Potential and Limitations of Open Satellite Data for Flood Mapping

Satellite remote sensing is a powerful tool to map flooded areas. In recent years, the availability of free satellite data significantly increased in terms of type and frequency, allowing the production of flood maps at low cost around the world. In this work, we propose a semi-automatic method for flood mapping, based only on free satellite images and open-source software. The proposed methods are suitable to be applied by the community involved in flood hazard management, not necessarily experts in remote sensing processing. As case studies, we selected three flood events that recently occurred in Spain and Italy. Multispectral satellite data acquired by MODIS, Proba-V, Landsat, and Sentinel-2 and synthetic aperture radar (SAR) data collected by Sentinel-1 were used to detect flooded areas using different methodologies (e.g., Modified Normalized Difference Water Index, SAR backscattering variation, and supervised classification). Then, we improved and manually refined the automatic mapping using free ancillary data such as the digital elevation model-based water depth model and available ground truth data. We calculated flood detection performance (flood ratio) for the different datasets by comparing with flood maps made by official river authorities. The results show that it is necessary to consider different factors when selecting the best satellite data. Among these factors, the time of the satellite pass with respect to the flood peak is the most important. With co-flood multispectral images, more than 90% of the flooded area was detected in the 2015 Ebro flood (Spain) case study. With post-flood multispectral data, the flood ratio showed values under 50% a few weeks after the 2016 flood in Po and Tanaro plains (Italy), but it remained useful to map the inundated pattern. The SAR could detect flooding only at the co-flood stage, and the flood ratio showed values below 5% only a few days after the 2016 Po River inundation. Another result of the research was the creation of geomorphology-based inundation maps that matched up to 95% with official flood maps

Mapping of Mature and Young Oil Palm Distributions in a Humid Tropical River Basin for Flood Vulnerability Assessment

International Conference on the Ocean and Earth Sciences 18-20 November 2020, Jakarta Selatan, IndonesiaOil palm is one of the key drivers of economic growth in some regions in the humid tropical countries such as Indonesia. Previous studies show that floods risk at particular river basins in Indonesia will increase in the future due to climate change. This will give negative impacts to the sustainable production of palm oil in the future and subsequently the regions' economy. Discussion on adaptation strategies on this matter is necessary however, the vulnerability of oil palm plantations against floods at river basin scale are still poorly understood. Field surveys for oil palms' vulnerability at such scale is costly in time, labour and resources, and making use of remote sensing is more feasible. The aim of this study is to use remote sensing in assessing oil palm vulnerability against floods at river basin scale. To achieve this objective two oil palm distribution maps which were developed using Sentinel imageries for years 2015 and 2018 allowing young oil palms to be matured under normal condition. To understand the impact of floods to oil palms, a composite of flood extents using radar scenes for years 2016 and 2017 was developed. Our results show that young oil palms are highly vulnerable to floods compared to matured ones. Only 6% of the earlier could survived floods and be matured in time, while most of the matured ones could survive

Analysis of Land Use Land Cover Changes Using Remote Sensing Data and Geographical Information Systems (GIS) at an Urban Set up of Damaturu, Nigeria

Change detection is useful in many applications related to land use and land cover change (LULCC), such as shifting cultivation and landscape changes. Land degradation and desertification. Remote sensing technology has been used for the detection of the changes in land use land cover in Damaturu town Nigeria. The main objectives of this research was to derive the land use/cover change map of Damaturu town from 1986 to 2017 and to quantify land use/ land cover change in the study area. Methodology employed while carry the research includes three satellites images for the year 1986, 1998 and 2017 were downloaded from USGS websites and used for detecting the land cover changes. Ground truth points were collected using google images and used for verification of image classifications. The accuracy of images classification was checked using ground truth point which showed the overall accuracy of 84.6% and a kappa coefficient of 0.89 which indicated that the method of classification was accurate. In the process of the research work, an increased was recorded in the built-up area which rose from 7.2% to 22.0%, open space increased from 10.8 to 22.8%, vegetation from 4.0% to 9.7%, water bodies from 0.0% to 0.1% while agricultural land decreased from 78% to 45.4% due to increase in interest of building as a result of the expansion of the town. The study arrived at the conclusion that there has been a significant land use change due to increase in population and development interest in built up areas which resulted in increased of amount of agricultural land being converted to build up areas over the period of 31 years.&nbsp

Google earth engine as multi-sensor open-source tool for supporting the preservation of archaeological areas: The case study of flood and fire mapping in metaponto, italy

In recent years, the impact of Climate change, anthropogenic and natural hazards (such as earthquakes, landslides, floods, tsunamis, fires) has dramatically increased and adversely affected modern and past human buildings including outstanding cultural properties and UNESCO heritage sites. Research about protection/monitoring of cultural heritage is crucial to preserve our cultural properties and (with them also) our history and identity. This paper is focused on the use of the open-source Google Earth Engine tool herein used to analyze flood and fire events which affected the area of Metaponto (southern Italy), near the homonymous Greek-Roman archaeological site. The use of the Google Earth Engine has allowed the supervised and unsupervised classification of areas affected by flooding (2013–2020) and fire (2017) in the past years, obtaining remarkable results and useful information for setting up strategies to mitigate damage and support the preservation of areas and landscape rich in cultural and natural heritage

Assessment of Pluvial Flooding in Syracuse, Ny, Using High-resolution Topographic Data

Although there have been many advances in regulations to assess flood risk in urban environments, the majority of these investigations to date have focused on fluvial or coastal flooding. However, in urban systems, pluvial flooding continues to be a pressing issue in need of attention. Due to the limited research on pluvial flooding in Syracuse, NY, its population and assets are exposed to the risks imposed by this type of flooding, as their primary metric for delineating flood risk is the traditional riverine flood zones designated by the Federal Emergency Management Agency (FEMA). To address this issue, this research implemented an existing 1D rainfall-runoff model to screen for pluvial flooding risk in Syracuse using a 1 m resolution DEM with simulations generated for a 100-year 1-hour storm size. The analysis was executed for five different boundaries, including the City of Syracuse municipal boundary and four watersheds that terminate within the city. To ascertain the accuracy of the approach, I compared model predictions of flood locations – called blue spots – to locations of flooding from news reports of large storms (n = 16) as well as areas of reported street flooding from a municipal database (n = 65). While 87.5% of locations obtained from news reports corresponded with the blue spots with various depths, only about a third of municipal database reports matched the blue spots. Across all boundaries, I compared blue spot depths within five depth categories (from nuisance to very high risk) to high resolution land cover and with the FEMA floodplain. I found that the majority of blue spots, including the deepest areas, were located in pervious areas, which may be related to some limitations and assumptions of the approach. However, some areas predicted to flood using the blue spot method were within critical areas, such as roads, commercial and residential areas. Information about these critical areas may be useful for providing mitigation and adaptation strategies (e.g., frequently maintenance of the drainage systems; locations where investments are needed to improve the drainage networks). Finally, I found that most blue spots indicative of areas at risk from pluvial flooding were concentrated outside of the FEMA floodplain. Overall, my study emphasizes the need to analyze different types of flooding together to improve flood risk assessment in urban environments

General overview of hydrological data with emphasis in extreme hydrological events

O conhecimento depende da existência de dados. A hidrologia moderna tem sido, prioritariamente, pautada em dados quantitativos provenientes das estações de monitoramento. No entanto, outras fontes podem fornecer dados relevantes ao avanço da hidrologia como demonstrado por pesquisadores desde a década de 1970. O panorama geral sobre o assunto evidencia a falta de padronização das terminologias dos tipos de dados e de fontes, podendo conduzir a equívocos. Além disso, ainda não existe consenso sobre o uso de dados provenientes de outras fontes, além das estações de monitoramento. Neste contexto, o presente estudo sugere a padronização nas denominações dos dados, bem como em suas fontes. Para isso, levou-se em consideração as características do registro, classificando-os em: dados sistemáticos e dados não sistemáticos. Os dados sistemáticos são dados quantitativos, mensurados continuamente ao longo do tempo com intervalo temporal pré-definido em um determinado local, enquanto os dados não sistemáticos são provenientes de uma grande variedade de outras fontes de dados que se caracterizam, principalmente, por registros cuja posição e intervalo temporal são variáveis. Quanto às fontes dos dados, sugere-se a classificação de acordo com a sua origem: evidência instrumental evidência natural e evidência documental. Considerando a relevância dos dados não sistemáticos, principalmente ao que tange eventos hidrológicos extremos, sugere-se o uso integrado de dados sistemáticos e não sistemáticos aplicando o método de triangulação de dados.Knowledge depends on the existence of data. Modern hydrology has been primarily based on quantitative data from gauging stations. However, other sources may provide data relevant to hydrology progress as demonstrated by researchers since the 1970s. The general picture on the subject highlights the lack of standard terminologies for data types and sources, which can lead to misunderstandings. Besides, there is still no consensus on the use of data from sources other than monitoring stations. In this context, in the present study, we suggested standard denomination for data and their sources. We classified from the recorded characteristics as systematic data and nonsystematic data. Systematic data are quantitative data, measured continuously over time with a pre-defined time interval at a given position, while non-systematic data are from a wide variety of other data sources, whose position and time interval of data are variable. We also classified the data sources according to the origin: instrumental evidence, natural evidence, and documentary evidence. Considering the relevance of non-systematic data, mainly concerning extreme hydrological events, we suggested the use of both data – systematic and non-systematic - applying the data triangulation method

A taxonomy of earth observation data for sustainable finance

Corporate Environmental, Social and Governance (ESG) reporting has been subject to heightened attention and demand within the financial sector, with the objective of efficiently directing capital towards firms engaging in sustainable practices. Effective ESG monitoring is challenging, given the prevalence of self-disclosed internal data and managerial signalling incentives, presenting a need for comprehensive and diverse external data sources to augment existing ESG-related disclosure. Earth Observation (EO) technologies – particularly satellite data – play a crucial role in collecting spatial data on land, water, and atmosphere, making them highly useful for facilitating transition in the sector. This paper aims to outline the various ways in which EO data can be applied for the purposes of (i) future academic research in the subject area of sustainable finance and (ii) detailed ESG reporting and monitoring by practitioners. Using the ESG Key Performance Indicator (KPI) framework established by the European Commission and EFFAS, we present a framework listing all applicable KPIs against the types of satellite imagery that can be utilised in each case. Additionally, for ESG KPIs that EO data cannot directly address, we compile an ancillary list to explore potential indirect applications. To underscore the wealth of available EO data sources that can be used for sustainable finance research, we present a comprehensive catalogue of all open-access and relevant private satellite missions. Listed missions are categorised based on their spatial resolution, temporal resolution, and mission duration, facilitating research with specific requirements for these parameters

Novel Satellite-Based Methodologies for Multi-Sensor and Multi-Scale Environmental Monitoring to Preserve Natural Capital

Global warming, as the biggest manifestation of climate change, has changed the distribution of water in the hydrological cycle by increasing the evapotranspiration rate resulting in anthropogenic and natural hazards adversely affecting modern and past human properties and heritage in different parts of the world. The comprehension of environmental issues is critical for ensuring our existence on Earth and environmental sustainability. Environmental modeling can be described as a simplified form of a real system that enhances our knowledge of how a system operates. Such models represent the functioning of various processes of the environment, such as processes related to the atmosphere, hydrology, land surface, and vegetation. The environmental models can be applied on a wide range of spatiotemporal scales (i.e. from local to global and from daily to decadal levels); and they can employ various types of models (e.g. process-driven, empirical or data-driven, deterministic, stochastic, etc.). Satellite remote sensing and Earth Observation techniques can be utilized as a powerful tool for flood mapping and monitoring. By increasing the number of satellites orbiting around the Earth, the spatial and temporal coverage of environmental phenomenon on the planet has in-creased. However, handling such a massive amount of data was a challenge for researchers in terms of data curation and pre-processing as well as required computational power. The advent of cloud computing platforms has eliminated such steps and created a great opportunity for rapid response to environmental crises. The purpose of this study was to gather state-of-the-art remote sensing and/or earth observation techniques and to further the knowledge concerned with any aspect of the use of remote sensing and/or big data in the field of geospatial analysis. In order to achieve the goals of this study, some of the water-related climate-change phenomena were studied via different mathematical, statistical, geomorphological and physical models using different satellite and in-situ data on different centralized and decentralized computational platforms. The structure of this study was divided into three chapters with their own materials, methodologies and results including: (1) flood monitoring; (2) soil water balance modeling; and (3) vegetation monitoring. The results of this part of the study can be summarize in: 1) presenting innovative procedures for fast and semi-automatic flood mapping and monitoring based on geomorphic methods, change detection techniques and remote sensing data; 2) modeling soil moisture and water balance components in the root zone layer using in-situ, drone and satellite data; incorporating downscaling techniques; 3) combining statistical methods with the remote sensing data for detecting inner anomalies in the vegetation covers such as pest emergence; 4) stablishing and disseminating the use of cloud computation platforms such as Google Earth Engine in order to eliminate the unnecessary steps for data curation and pre-processing as well as required computational power to handle the massive amount of RS data. As a conclusion, this study resulted in provision of useful information and methodologies for setting up strategies to mitigate damage and support the preservation of areas and landscape rich in cultural and natural heritage

A collaborative approach for disaster risk reduction: mapping social learning with Mistawasis Nêhiyawak

Social learning and its relation to disaster risk reduction (DRR) have been increasingly highlighted in the literature. Yet, limited empirical research has hampered practical DRR applications. This thesis demonstrated social learning loops and their outcomes by reflecting on the case of 2011 flooding in Mistawasis Nêhiyawak. Using a mixed-methods research design, I explored the role of participatory processes, including communication of scientific knowledge to lay-experts, in social learning. First, I created flood extent maps for the community using spatial data and modeling techniques. In the second phase, I presented the maps in a workshop held at the community center to understand their value in regard to what people learn from them. This included deliberating not only about physical parameters of the flood but also exploring the social (and human) parameters. Hence, I used fuzzy cognitive mapping (FCM) as a novel method to represent the human perception of flood risk and to measure social learning. In the workshop, FCM was complemented by focus group discussions and participatory mapping. From the results, it was found that i) social learning can be measured using social sciences tools, ii) sharing experiences and stories from past events augmented learning, and iii) awareness on the role of emergency planning in DRR was found to be a significant outcome of social learning. In the growing urgency of climate uncertainties, social learning theory will be critical in helping design practical and ethical research approaches to DRR that emphasize knowledge sharing, two-way communication, and reflexivity. These will ultimately have enhanced emphasis on behavioral responses to disasters that are complementary to the investments in structural responses

Impact of tropical rainforest transformation in Indonesia on soil carbon sources, turnover and losses

Die landwirtschaftliche Erweiterung gilt weltweit als einer der wichtigsten Treiber für die Abholzung von Wäldern. Die weltweit steigende Nachfrage nach Agrarprodukten wie Palmöl und Kautschuk führte in den letzten Jahrzehnten, insbesondere in Südostasien zu einer rasanten Ausweitung der Landwirtschaft. Es wird erwartet, dass die Umwandlung von tropischem Regenwald in monokulturelle Plantagen zu schwerwiegenden Veränderungen im biogeochemischen Kreislauf und in der Funktionsweise von Ökosystemen führen wird. Dieser Landnutzungswandel hat große Auswirkungen auf den globalen Kohlenstoffkreislauf, da er den Vorrat an organischem Bodenkohlenstoff (engl. SOC) verringert und die Kohlenstoffdioxidemissionen (CO2) erhöht. Darüber hinaus begünstigt die steigende Nachfrage nach Agrarprodukten die fortschreitende Umwandlung von weniger gut zugänglichen Landschaftstypen in landwirtschaftliche Flächen, wie z. B. Flussufergebieten. Uferbereiche reagieren besonders empfindlich auf Landnutzungsänderungen, da sie meist einen höheren SOC-Gehalt aufweisen als mineralisch terrestrische Böden und Lebensraum für eine Vielzahl von Tier- und Pflanzenarten sind. Es ist daher entscheidend die Veränderungen des SOC-Pools und der SOC-Flüsse unter den aktuellen Landnutzungsveränderungen zu verstehen, um die Auswirkungen auf den Kohlenstoffkreislauf im Boden zu beurteilen. Ziel dieses Forschungsprojekts war es daher, Veränderungen der SOC-Quellen, d.h. SOM-Zusammensetzung, die SOC Umsätze und die SOC Verluste nach der Umwandlung von Wald in Kautschuk- und Ölpalm-Monokulturen zu identifizieren. Die Studie wurde in Sumatra (Indonesien) durchgeführt, welches ein Hotspot des Regenwaldverlusts aufgrund der landwirtschaftlichen Erweiterung ist. Das erste Ziel war es, die physikalischen und chemischen Veränderungen, insbesondere die Veränderungen des SOC-Bestandes von Uferböden nach einer Landnutzungsänderung zu bestimmen und sie mit den Veränderungen in mineralisch terrestrischen Böden zu vergleichen. Das zweite Ziel war es, den Beitrag der vergangenen Vegetation zum aktuellen SOC-Pool in Wald- und Plantagenböden zu ermitteln und herauszufinden, ob es eine Veränderung der SOM-Zusammensetzung gibt, die auf Unterschiede in den SOM-Quellen zwischen den Landnutzungssystemen hinweist. Im Hinblick auf dringend benötigte Lösungen zur Anpassung an den Klimawandel, die Bodenfruchtbarkeit zu erhalten und der Tatsache, dass die Auswirkungen intensiver Stickstoff (N)-Düngung und Herbizideinsatz auf den Bodenkohlenstoffkreislauf in diesen Monokulturen unbekannt sind, war es das Ziel, die Auswirkungen landwirtschaftlicher Bewirtschaftungsstrategien auf den SOC-Abbau und die SOC Einlagerung in Ölpalmenplantagen zu bestimmen. Hier wurde eine Plantage mit mineralisch terrestrischem Boden ausgewählt, da eine größere Allgemeingültigkeit aus den Ergebnissen abgeleitet werden kann, da sich die Mehrheit des Palmölanbaus auf mineralisch terrestrischen Böden stattfindet. Für das Erreichen des ersten Forschungsziels wurden SOC-Vorräte und δ13C-Werte bestimmt, um die Veränderung der Kohlenstoffvorräte und den SOC-Abbau an vier Uferwald-, vier Kautschuk- und vier Ölpalmenplantagenstandorten zu bewerten und mit der gleichen Anzahl von mineralisch terrestrischen Standorten zu vergleichen. Die durchschnittlichen Verluste des Kohlenstoffvorrats in den obersten 30 cm des Bodens betrugen 14% bzw. 4% nach der Umwandlung von Auwäldern in Kautschuk- und Ölpalmenplantagen, was auf eine hohe Resistenz des Kohlenstoffs (C) gegenüber der Mineralisierung hinweist. Kohlenstoffverluste aus mineralisch terrestrischen Böden waren nach dem Landnutzungswandel doppelt so hoch wie aus Uferbereichen. δ13C-Werte aus Uferbereichen zeigten eine starke Heterogenität innerhalb des Bodenprofils im Vergleich zu mineralisch terrestrischen Profilen, was auf unterschiedliche Grade der Zersetzung von SOM hinweist. Mineralisch terrestrische Bodenprofile zeigten das erwartete Muster mit niedrigeren Werten (- 29‰) im Oberboden und einer Anpassung an höhere Werte (-26‰) im Unterboden, was darauf hinweist, dass SOC im Oberboden intensiver abgebaut wurde als im Unterboden. In Kombination mit der Auswertung des Grundwasserspiegels (GWT) schlossen wir erstens auf wechselnde oxische und anoxische Bedingungen in Uferbereichen, die durch Schwankungen des GWT und periodische Überflutungen verursacht wurden, und folglich auf wechselnde aerobe und anaerobe Abbauprozesse, die zu reduzierter SOM- und Streuzersetzung in Uferbereichen führen. Zweitens schlossen wir aufgrund der heterogenen δ13C-Tiefenprofile, insbesondere nach Landnutzungsänderungen, auf den Eintrag und die Akkumulation von allochthonem organischem Material mit unterschiedlichen Zersetzungsgraden durch mineralische Sedimente und die Ablagerung von organischem Material. Basierend auf diesen Ergebnissen stellen wir einen uferlandschafts-spezifischen Effekt fest, der dem erwarteten Landnutzungseffekt auf SOC-Verluste entgegenwirkt. Die Dynamik der saisonalen Überflutung, gefolgt von einer verzögerten Mineralisierung, spiegelt sich in dem heterogenen δ13C-Muster wider. Im Vergleich zu mineralisch terrestrischen Böden sind Böden in Uferbereichen widerstandsfähiger gegenüber kurzfristigen (1-2 Jahrzehnte) Bodenkohlenstoffverlusten nach Landnutzungsänderungen, da die Oberbodenschichten ähnliche SOC-Vorräte aufweisen wie die unter natürlicher Vegetation, jedoch muss berücksichtigt werden, dass sie, insbesondere wenn sie entwässert sind, langfristig ein hohes C-Verlustpotenzial haben. Unter Berücksichtigung der geringen SOC-Verluste in Uferbereichen nach Landnutzungsänderung und der Tatsache, dass das organische Material aufgrund anoxischer Bedingungen über einen langen Zeitraum unverändert erhalten bleibt, haben wir die Herkunftspools der SOM-Bestandteile und die Veränderung der SOM-Zusammensetzung nach Umwandlung von Wald in Plantagen bestimmt. Für die Untersuchung des zweiten Ziels verwendeten wir pflanzliche Lipide als molekulare Biomarker, die Einblicke in den vergangenen und gegenwärtigen SOC-Eintrag und dessen Abbaugrad im Boden geben können. Um zu untersuchen, ob Böden von Plantagen die rezente und/oder vergangene Vegetation widerspiegeln, verglichen wir Bodenlipide, die n-Alkane, Carbonsäuren, Alkohole und Ketone umfassen, in Streu-, Wurzel- und Bodenproben aus primärem Regenwald, Kautschuk- und Ölpalmenplantagen. Durch die Durchführung einer Indikator-Typen-Analyse fanden wir spezifische Substanzen (Biomarker), die einen einzelnen C-Pool in einem bestimmten Landnutzungstyp oder kleine Gruppen von C-Pools von den anderen C-Pools und Landnutzungstypen trennen. Diese Trennung war ein Indiz für höhere Abundanzen bestimmter Substanzen in bestimmten C-Pools und in einem bestimmten Landnutzungstyp. Wenn die Abundanzen zwischen dem Oberboden von Wäldern und dem Oberboden von Plantagen nicht signifikant waren, nahmen wir an, dass es immer noch einen Beitrag des C der vergangenen Vegetation zum aktuellen SOC-Pool in Plantagen gibt. In den Proben fanden wir sowohl pflanzliche als auch mikrobielle Stoffe, die auf einen Beitrag vergangener C-Pools hinweisen. Biomarker, die mikrobiellem Ursprung zugeordnet wurden, waren i15:0 und 18:2Ѡ6,2, während langkettige n-Alkane, wie C25 und C31 und n-Fettsäuren, wie 24:0, 27:0, 28:0 und 29:0, pflanzlichem Material zugeordnet wurden. Langkettige Fettsäuren, wie 24:0, weisen aufgrund ihrer langkettigen C-Verbindungen und der damit verbundenen hohen Resistenz gegenüber biologischem Abbau ähnliche Häufigkeiten zwischen Wäldern und Plantagen auf. Fettsäuren mit einer ungeraden Anzahl von C-Atomen, wie 27:0 und 29:0, sind eher Produkte der mikrobiellen Transformation von geradkettigen pflanzlichen Fettsäuren. Somit stellten wir fest, dass die Transformation von pflanzlichen Lipid- Zusammensetzungen durch Mikroorganismen eine Schlüsselrolle beim C-Umsatz im Boden spielt. Als weitere Indikatoren wurden die even-over-odd-predominance (OEP) des Alkanmusters und die even-over-odd-predominance (EOP) der n-Fettsäuren herangezogen, die auch auf einen hohen Anteil an noch untransformiertem pflanzlichen Ursprung des SOC hinweisen. Ähnliche Abundanzen der Hydroxyfettsäure 16-OH-16:0 wurden in allen Böden der drei Landnutzungstypen gefunden und konnte eindeutig der Waldstreu als wichtige C-Quelle zugeschrieben werden, die immer noch die C-Pools der Plantagen beeinflusst. Die Kombination mehrerer Biomarker, wie z. B. n- Alkane, n-Fettsäuren und Hydroxyfettsäuren, hilft, ein komplexes System von Wegen der SOC-Bildung im Boden zu aufzulösen. Nach dem Aufbau der Plantage beeinflussen weitere Faktoren den SOC-Abbau, da insbesondere in Ölpalmenplantagen üblicherweise Düngemittel und Herbizide zur Unkrautbekämpfung eingesetzt werden. Ausgehend davon wurde der Einfluss von Düngung (konventioneller und reduzierter NPK) und Unkrautbekämpfung (Herbizideinsatz oder die händische Unkrautbeseitigung) auf den SOC-Abbau in den Reihen zwischen den Palmen (engl. interrows) und um die Palmstämme (engl. weeding circles) untersucht. Dazu wurde dem Boden 14C-markierte Glukose zugesetzt, um die Reaktion der mikrobiellen Aktivität und der SOC-Mineralisierung während der 30-tägigen Inkubation zu analysieren. Die höchsten CO2-Emissionen wurden von den weeding circles (WC) gemessen, die mit dem konventionellen Düngungsniveau und Glyphosat behandelt wurden. Das hohe Düngungsniveau verursachte eine mikrobielle Aktivierung und destabilisierte den SOC durch sogenanntes Priming. In Kombination mit Glyphosat nahm die mikrobielle Aktivität weiter zu. Obwohl erwartet wurde, dass Glyphosat die mikrobielle Aktivität senkt, trat das Gegenteil ein und die mikrobielle Aktivität war unter dieser Behandlung am höchsten. Eine Erklärung dafür ist, dass NPK (Stickstoff, Phosphor, Kalium) einen größeren Anteil der Sorptionskapazitäten an den Bodenpartikeln einnimmt; daher ist Glyphosat immer noch verfügbar und kann als zusätzliche Quelle für C und möglicherweise N und P fungieren. Stattdessen verringern extensive Bewirtschaftungsmethoden (reduzierte Düngung + Glyphosat und händische Unkrautbeseitigung) die CO2-Emissionen und den SOC-Abbau, indem sie zu ausgeprägten negativen Priming-Effekten führten. Reduzierte Düngung und die Abwesenheit von Glyphosat führten zu dem stärksten negativen Priming (-47,9 µg g -1), was auf eine Verlangsamung des SOC-Abbaus hindeutet. Dieser verzögerte Abbau weist auf damit auf positive Effekte auf die C Akkumulation und Speicherung im Boden hin. In den interrows (IR) waren die Respirationsraten deutlich niedriger als in den WC, was durch die fehlende Düngung erklärt werden kann, die zu einem reduzierten Nährstoffangebot für Mikroorganismen führt. Normalerweise leiden Ölpalmenplantagen und insbesondere die ungedüngten IR aufgrund des fehlenden Eintrags von frischer Streu, geringer Wurzelbiomasse, geringer Rhizodeposition und hoher Nährstoffauswaschung unter Nährstoff- und C-Limitierung. Die Respirationsdaten deuten darauf hin, dass die C-Limitierung in IR bei allen Bewirtschaftungs-methoden stark ausgeprägt ist und die mikrobielle Aktivität in diesen Böden weitgehend einschränkt. Die C-Limitierung kann auf fehlenden organischen Input, z. B. Streu oder Unterholzvegetation, zurückgeführt werden, der auch die C-Sequestrierung im Boden beeinflusst. Insgesamt stellt die Studie ein verbessertes Verständnis der SOC-Pools und -Flüsse, die von den spezifischen Landschaftseigenschaften der Uferbereiche nach der Umwandlung von Wald in Plantagen sowie während der Anwendung von Managementpraktiken beim Ölpalmenanbau beeinflusst werden, bereit. Sie unterstreicht die Anfälligkeit von Böden in Uferbereichen, die langfristig eine starke C-Quelle darstellen können, insbesondere wenn sie entwässert werden, da sie ein hohes SOC-Verlustpotenzial haben. Veränderungen in der molekularen Zusammensetzung von SOM nach Landnutzungsänderungen haben noch unbekannte Auswirkungen auf die Ökosystemfunktion von SOM und die Stabilität dieses C-Pools. Um weitere Auswirkungen auf den Boden zu reduzieren, sollte eine nachhaltige Bewirtschaftungspraxis bei landwirtschaftlicher Nutzung angewendet werden, wie zum Beispiel die Reduzierung der NPK Düngermittelmenge und die Reduzierung von Herbiziden. Unsere Ergebnisse unterstreichen das Risiko der Bewirtschaftungsintensivierung und die Notwendigkeit einer schonenden Bewirtschaftungsstrategie, um die Bodenfruchtbarkeit und die Funktion als C-Speicher zu erhalten. Um dieses Ziel zu erreichen, ist es notwendig, den ober- und unterirdischen C-Eintrag zu gewährleisten, z.B. durch das Anhäufen von Ölpalmwedeln und das Ausbringen von leeren Fruchthülsen (engl. empty fruit bunches) als organischen Dünger und zur Unterstützung und Stabilisierung der Bodenqualität.Agricultural expansion is one of the most dominant drivers of deforestation word wide. The globally rising demand for cash crops such as oil palm and rubber, caused rapid agricultural expansion during the last decades, especially in South East Asia. Conversion of tropical rainforest to monocultural plantations are expected to lead to severe alterations in biogeochemical cycling and ecosystem functioning. This land-use change has major impacts on the global carbon (C) cycle as it reduces soil organic carbon (SOC) stocks, and increases carbon dioxide emissions (CO2). Additionally, increasing demand for cash crops favors the progressive conversion of less-well accessible landscape types, such as riparian areas. Riparian areas are especially sensitive to land-use change as they are mostly characterized by higher SOC stocks than well-drained areas and are habitats for a broad range of animals as well as plant species. It is therefore crucial to understand the changes in the SOC pool and SOC fluxes under the current land-use change to assess the impact on soil C cycling. The aim of this research project was therefore, to identify changes of SOC sources, i.e., soil organic matter (SOM) composition, its turnover and losses after riparian forest conversion to rubber and oil palm monocultures. The study was conducted in Sumatra, Indonesia, which is a hotspot of primary forest loss due to agricultural expansion. The first objective was to determine physical and chemical changes, especially SOC stock changes of riparian soils after land-use change and to compare them with SOC stock changes in well-drained areas. The second objective was to assess the contribution of past vegetation to the current SOC pool in forest and plantation soils and to find whether there is a change of SOM composition which indicates differences in SOM sources among the land use systems. With regard to urgently needed solutions to adapt to climate change, to maintain soil fertility, and the fact that the impact of intensive nitrogen (N) fertilization and herbicide application on the soil C cycle in these monocultures remains unknown, our last goal was to determine the effects of agricultural management practices on SOC decomposition and sequestration in oil palm plantations. For this purpose, a plantation with well-drained soil was selected, as greater generality can be derived from the results, since the majority of palm oil cultivation takes place on well-drained soils. For studying the first objective, SOC stocks and δ13C values were determined to assess C stocks changes and SOC decomposition in four riparian forest, four riparian rubber and four riparian oil palm plantation sites and compared to the same number of well-drained sites. Average soil C stock losses from the top 30 cm were about 14% and 4% following conversion of riparian forest to rubber and oil palm plantations, respectively, indicating a high resistance of C to mineralization. C losses from well-drained areas were twice as high as from riparian areas after conversion. δ13C values from riparian areas showed a strong heterogeneity within the soil profile compared to well-drained profiles, indicating different degrees of decomposition of SOM. Well-drained soil profiles showed the expected pattern with lower values (-29‰) in the topsoil and an adjustment to higher values (- 26‰) in the subsoil indicating that SOC in the topsoil was more intensively decomposed than in the subsoil. In combination with the evaluation of groundwater tables (GWT) we concluded first, alternating oxic and anoxic conditions in riparian areas caused by fluctuations in GWT and periodical flooding and consequently alternating aerobic and anaerobic decomposition processes leading to reduced SOM and litter decomposition in riparian areas. Second, due to the heterogeneous δ13C depth profiles, especially after land-use change, we concluded input and accumulation of allochthonous organic materials with various decomposition degrees by mineral sediments and organic matter deposition. Based on these findings we postulated a riparian landscape specific effect countering the expected land-use effect on SOC stocks. These dynamics of seasonal flooding followed by delayed mineralization are reflected by the heterogeneous δ13C pattern. Compared to well-drained areas, riparian areas are more resilient to short-term (1-2 decades) soil C loss after land-use change, indicated by similar topsoil C stocks as under natural vegetation. However, it has to be considered that they have, especially if drained, a high C loss potential in the long-term. Taking into account the minor loss in SOC stocks in riparian areas after land-use change, and that C is preserved over a long period of time due to anoxic conditions, we determined the pools of origin of SOM constituents and the change of SOM composition and its transformation after forest conversion to plantations. For studying the second objective, we used plant-derived lipids as molecular biomarkers that can provide insights into present and past SOC input and its degree of degradation within soil. To examine whether soils from plantations reflect recent and/or past vegetation, we compared soil lipids comprising n-alkanes, carboxylic acids, alcohols and ketons in litter, roots and soil samples from primary rainforest, rubber and oil palm plantations. By performing an indicator species analysis, we found specific substances (biomarkers) separating a single C pool in a specific land-use type or small groups of C pools from the other C pools and land-use types. This separation was indicative for higher abundances of specific substances in specific C pools and in a specific land-use type. If the abundances between forest topsoil and plantation topsoil were not significant different, we assumed that there was still a contribution of past vegetation to the current SOC pool in plantations. We found both plant and microbial materials in the samples, indicating a contribution from past C pools. Biomarkers assigned to microbial origin were e.g., i15:0 and 18:2Ѡ6,2, while long-chain n-alkanes, such as C25 and C31 and n-fatty acids, such as 24:0, 27:0, 28:0 and 29:0 were attributed to plant material. Long-chain fatty acids, such as 24:0, showed similar abundances between forests and plantations, due to their long-chain C compounds and the associated high resistance to biodegradation. Odd-chain fatty acids like 27:0 and 29:0 are rather the products of microbial transformation of even-chain plant-derived fatty acids. Hence, we found that transformation of plant-derived lipid fingerprints by microorganisms plays a key role during C turnover in soil. Further indicators were used, such as the odd-over-even predominance (OEP) of the alkane pattern and even-over-odd predominance (EOP) of the n-fatty acids also point to a high proportion of still untransformed plant-derived SOC. Similar abundances of the hydroxy fatty acid 16-OH-16:0 were found in all soils of the three land-use types and could be clearly attributed to forest litter as an important C source still influencing plantations C pools. Combining multiple biomarkers, such as n-alkanes, n-fatty acids and hydroxy fatty acids helped to disentangle a complex system of pathways of SOC formation in soil. After plantation establishment further factors influence SOC decomposition since especially oil palm plantations are commonly treated with fertilizer and herbicide for weed control. The impact of fertilization (conventional and reduced NPK) and weed control (herbicide application or mechanical weeding) on the SOC decomposition in the rows between the palms (interrows) and around the palm stems (weeding circles) was therefore studied for the third objective. 14C labelled glucose was added to soil to analyze the response of microbial activity and SOC mineralization during 30-day incubation. Highest CO2 emissions were measured from weeding circles (WC) treated with the conventional fertilization level and glyphosate. The high fertilization level caused microbial activation and destabilized SOC by priming. Although glyphosate was expected to lower the microbial activity, the opposite occurred and microbial activity was highest under this treatment. An explanation might be that NPK occupies a large share of sorption capacities on soil particles; hence, glyphosate is still available and can act as an additional source of C and possibly N and P to microorganisms. Instead, extensive management practices (reduced fertilization + glyphosate and mechanical weeding) decreased CO2 emissions and SOC decomposition by leading to pronounced negative priming effects. Reduced fertilization and the absence of glyphosate led to strongest negative priming (-47.9 µg C g -1), indicating a retardation of SOC decomposition. This suggests a retardation of SOC decomposition and therefore positive effects on C accumulation and storage. In interrows (IR), respiration rates were significantly lower than in the WC, which can be explained by the lack of fertilizer applicati