological degradation, biodiversity decline, and food security, all being further aggravated by anthropogenic climate change. To resolve the contemporary and complex challenges, many individual environmental laws and regulations have been enacted by various Chinese ministries. However, these policies often pursue different, often contradictory goals, are too general to tackle specific problems and are usually implemented by a strong top-down approach. Recently, more flexible economic and market-based incentives (pricing, tradable permits, investments) have been successfully adopted, which are specifically tailored to the respective needs, shifting now away from the pure command and regulating instruments. One way towards a more holistic and integrated river basin management could be the establishment of a common platform (e.g. a Geographical Information System) for data handling and sharing, possibly operated by the Yellow River Basin Conservancy Commission (YRCC), where available spatial data, statistical information and in-situ measures are coalesced, on which sustainable decision-making could be based. So far, the collected data is hardly accessible, fragmented, inconsistent, or outdated. The first step to address the absence and lack of consistent and spatially up-to-date information for the entire basin capturing the heterogeneous landscape conditions was taken up in this thesis. Land cover characteristics and dynamics were derived from the last decade for the years 2003 and 2013, based on optical medium-resolution hightemporal MODIS Normalized Differenced Vegetation Index (NDVI) time series at 250 m. To minimize the inherent influence of atmospheric and geometric interferences found in raw high temporal data, the applied adaptive Savitzky-Golay filter successfully smoothed the time series and substantially reduced noise. Based on the smoothed time series data, a large variety of intra-annual phenology metrics as well as spectral and multispectral annual statistics were derived, which served as input variables for random forest (RF) classifiers. High quality reference data sets were derived from very high resolution imagery for each year independently of which 70 \% trained the RF models. The accuracy assessments for all regionally specific defined thematic classes were based on the remaining 30 \% reference data split and yielded overall accuracies of 87 \% and 84 \% for 2003 and 2013, respectively. The first regional adapted Yellow River Land Cover Products (YRB LC) depict the detail spatial extent and distribution of the current land cover status and dynamics. The novel products overall differentiate overall 18 land cover and use classes, including classes of natural vegetation (terrestrial and aquatic), cultivated classes, mosaic classes, non-vegetated, and artificial classes, which are not presented in previous land cover studies so far. Building on this, an extended multi-faceted land cover analysis on the most prominent land cover change types at finer spatial and temporal scales provides a better and more detailed picture of the Yellow River Basin dynamics. Precise spatio-temporal products about mining, agriculture, forest, and urban areas were examined from long-trem Landsat satellite time series monitored at annual scales to capture the rapid rate of change in four selected focus regions. All archived Landsat images between 2000 and 2015 were used to derive spatially continuous spectral-temporal, multi-spectral, and textural metrics. For each thematic region and year RF models were built, trained and tested based on a stablepixels reference data set. The automated adaptive signature (AASG) algorithm identifies those pixels that did not change between the investigated time periods to generate a mono-temporal reference stable-pixels data set to keep manual sampling requirements to a minimum level. Derived results gained high accuracies ranging from 88 \% to 98 \%. Throughout the basin, afforestation on the Central Loess Plateau and urban sprawl are identified as most prominent drivers of land cover change, whereas agricultural land remained stable, only showing local small-scale dynamics. Mining operations started in 2004 on the Qinghai-Tibet Plateau, which resulted in a substantial loss of pristine alpine meadows and wetlands. In this thesis, a novel and unique regional specific view of current and past land cover characteristics in a complex and heterogeneous landscape was presented by using a multi-source remote sensing approach. The delineated products hold great potential for various model and management applications. They could serve as valuable components for effective and sustainable land and water management to adapt and mitigate the predicted consequences of Global Change processes.},
  subject      = {Fernerkundung},
  language  = {en}
}
@phdthesis{Knauer2018,
  author    = {Knauer, Kim},
  title     = {Vegetation Dynamics in West Africa - Spatio-temporal Data Fusion for the Monitoring of Agricultural Expansion},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-164776},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2018},
  abstract  = {West Africa is one of the fastest growing regions in the world with annual population growth rates of more than three percent for several countries. Since the 1950s, West Africa experienced a fivefold increase of inhabitants, from 71 to 353 million people in 2015 and it is expected that the region's population will continue to grow to almost 800 million people by the year 2050. This strong trend has and will have serious consequences for food security since agricultural productivity is still on a comparatively low level in most countries of West Africa. In order to compensate for this low productivity, an expansion of agricultural areas is rapidly progressing. The mapping and monitoring of agricultural areas in West Africa is a difficult task even on the basis of remote sensing. The small scale extensive farming practices with a low level of agricultural inputs and mechanization make the delineation of cultivated land from other land cover and land use (LULC) types highly challenging. In addition, the frequent cloud coverage in the region considerably decreases the availability of earth observation datasets. For the accurate mapping of agricultural area in West Africa, high temporal as well as spatial resolution is necessary to delineate the small-sized fields and to obtain data from periods where different LULC types are distinguishable. However, such consistent time series are currently not available for West Africa. Thus, a spatio-temporal data fusion framework was developed in this thesis for the generation of high spatial and temporal resolution time series. Data fusion algorithms such as the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM) enjoyed increasing popularity during recent years but they have hardly been used for the application on larger scales. In order to make it applicable for this purpose and to increase the input data availability, especially in cloud-prone areas such as West Africa, the ESTARFM framework was developed in this thesis introducing several enhancements. An automatic filling of cloud gaps was included in the framework in order to use even partly cloud-covered Landsat images for the fusion without producing gaps on the output images. In addition, the ESTARFM algorithm was improved to automatically account for regional differences in the heterogeneity of the study region. Further improvements comprise the automation of the time series generation as well as the significant acceleration of the processing speed through parallelization. The performance of the developed ESTARFM framework was tested by fusing an 8-day NDVI time series from Landsat and MODIS data for a focus area of 98,000 km² in the border region between Burkina Faso and Ghana. The results of this test show the capability of the ESTARFM framework to accurately produce high temporal resolution time series while maintaining the spatial detail, even in such a heterogeneous and cloud-prone region. The successfully tested framework was subsequently applied to generate consistent time series as the basis for the mapping of agricultural area in Burkina Faso for the years 2001, 2007, and 2014. In a first step, high temporal (8-day) and high spatial (30 m) resolution NDVI time series for the entire country and the three years were derived with the ESTARFM framework. More than 500 Landsat scenes and 3000 MODIS scenes were automatically processed for this purpose. From the fused ESTARFM NDVI time series, phenological metrics were extracted and together with the single time steps of NDVI served as input for the delineation of rainfed agricultural areas, irrigated agricultural areas and plantations. The classification was conducted with the random forest algorithm at a 30 m spatial resolution for entire Burkina Faso and the three years 2001, 2007, and 2014. For the training and validation of the classifier, a randomly sampled reference dataset was generated from Google Earth images based on expert knowledge of the region. The overall classification accuracies of 92\% (2001), 91\% (2007), and 91\% (2014) indicate the well-functioning of the developed methodology. The resulting maps show an expansion of agricultural area of 91\% from about 61,000 km² in 2001 to 116,900 km² in 2014. While rainfed agricultural areas account for the major part of this increase, irrigated areas and plantations also spread considerably. Especially the expansion of irrigation systems and plantation area can be explained by the promotion through various national and international development projects. The increase of agricultural areas goes in line with the rapid population growth in most of Burkina Faso's provinces which still had available land resources for an expansion of agricultural area. An analysis of the development of agricultural areas in the vicinity of protected areas highlighted the increased human pressure on these reserves. The protection of the remnant habitats for flora and fauna while at the same time improving food security for a rapidly growing population, are the major challenges for the region in the future. The developed ESTARFM framework showed great potential beyond its utilization for the mapping of agricultural area. Other large-scale research that requires a sufficiently high temporal and spatial resolution such as the monitoring of land degradation or the investigation of land surface phenology could greatly benefit from the application of this framework.},
  subject      = {Fernerkundung},
  language  = {en}
}
@phdthesis{Knoefel2018,
  author    = {Kn{\"o}fel, Patrick},
  title     = {Energiebilanzmodellierung zur Ableitung der Evapotranspiration - Beispielregion Khorezm},
  edition   = {1. Auflage},
  publisher = {W{\"u}rzburg University Press},
  address   = {W{\"u}rzburg},
  isbn      = {978-3-95826-042-9 (Print)},
  issn      = {0510-9833},
  doi       = {10.25972/WUP-978-3-95826-043-6},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-135669},
  school      = {W{\"u}rzburg University Press},
  pages     = {276},
  year      = {2018},
  abstract  = {Zum Verst{\"a}ndnis der komplexen Wechselwirkungen innerhalb des Klimasystems der Erde sind Kenntnisse {\"u}ber den hydrologischen Zyklus und den Energiekreislauf essentiell. Eine besondere Rolle obliegt hierbei der Evapotranspiration (ET), da sie eine wesentliche Teilkomponente beider oben erw{\"a}hnter Kreisl{\"a}ufe ist. Die exakte Quantifizierung der regionalen, tats{\"a}chlichen Evapotranspiration innerhalb der Wasser- und Energiekreisl{\"a}ufe der Erdoberfl{\"a}che auf unterschiedlichen zeitlichen und r{\"a}umlichen Skalen ist f{\"u}r hydrologische, klimatologische und agronomische Fragestellungen von großer Bedeutung. Dabei ist eine realistische Absch{\"a}tzung der regionalen tats{\"a}chlichen Evapotranspiration die wichtigste Herausforderung der hydrologischen Modellierung. Besonders die unterschiedlichen r{\"a}umlichen und zeitlichen Aufl{\"o}sungen von Satelliteninformationen machen die Fernerkundung sowohl f{\"u}r globale als auch regionale hydrologischen Fragestellungen interessant. Zus{\"a}tzlich zur Notwendigkeit des Prozessverst{\"a}ndnisses des Wasserkreislaufs auf globaler Ebene kommt dessen regionale Bedeutung f{\"u}r die Landwirtschaft, insbesondere in Bew{\"a}sserungssystemen arider Regionen. In ariden Klimazonen {\"u}bersteigt die Menge der Verdunstung oft bei weitem die Niederschlagsmengen. Aufgrund der geringen Niederschlagsmenge muss in ariden agrarischen Regionen das zum Pflanzenwachstum ben{\"o}tigte Wasser mit Hilfe k{\"u}nstlicher Bew{\"a}sserung aufgebracht werden. Der jeweilige lokale Bew{\"a}sserungsbedarf h{\"a}ngt von der Feldfrucht und deren Wachstumsphase, den Klimabedingungen, den Bodeneigenschaften und der Ausdehnung der Wurzelzone ab. Die Evapotranspiration ist als Komponente der regionalen Wasserbilanz eine wichtige Steuerungsgr{\"o}ße und Effizienzindikator f{\"u}r das lokale Bew{\"a}sserungsmanagement. Die Bew{\"a}sse-rungslandwirtschaft verbraucht weltweit etwa 70 \% der verf{\"u}gbaren S{\"u}ßwasservorkom-men. Dies wird als einer der Hauptgr{\"u}nde f{\"u}r die weltweit steigende Wasserknappheit identifiziert. Dabei liegt die Wasserentnahme des landwirtschaftlichen Sektors in den OECD Staaten im Mittel bei etwa 44 \%, in den Staaten Mittelasiens bei {\"u}ber 90 \%. Bei der Erstellung der vorliegenden Arbeit kam die Methode der residualen Bestimmung der Energiebilanz zum Einsatz. Eines der weltweit am h{\"a}ufigsten eingesetzten und vali-dierten fernerkundlichen Residualmodelle zur ET Ableitung ist das SEBAL-Modell (Surface Energy Balance Algorithm for Land, mit {\"u}ber 40 ver{\"o}ffentlichten Studien. SEBAL eignet sich zur Quantifizierung der Verdunstung großfl{\"a}chiger Gebiete und wurde bisher {\"u}ber-wiegend in der Bew{\"a}sserungslandwirtschaft eingesetzt. Aus diesen Gr{\"u}nden wurde es f{\"u}r die Bearbeitung der Fragestellungen in dieser Arbeit ausgew{\"a}hlt. SEBAL verwendet physikalische und empirische Beziehungen zur Berechnung der Energiebilanzkomponenten basierend auf Fernerkundungsdaten, bei gleichzeitig minimalem Einsatz bodengest{\"u}tzter Daten. Als Eingangsdaten werden u.a. Informationen {\"u}ber Strahlung, Bodenoberfl{\"a}chentemperatur, NDVI, LAI und Albedo verwendet. Zus{\"a}tzlich zu SEBAL wurden einige Komponenten der SEBAL Weiterentwicklung METRIC (Mapping Evapotranspiration with Internalized Calibration) verwendet, um die Modellierung der ET vorzunehmen. METRIC {\"u}berwindet einige Limitierungen des SEBAL Verfahrens und kann beispielsweise auch in st{\"a}rker reliefierten Regionen angewendet werden. Außerdem erm{\"o}glicht die Integration einer gebietsspezifischen Referenz-ET sowie einer Landnutzungsklassifikation eine bessere regionale Anpassung des Residualverfahrens. Unter der Annahme der Bedingungen zum Zeitpunkt der Fernerkundungsaufnahme ergibt sich die Energiebilanz an der Erdoberfl{\"a}che RN = LvE + H + G. Demnach teilt sich die verf{\"u}gbare Strahlungsenergie RN in die Komponenten latenter W{\"a}rme (LVE), f{\"u}hlbarer W{\"a}rme (H) und Bodenw{\"a}rme (G) auf. Durch Umstellen der Gleichung kann auf die latente W{\"a}rme geschlossen werden. Das wesentliche Ziel der vorliegenden Arbeit ist die Optimierung, Erweiterung und Validierung des ausgew{\"a}hlten SEBAL Verfahrens zur regionalen Modellierung der Energiebilanzkomponenten und der daraus abgeleiteten tats{\"a}chlichen Evapotranspiration. Die validierten Modellergebnisse der Gebietsverdunstung der Jahre 2009-2011 sollen anschließend als Grundlage dienen, das Gesamtverst{\"a}ndnis der regionalen Prozesse des Wasserkreislaufs zu verbessern. Die Arbeit basiert auf der Datengrundlage von MODIS Daten mit 1 km r{\"a}umlicher Aufl{\"o}sung. W{\"a}hrend die Komponenten verf{\"u}gbare Strahlungsenergie und f{\"u}hlbarer W{\"a}rmestrom physikalisch basiert ermittelt werden, beruht die Berechnung des Bodenw{\"a}rmestroms ausschließlich auf empirischen Absch{\"a}tzungen. Ein großer Nachteil des empirischen Ansatzes ist die Vernachl{\"a}ssigung des zeitlichen Versatzes zwischen Strahlungsbilanz und Bodenw{\"a}rmestrom in Abh{\"a}ngigkeit der aktuellen Bodenfeuchtesituation. Ein besonderer Schwerpunkt der vorliegenden Arbeit liegt auf der Bewertung und Verbesserung der Modellg{\"u}te des Bodenw{\"a}rmestroms durch Verwendung eines neuen Ansatzes zur Integration von Bodenfeuchteinformationen. Daher wird in der Arbeit ein physikalischer Ansatz entwickelt der auf dem Ansatz der periodischen Temperaturver{\"a}nderung basiert. Hierbei wurde neben dem ENVISAT ASAR SSM Produkt der TU Wien das operationelle Oberfl{\"a}chenbodenfeuchteprodukt ASCAT SSM als Fernerkundungseingangsdaten ausgew{\"a}hlt. Die mit SEBAL modellierten Energiebilanzkomponenten werden durch eine intensive Validierung mit bodengest{\"u}tzten Messungen bewertet, die Messungen stammen von Bodensensoren und Daten einer Eddy-Kovarianz-Station aus den Jahren 2009 bis 2011. Die Region Khorezm gilt als charakteristisch f{\"u}r die wasserbezogene Problematik der Bew{\"a}sserungslandwirtschaft Mittelasiens und wurde als Untersuchungsgebiet f{\"u}r diese Arbeit ausgew{\"a}hlt. Die wesentlichen Probleme dieser Region entstehen durch die nach wie vor nicht nachhaltige Land- und Wassernutzung, das marode Bew{\"a}sserungsnetz mit einer Verlustrate von bis zu 40 \% und der Bodenversalzung aufgrund hoher Grundwasserspiegel. Im Untersuchungsgebiet wurden in den Jahren 2010 und 2011 umfangreiche Feldarbeiten zur Erhebung lokaler bodengest{\"u}tzter Informationen durchgef{\"u}hrt. Bei der Evaluierung der modellierten Einzelkomponenten ergab sich f{\"u}r die Strahlungsbi-lanz eine hohe Modellg{\"u}te (R² > 0,9; rRMSE < 0,2 und NSE > 0,5). Diese Komponente bildet die Grundlage bei der Bezifferung der f{\"u}r die Prozesse an der Erdoberfl{\"a}che zur Verf{\"u}gung stehenden Energie. F{\"u}r die f{\"u}hlbaren W{\"a}rmestr{\"o}me wurden ebenfalls gute Ergebnisse erzielt, mit NSE von 0,31 und rRMSE von ca. 0,21. F{\"u}r die residual bestimmte Gr{\"o}ße der latenten W{\"a}rmestr{\"o}mung konnte eine insgesamt gute Modellg{\"u}te festgestellt werden (R² > 0,6; rRMSE < 0,2 und NSE > 0,5). Dementsprechend gut wurde die t{\"a}gliche Evapotranspiration modelliert. Hier ergab sich, nach der Interpolation t{\"a}glicher Werte, eine insgesamt ausreichend gute Modellg{\"u}te (R² > 0,5; rRMSE < 0,2 und NSE > 0,4). Dies best{\"a}tigt die Ergebnisse vieler Energiebilanzstudien, die lediglich den f{\"u}r die Ableitung der Evapotranspiration maßgebenden W{\"a}rmestrom untersuchten. Die Modellergebnisse f{\"u}r den Bodenw{\"a}rmestrom konnten durch die Entwicklung und Verwendung des neu entwickelten physikalischen Ansatzes von NSE < 0 und rRMSE von ca. 0,57 auf NSE von 0,19 und rRMSE von 0,35 verbessert werden. Dies f{\"u}hrt zu einer insgesamt positiven Einsch{\"a}tzung des Verbesserungspotenzials des neu entwickelten Bodenw{\"a}rmestromansatzes bei der Berechnung der Energiebilanz mit Hilfe von Fernerkundung.},
  subject      = {Evapotranspiration},
  language  = {de}
}
@article{LauschBorgBumbergeretal.2018,
  author    = {Lausch, Angela and Borg, Erik and Bumberger, Jan and Dietrich, Peter and Heurich, Marco and Huth, Andreas and Jung, Andr{\´a}s and Klenke, Reinhard and Knapp, Sonja and Mollenhauer, Hannes and Paasche, Hendrik and Paulheim, Heiko and Pause, Marion and Schweitzer, Christian and Schmulius, Christiane and Settele, Josef and Skidmore, Andrew K. and Wegmann, Martin and Zacharias, Steffen and Kirsten, Toralf and Schaepman, Michael E.},
  title     = {Understanding forest health with remote sensing, part III: requirements for a scalable multi-source forest health monitoring network based on data science approaches},
  series = {Remote Sensing},
  volume    = {10},
  journal   = {Remote Sensing},
  number    = {7},
  issn      = {2072-4292},
  doi       = {10.3390/rs10071120},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-197691},
  pages     = {1120},
  year      = {2018},
  abstract  = {Forest ecosystems fulfill a whole host of ecosystem functions that are essential for life on our planet. However, an unprecedented level of anthropogenic influences is reducing the resilience and stability of our forest ecosystems as well as their ecosystem functions. The relationships between drivers, stress, and ecosystem functions in forest ecosystems are complex, multi-faceted, and often non-linear, and yet forest managers, decision makers, and politicians need to be able to make rapid decisions that are data-driven and based on short and long-term monitoring information, complex modeling, and analysis approaches. A huge number of long-standing and standardized forest health inventory approaches already exist, and are increasingly integrating remote-sensing based monitoring approaches. Unfortunately, these approaches in monitoring, data storage, analysis, prognosis, and assessment still do not satisfy the future requirements of information and digital knowledge processing of the 21st century. Therefore, this paper discusses and presents in detail five sets of requirements, including their relevance, necessity, and the possible solutions that would be necessary for establishing a feasible multi-source forest health monitoring network for the 21st century. Namely, these requirements are: (1) understanding the effects of multiple stressors on forest health; (2) using remote sensing (RS) approaches to monitor forest health; (3) coupling different monitoring approaches; (4) using data science as a bridge between complex and multidimensional big forest health (FH) data; and (5) a future multi-source forest health monitoring network. It became apparent that no existing monitoring approach, technique, model, or platform is sufficient on its own to monitor, model, forecast, or assess forest health and its resilience. In order to advance the development of a multi-source forest health monitoring network, we argue that in order to gain a better understanding of forest health in our complex world, it would be conducive to implement the concepts of data science with the components: (i) digitalization; (ii) standardization with metadata management after the FAIR (Findability, Accessibility, Interoperability, and Reusability) principles; (iii) Semantic Web; (iv) proof, trust, and uncertainties; (v) tools for data science analysis; and (vi) easy tools for scientists, data managers, and stakeholders for decision-making support.},
  language  = {en}
}
@article{NyamekyeThielSchoenbrodtStittetal.2018,
  author    = {Nyamekye, Clement and Thiel, Michael and Sch{\"o}nbrodt-Stitt, Sarah and Zoungrana, Benewinde J.-B. and Amekudzi, Leonard K.},
  title     = {Soil and water conservation in Burkina Faso, West Africa},
  series = {Sustainability},
  volume    = {10},
  journal   = {Sustainability},
  number    = {9},
  issn      = {2071-1050},
  doi       = {10.3390/su10093182},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-197653},
  pages     = {3182},
  year      = {2018},
  abstract  = {Inadequate land management and agricultural activities have largely resulted in land degradation in Burkina Faso. The nationwide governmental and institutional driven implementation and adoption of soil and water conservation measures (SWCM) since the early 1960s, however, is expected to successively slow down the degradation process and to increase the agricultural output. Even though relevant measures have been taken, only a few studies have been conducted to quantify their effect, for instance, on soil erosion and environmental restoration. In addition, a comprehensive summary of initiatives, implementation strategies, and eventually region-specific requirements for adopting different SWCM is missing. The present study therefore aims to review the different SWCM in Burkina Faso and implementation programs, as well as to provide information on their effects on environmental restoration and agricultural productivity. This was achieved by considering over 143 studies focusing on Burkina Faso's experience and research progress in areas of SWCM and soil erosion. SWCM in Burkina Faso have largely resulted in an increase in agricultural productivity and improvement in food security. Finally, this study aims at supporting the country's informed decision-making for extending already existing SWCM and for deriving further implementation strategies.},
  language  = {en}
}
@article{QamarAzmatAbbasetal.2018,
  author    = {Qamar, Muhammad Uzair and Azmat, Muhammad and Abbas, Azhar and Usman, Muhammad and Shahid, Muhammad Adnan and Khan, Zahid Mahmood},
  title     = {Water Pricing and Implementation Strategies for the Sustainability of an Irrigation System: A Case Study within the Command Area of the Rakh Branch Canal},
  series = {Water},
  volume    = {10},
  journal   = {Water},
  number    = {4, 509},
  doi       = {10.3390/w10040509},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-224711},
  pages     = {1-24},
  year      = {2018},
  abstract  = {The command area of the Rakh branch canal grows wheat, sugarcane, and rice crops in abundance. The canal water, which is trivial for irrigating these crops, is conveyed to the farms through the network of canals and distributaries. For the maintenance of this vast infrastructure; the end users are charged on a seasonal basis. The present water charges are severely criticized for not being adequate to properly manage the entire infrastructure. We use the residual value to determine the value of the irrigation water and then based on the quantity of irrigation water supplied to farm land coupled with the infrastructure maintenance cost, full cost recovery figures are executed for the study area, and policy recommendations are made for the implementation of the full cost recovery system. The approach is unique in the sense that the pricings are based on the actual quantity of water conveyed to the field for irrigating crops. The results of our analysis showed that the canal water is severely under charged in the culturable command area of selected distributaries, thus negating the plan of having a self-sustainable irrigation system.},
  language  = {en}
}
@article{HaggMayrMannigetal.2018,
  author    = {Hagg, Wilfried and Mayr, Elisabeth and Mannig, Birgit and Reyers, Mark and Schubert, David and Pinto, Joaquim G. and Peters, Juliane and Pieczonka, Tino and Juen, Martin and Bolch, Tobias and Paeth, Heiko and Mayer, Christoph},
  title     = {Future climate change and its impact on runoff generation from the debris-covered Inylchek glaciers, Central Tian Shan, Kyrgyzstan},
  series = {Water},
  volume    = {10},
  journal   = {Water},
  number    = {11},
  issn      = {2073-4441},
  doi       = {10.3390/w10111513},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-197592},
  pages     = {1513},
  year      = {2018},
  abstract  = {The heavily debris-covered Inylchek glaciers in the central Tian Shan are the largest glacier system in the Tarim catchment. It is assumed that almost 50\% of the discharge of Tarim River are provided by glaciers. For this reason, climatic changes, and thus changes in glacier mass balance and glacier discharge are of high impact for the whole region. In this study, a conceptual hydrological model able to incorporate discharge from debris-covered glacier areas is presented. To simulate glacier melt and subsequent runoff in the past (1970/1971-1999/2000) and future (2070/2071-2099/2100), meteorological input data were generated based on ECHAM5/MPI-OM1 global climate model projections. The hydrological model HBV-LMU was calibrated by an automatic calibration algorithm using runoff and snow cover information as objective functions. Manual fine-tuning was performed to avoid unrealistic results for glacier mass balance. The simulations show that annual runoff sums will increase significantly under future climate conditions. A sensitivity analysis revealed that total runoff does not decrease until the glacier area is reduced by 43\%. Ice melt is the major runoff source in the recent past, and its contribution will even increase in the coming decades. Seasonal changes reveal a trend towards enhanced melt in spring, but a change from a glacial-nival to a nival-pluvial runoff regime will not be reached until the end of this century.},
  language  = {en}
}
@phdthesis{Krech2018,
  author    = {Krech, Martin},
  title     = {Pedosediment{\"a}re Archive in pr{\"a}historischen Fundpl{\"a}tzen in Franken},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-163682},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2018},
  abstract  = {Pedosediment{\"a}re Archive liefern einen wichtigen Beitrag zur Rekonstruktion der Landschaftsgeschichte. Die anthropogene Besiedlung und Nutzung der Landoberfl{\"a}che seit dem Beginn des Holoz{\"a}ns verursacht Boden-, Vegetations- und Reliefver{\"a}nderungen, welche sich durch die Verbreitung von B{\"o}den mit ihren Erosionsstadien und Kolluvien zeigen. Das Ausmaß und die Art der Bodenerosion und die damit verbundene Bildung der Kolluvien werden neben den nat{\"u}rlichen Faktoren wesentlich durch die Landnutzung bestimmt. B{\"o}den und Kolluvien enthalten wichtige Informationen {\"u}ber die urspr{\"u}ngliche Landschaft, ehemalige Landnutzungsphasen und Umweltver{\"a}nderungen. Die spezifischen Merkmale in Kombination mit den arch{\"a}ologischen Befunden erm{\"o}glichen R{\"u}ckschl{\"u}sse auf vergangene Natur- und Kulturr{\"a}ume. Das Ziel der vorliegenden Arbeit ist es, ein besseres Verst{\"a}ndnis {\"u}ber die Siedlungs- und Landschaftsentwicklung der untersuchten Gebiete in Franken zu erlangen. Hierf{\"u}r ist es angebracht, mehrere r{\"a}umlich verteilte Standorte zu untersuchen. Um den menschlichen Einfluss auf die pr{\"a}historische Landschaft besser verstehen zu k{\"o}nnen, kam ein interdisziplin{\"a}rer Ansatz mit arch{\"a}ologischen und physisch-geographischen Methoden zur Anwendung. Die Umgebungen der einzelnen Untersuchungsstandorte wurden nach geomorphologischen Kriterien charakterisiert und ausgew{\"a}hlten Befunde nach bodenkundlichen Fragestellungen aufgenommen. Die Bestimmung der bodenphysikalischen und -chemischen Eigenschaften von B{\"o}den und Sedimenten erfolgte anhand repr{\"a}sentativer Probenmengen. Bei ausgew{\"a}hlten Profilen kamen zus{\"a}tzlich die Analysen zur Bestimmung der Gesamt- und Tonmineralogie sowie die Methode der 14C-Datierung f{\"u}r Bodensedimente, Tierknochen und Holzkohlen hinzu. Die physisch-geographischen Ergebnisse konnten anschließend mit den arch{\"a}ologischen Informationen erg{\"a}nzt. Die drei ausgew{\"a}hlten Untersuchungsgebiete befinden sich im Fr{\"a}nkischen Schichtstufenland. Der Bullenheimer Berg wurde aufgrund seiner bedeutenden Besiedlungsgeschichte ausgew{\"a}hlt. Die ausgew{\"a}hlten Profile liegen in verschiedenen Nutzungsarealen auf dem Plateau. Die Standorte Marktbergel und Ergersheim liegen im Gebiet des Fr{\"a}nkischen Gipskarstes. Diese Untersuchungen sind ein Teil des DFG-gef{\"o}rderten Projektes „Pr{\"a}historische Mensch-Umwelt-Beziehungen im Gipskarst der Windsheimer Bucht, Nordbayern. Dolinen als Archive f{\"u}r Siedlungs- und Landschaftsentwicklung." Die vorliegenden Ergebnisse zeigen, dass der anthropogene Einfluss zu einer deutlichen Ver{\"a}nderung in der Landschaft f{\"u}hrte. F{\"u}r die Untersuchungsr{\"a}ume zeichnet sich eine lange Nutzungsgeschichte seit dem Beginn des Holoz{\"a}ns ab. Durch die Auswertung der Gel{\"a}ndebefunde und der labortechnisch erzeugten Kennwerte konnten die untersuchten Profile in mehrere Phasen gegliedert werden. Es zeigten sich Stabilit{\"a}tsphasen in denen Bodenbildung stattfinden konnte, aber auch geomorphodynamisch aktive Phasen der Erosion und Akkumulation von Bodensedimenten.},
  subject      = {Pedostratigraphie},
  language  = {de}
}
@article{ReichmuthHenningPinneletal.2018,
  author    = {Reichmuth, Anne and Henning, Lea and Pinnel, Nicole and Bachmann, Martin and Rogge, Derek},
  title     = {Early detection of vitality changes of multi-temporal Norway spruce laboratory needle measurements—the ring-barking experiment},
  series = {Remote Sensing},
  volume    = {10},
  journal   = {Remote Sensing},
  number    = {1},
  doi       = {10.3390/rs10010057},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-159253},
  pages     = {57},
  year      = {2018},
  abstract  = {The focus of this analysis is on the early detection of forest health changes, specifically that of Norway spruce (Picea abies L. Karst.). In this analysis, we planned to examine the time (degree of early detection), spectral wavelengths and appropriate method for detecting vitality changes. To accomplish this, a ring-barking experiment with seven subsequent laboratory needle measurements was carried out in 2013 and 2014 in an area in southeastern Germany near Alt{\"o}tting. The experiment was also accompanied by visual crown condition assessment. In total, 140 spruce trees in groups of five were ring-barked with the same number of control trees in groups of five that were selected as reference trees in order to compare their development. The laboratory measurements were analysed regarding the separability of ring-barked and control samples using spectral reflectance, vegetation indices and derivative analysis. Subsequently, a random forest classifier for determining important spectral wavelength regions was applied. Results from the methods are consistent and showed a high importance of the visible (VIS) spectral region, very low importance of the near-infrared (NIR) and minor importance of the shortwave infrared (SWIR) spectral region. Using spectral reflectance data as well as indices, the earliest separation time was found to be 292 days after ring-barking. The derivative analysis showed that a significant separation was observed 152 days after ring-barking for six spectral features spread through VIS and SWIR. A significant separation was detected using a random forest classifier 292 days after ring-barking with 58\% separability. The visual crown condition assessment was analysed regarding obvious changes of vitality and the first indication was observed 302 days after ring-barking as bark beetle infestation and yellowing of foliage in the ring-barked trees only. This experiment shows that an early detection, compared with visual crown assessment, is possible using the proposed methods for this specific data set. This study will contribute to ongoing research for early detection of vitality changes that will support foresters and decision makers.},
  language  = {en}
}