Beschreibung: The scope of the Science Plan is to describe the scientific background, applications, and activities related to the Environmental Mapping and Analysis Program (EnMAP) mission. Primarily, the document addresses scientists and funding institutions, but it may also be of interest for environmental stakeholders and governmental bodies. It is conceived to be a living document that will be updated throughout the entire mission. Chapter 1 provides a brief overview of the principles and current state of imaging spectroscopy. This is followed by an introduction to the EnMAP mission, including its objectives and potential impact on international programs as well as major environmental and societal challenges to their understanding and management EnMAP can contribute. Chapter 2 describes the EnMAP system together with data products and access, calibration/validation issues, and synergies with other missions. Chapter 3 gives an overview of the relevance, current lines of research, and potential contributions of EnMAP for major fields of application, such as vegetation, geology and soils, coastal and inland waters, cryosphere, urban areas, atmosphere and hazards to address the environmental and societal challenges presented in Chapter 1. Finally, Chapter 4 outlines the scientific exploitation strategy, which includes the strategy for community building and training, preparatory flight campaigns and software developments. A list of abbreviations is provided in the annex to this document, while an extended glossary of terms and abbreviations is available at the EnMAP website.

Beschreibung: The scope of this Science Plan is to describe the scientific background, applications, and activities related to the EnMAP mission. Primarily, the Science Plan addresses scientists and funding institutions, but it may also be of interest for environmental stakeholders and governmental bodies. It is conceived to be a living document that will be updated throughout the whole mission. Current global challenges call for interdisciplinary approaches. Hence, the science plan is not structured in the traditional disciplinary way. Instead, it builds on overarching research themes to which EnMAP can contribute. This Science Plan comprises the following five chapters presenting the significance, background, framework, applications, and strategy of the EnMAP mission: Chapter 2 highlights the need for EnMAP data with respect to major environmental issues and various stakeholders. This chapter states the mission’s main objectives and provides a list of research themes addressing global challenges to whose understanding and management EnMAP can contribute. Chapter 3 presents an overview of the EnMAP mission from a scientific point of view including a brief description of the mission parameters, data products and access, and calibration/validation issues. Chapter 4 provides an overview of hyperspectral remote sensing regarding its principles, development, and current state and synergies to other satellite missions. Chapter 5 describes current lines of research and EnMAP applications to address the research themes presented in Chapter 2. Finally, Chapter 6 outlines the scientific exploitation strategy, which includes the strategy for community building, dissemination of knowledge and increasing public awareness.

Beschreibung: The scope of the Science Plan is to describe the scientific background, applications, and activities of the Environmental Mapping and Analysis Program (EnMAP) imaging spectroscopy mission. Primarily, this document addresses scientists and funding institutions, but it may also be of interest to environmental stakeholders and governmental agencies. It is designed to be a living document that will be updated throughout the entire mission lifetime. Chapter 1 provides a brief overview of the principles and current state of imaging spectroscopy. This is followed by an introduction to the EnMAP mission, including its objectives and impact on international programs as well as major environmental and societal challenges. Chapter 2 describes the EnMAP system together with data products and access, calibration/validation, and synergies with other missions. Chapter 3 gives an overview of the major fields of application such as vegetation and forests, geology and soils, coastal and inland waters, cryosphere, urban areas, atmosphere and hazards. Finally, Chapter 4 outlines the scientific exploitation strategy, which includes the strategy for community building and training, preparatory flight campaigns and software developments. A list of abbreviations is provided in the annex to this document and an extended glossary of terms and abbreviations is available on the EnMAP website.

Beschreibung: Climate change manifests in terms of changing frequency and magnitude of extreme hydro-meteorological events and thus drives changes in urban flood hazard. Flood risk oriented urban planning is key to derive smart adaptation strategies, strengthen resilience and achieve sustainable development. 3D city models offer detailed spatial information which is useful to describe the exposure and to characterize the susceptibility of buildings at risk.This web-based application presents the 3d-city flood damage module (3DCFD) prototype which has been developed and implemented within a pathfinder projected funded by Climate-KIC during 2015-2016. The presentation illustrates the results of the 3DCFD-module exemplarily for the demonstration case in the City of Dresden. Relative damage to residential buildings which results from various flooding scenarios is shown for the focus area Pieschen in Dresden.The application allows the user to browse through the virtual city model and to colour the residential buildings regarding their relative damage values caused by different flooding scenarios. To do so click on 'Content', then on the brush-icon next to 'Buildings' and select a certain style from the drop-down menu. A style represents a specific combination of loss model and flooding scenario. Flooding scenarios provide spatially detailed inundation depth information according to different water stages at the gauge Dresden. Currently two flood loss models are implemented: a simple stage-damage-function (sdf) which related inundation depth to relative loss and the 3DCFD-module which uses additional information about building characteristics available from the virtual city model. A click on a coloured building will display additional information. The loss estimation module has been developed by the German Research Centre for Geosciences (GFZ), Section Hydrology. The web-application has been developed by virtualcitySYSTEMS GmbH. The data consisting of flood scenarios, a virtual 3D city model, and a terrain model were provided by the City of Dresden.

Beschreibung: Plastics have become an indispensable part of our daily life. It is a group of materials with outstanding properties for various products in a wide range of applications. They are durable, lightweight and cost-effective to manufacture. However, these advantages can develop to disadvantages if plastics are released into the environment uncontrolled and in large quantities. Here, both seas and soils form a final sink. Remote sensing has been used for many decades to observe the earth's surface and the processes that take place on it. The detection and identification of plastic litter is one of the latest applications of remote sensing. In recent publications, the potential of imaging spectroscopy has been highlighted, since it allows material identification and quantification based on material-specific absorption bands. In this study we investigate the influence of the object transparency and background surface reflectance on the detection and identification using hyperspectral remote sensing.

Beschreibung: Plastic pollution in inland waters and the open ocean is a long recognized problem for marine wildlife, coral reefs,the fishing industry and shipping transport safety. Microplastics, defined as particles 〈 5 mm, form a considerableportion of this pollution and have increasingly received public attention following recent discoveries that not onlycan these particles be ingested by planktonic animals, but also outnumber natural food items in some ocean ar-eas. Microplastic research has mainly concentrated on open seas, while riverine plumes and coastal areas remainlargely unexplored despite their hypothesized importance as microplastic sources. This work models coastal accu-mulation along the Adriatic coastline of microplastic particles (1-5 mm) emitted by the Po River, northern Italy,over 1.5 years. We hypothesize that river-induced microplastic accumulation on adjacent coasts can be predictedusing (1) hydrodynamic-based and (2) remote sensing-based modelling. Model accumulation maps were validatedagainst sampling at nine beaches (analyzed particle size range: 1-5 mm), with sediment microplastic concentra-tions up to 78 particles/kg (dry weight). Hydrodynamic modelling revealed that discharged particle amount is onlysemi-coupled to beaching rates, which are strongly river mouth dependent and occur primarily within the first tendays after discharge. Particles which did not beach within this period, representing more than 80% of all modelledparticles, were transported offshore and remained offshore. Remote sensing modelling was found to better captureriver mouth relative strength, and accumulation patterns were found largely consistent with hydrodynamic mod-elling. Comparison with remote sensing based accumulation maps and validation against in situ beach samplingare discussed. Suggestions are presented for future development of an operational monitoring system to assessmicroplastic pollution being emitted by a major river and its distribution along adjacent coastlines as well as intothe open ocean.

Beschreibung: Due to high spatiotemporal variability of aquatic systems, relationships between microplastic sources and sinks are highly complex and transportation pathways yet to be understood. Field data acquisitions are a necessary component for monitoring of microplastic contamination but alone cannot capture such complex relationships. Remote sensing is a key technology for environmental monitoring through which extrapolation of spatially limited field data to larger areas can be obtained. In this field study we tested whether microplastic distribution follows the same transport pattern as water constituents depictable from satellite images, namely chlorophyll-a, suspended particulate matter, and colored dissolved organic matter, and discuss their applicability as proxies. As rivers are a major source for marine microplastic contamination, we sampled three example river systems: the lower courses and river mouths of the Trave and Elbe estuary in Germany and the Po delta in Italy. For a full quantitative analysis of microplastics (〉300 μm), ATR- and FPA-based μFT-IR spectroscopy and NIR imaging spectroscopy were utilized. Comparing water constituents with in-situ data using regression analysis, neither a relationship for the Elbe estuary nor for the Po delta was found. Only for the Trave river, a positive relationship between microplastics and water constituents was present. Differences in hydrodynamic conditions and spatiotemporal dynamics of water constituents and microplastic emissions among the river systems are possible explanations for the contrary results. Based on our results no conclusions on other river systems and likewise different seasons can be drawn. For remote sensing algorithms of water constituents to be used as microplastic proxy an adaption for each system as well as for different seasons would thus be necessary. The lower detection limit of 300 μm for microplastics could also have influenced relationships as microplastic abundance exponentially increases with decreasing size class. Further studies with improved sampling methods are necessary to assess our proposed method.

Beschreibung: Plastic pollution in inland waters and the open ocean is a long recognized problem for marine wildlife, coral reefs,the fishing industry and shipping transport safety. Microplastics, defined as particles 〈 5 mm, form a considerableportion of this pollution and have increasingly received public attention following recent discoveries that not onlycan these particles be ingested by planktonic animals, but also outnumber natural food items in some ocean ar-eas. Microplastic research has mainly concentrated on open seas, while riverine plumes and coastal areas remainlargely unexplored despite their hypothesized importance as microplastic sources. This work models coastal accu-mulation along the Adriatic coastline of microplastic particles (1-5 mm) emitted by the Po River, northern Italy,over 1.5 years. We hypothesize that river-induced microplastic accumulation on adjacent coasts can be predictedusing (1) hydrodynamic-based and (2) remote sensing-based modelling. Model accumulation maps were validatedagainst sampling at nine beaches (analyzed particle size range: 1-5 mm), with sediment microplastic concentra-tions up to 78 particles/kg (dry weight). Hydrodynamic modelling revealed that discharged particle amount is onlysemi-coupled to beaching rates, which are strongly river mouth dependent and occur primarily within the first tendays after discharge. Particles which did not beach within this period, representing more than 80% of all modelledparticles, were transported offshore and remained offshore. Remote sensing modelling was found to better captureriver mouth relative strength, and accumulation patterns were found largely consistent with hydrodynamic mod-elling. Comparison with remote sensing based accumulation maps and validation against in situ beach samplingare discussed. Suggestions are presented for future development of an operational monitoring system to assessmicroplastic pollution being emitted by a major river and its distribution along adjacent coastlines as well as intothe open ocean.

Beschreibung: Although the Csingle bondH chains of petroleum derivatives display unique absorption features in the short-wave infrared (SWIR), it is a challenge to identify plastics on terrestrial surfaces. The diverse reflectance spectra caused by chemically varying polymer types and their different kinds of brightness and transparencies, which are, moreover, influenced further by the respective surface backgrounds. This paper investigates the capability of WorldView-3 (WV-3) satellite data, characterized by a high spatial resolution and equipped with eight distinct and relatively narrow SWIR bands suitable for global monitoring of different types of plastic materials. To meet the objective, hyperspectral measurements and simulations were conducted in the laboratory and by aircraft campaigns, based on the JPL-ECOSTRESS, USGS, and inhouse hyperspectral libraries, all of which are convolved to the spectral response functions of the WV-3 system. Experiments further supported the analyses wherein different plastic materials were placed on different backgrounds, and scaled percentages of plastics per pixel were modeled to determine the minimum detectable fractions. To determine the detectability of plastics with various chemical and physical properties and different fractions against diverse backgrounds, a knowledge-based classifier was developed, the routines of which are based on diagnostic spectral features in the SWIR range. The classifier shows outstanding results on various background scenarios for lab experimental imagery as well as for airborne data and it is further able to mask non-plastic materials. Three clusters of plastic materials can clearly be identified, based on spectra and imagery: The first cluster identifies aliphatic compounds, comprising polyethylene (PE), polyvinylchloride (PVC), ethylene vinyl acetate copolymer (EVAC), polypropylene (PP), polyoxymethylene (POM), polymethyl methacrylate (PMMA), and polyamide (PA). The second and third clusters are diagnostic for aromatic hydrocarbons, including polyethylene terephthalate (PET), polystyrene (PS), polycarbonate (PC), and styrene-acrylonitrile (SAN), respectively separated from polybutylene adipate terephthalate (PBAT), acrylonitrile butadiene styrene (ABS), and polyurethane (PU). The robustness of the classifier is examined on the basis of simulated spectra derived from our HySimCaR model, which has been developed in-house. The model simulates radiation transfer by using virtual 3D scenarios and ray tracing, hence, enables the analysis of the influence of various factors, such as material brightness, transparency, and fractional coverage as well as different background materials. We validated our results by laboratory and simulated datasets and by tests using airborne data recorded at four distinct sites with different surface characteristics. The results of the classifier were further compared to results produced by another signature-based method, the spectral angle mapper (SAM) and a commonly used technique, the maximum likelihood estimation (MLE). Finally, we applied and successfully tested the classifier on WV-3 imagery of sites known for a high abundance of plastics in Almeria (Spain), Cairo (Egypt), and Accra, (Ghana, West Africa). Both airborne and WV-3 data were atmospherically corrected and transferred to “at-surface reflectances”. The results prove the combination of WV-3 data and the newly designed classifier to be an efficient and reliable approach to globally monitor and identify three clusters of plastic materials at various fractions on different backgrounds.