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  • 1
    Call number: PIK N 454-99-0391
    Type of Medium: Monograph available for loan
    Pages: 477 p. + CD
    ISBN: 3527271457
    Branch Library: PIK Library
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  • 2
    Monograph available for loan
    Monograph available for loan
    Frankfurt am Main : Fischer
    Call number: PIK N 453-07-0280 ; PIK N 453-08-0265
    Type of Medium: Monograph available for loan
    Pages: 224 S. , 190 mm x 125 mm
    Edition: Orig.-Ausg., 1. Aufl
    ISBN: 359617273X , 978-3-596-17273-3
    Series Statement: Forum für Verantwortung 17273
    Branch Library: PIK Library
    Branch Library: PIK Library
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  • 3
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    PANGAEA
    In:  Supplement to: Meier, Jonas; Zabel, Florian; Mauser, Wolfram (2018): A global approach to estimate irrigated areas – a comparison between different data and statistics. Hydrology and Earth System Sciences, 22(2), 1119-1133, https://doi.org/10.5194/hess-22-1119-2018
    Publication Date: 2020-01-17
    Description: Agriculture is the largest global consumer of water. Irrigated areas constitute 40 % of the total area used for agricultural production (FAO, 2014a) Information on their spatial distribution is highly relevant for regional water management and food security. Spatial information on irrigation is highly important for policy and decision makers, who are facing the transition towards more efficient sustainable agriculture. However, the mapping of irrigated areas still represents a challenge for land use classifications, and existing global data sets differ strongly in their results. The following study tests an existing irrigation map based on statistics and extends the irrigated area using ancillary data. The approach processes and analyzes multi-temporal normalized difference vegetation index (NDVI) SPOT-VGT data and agricultural suitability data - both at a spatial resolution of 30arcsec - incrementally in a multiple decision tree. It covers the period from 1999 to 2012. The results globally show a 18 % larger irrigated area than existing approaches based on statistical data. The largest differences compared to the official national statistics are found in Asia and particularly in China and India. The additional areas are mainly identified within already known irrigated regions where irrigation is more dense than previously estimated. The validation with global and regional products shows the large divergence of existing data sets with respect to size and distribution of irrigated areas caused by spatial resolution, the considered time period and the input data and assumption made.
    Type: Dataset
    Format: application/zip, 4577.0 kBytes
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  • 4
    ISSN: 1420-9055
    Keywords: Patchiness ; calcite ; Lake Constance ; LANDSAT-Thematic Mapper
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: Abstract Calcite precipitation is a phenomenon occuring in most hardwater lakes world-wide. On May 5th, 1990, a whiting in Lake Constance was observed by LANDSAT for the first time. Physical, chemical and biological ground data sets prove that the observed structures are caused by calcite precipitation. This satellite observation provides information about the patchiness of calcite crystals suspended in the surface water of the lake western basin.
    Type of Medium: Electronic Resource
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  • 5
    Publication Date: 2017-01-18
    Description: The temporal evolution of Alpine snowpacks is important for assessing water supply, hydropower generation, flood predictions and avalanche forecasts. Especially in high mountain regions with an extremely varying topography, it is until now often difficult to derive continuous and non-destructive information on snow parameters. Since autumn 2012, we are running a new low-cost GPS (Global Positioning System) snow measurement experiment at the high alpine study site Weissfluhjoch (2450 m a.s.l.) in Switzerland. The globally and freely broadcasted GPS L1-band (1.57542 GHz) was continuously recorded with GPS antennas, which are installed at the ground surface underneath the snowpack. GPS raw data, containing carrier-to-noise power density ratio (C/N0) as well as elevation and azimuth angle information for each time step of 1 s, was stored and analyzed for all 32 GPS satellites. Since the dielectric permittivity of an overlying wet snowpack influences microwave radiation, the bulk volumetric liquid water content as well as daily melt-freeze cycles can be derived non-destructively from GPS signal strength losses and external snow height information. This liquid water content information is qualitatively in good accordance with meteorological and snow-hydrological data and quantitatively highly agrees with continuous data derived from an upward-looking ground-penetrating radar (upGPR) working in a similar frequency range. As a promising novelty, we combined the GPS signal strength data with upGPR travel-time information of active impulse radar rays to the snow surface and back from underneath the snow cover. This combination allows determining liquid water content, snow height and snow water equivalent from beneath the snow cover without using any other external information. The snow parameters derived by combining upGPR and GPS data are in good agreement with conventional sensors as e.g. laser distance gauges or snow pillows. As the GPS sensors are cheap, they can easily be installed in parallel with further upGPR systems or as sensor networks to monitor the snowpack evolution in avalanche paths or at a larger scale in an entire hydrological basin to derive distributed melt-water runoff information.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Conference , NonPeerReviewed
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  • 6
    Publication Date: 2017-01-16
    Description: Information on snowpack properties is highly relevant for avalanche warning systems, flood predictions and hydropower management within alpine regions influenced by seasonal snow cover. However, snow measurements are often scarce and labour-intense and it is still challenging to monitor snow parameters with sufficient temporal and spatial resolution, especially in remote complex terrain. Since 2012, we are running three low-cost GPS (Global Positioning System) receivers at the high-alpine study site Weissfluhjoch in Switzerland. The sensors record the globally and freely broadcasted GPS L1-band data continuously above and underneath the snow cover. Snow liquid water content and daily melt-freeze cycles were successfully calculated based on GPS signal strength losses, complex permittivity models and external snow height information. The results show high accordance with meteorological and snow-hydrological data. The evolution of liquid water content derived by GPS agrees very well (RMSE: 0.4-0.7 pp) with simultaneous non-destructive upward-looking ground-penetrating radar (upGPR) measurements from below the snow cover. Moreover, we aim to determine further snow properties by analysing temporal changes in the received GPS carrier-to-noise-power-density ratio and carrier phase information for all 32 GPS satellites, whereof preliminary results will be presented, too. Due to its non-destructive setup, low costs and low power consumption, networks of these in-situ GNSS (Global Navigation Satellite System) sensors can be used for a applications in remote areas, for instance to cover a better geographical distribution of snow measurements aiming to support users in the water supply and hazard management sectors.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Conference , NonPeerReviewed
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  • 7
    Publication Date: 2017-01-16
    Description: The temporal evolution of snowpacks is important for avalanche forecasts and flood predictions. Especially in complex alpine terrain, such as avalanche starting zones, it is until now difficult to derive continuous and non-destructive information on snow parameters. In our previous work, we already demonstrated the feasibility to quantitatively derive snowpack properties and monitor their evolution in time using an upward-looking ground penetrating radar (upGPR) that was buried underneath the snow. To determine some properties, we still needed additional information such as independently measured snow height. To overcome these limitations, we present two promising methods: (1) We combined the upGPR travel-time information with tomographic GPS signal strength losses. This combination allowed determining liquid water content, snow height and snow water equivalent from beneath the snow cover without using external information. The snow parameters derived by combining upGPR and GPS data are in good agreement with conventional sensors as e.g. laser distance gauges or snow pillows. As the GPS sensors are cheap, they can easily be installed in parallel with upGPR systems. (2) To fully exploit the information content of upGPR data, and thus to at least partially compensate for the lack of information, we applied full-waveform inversion (FWI) techniques. We refined the model of the snowpack by repeated forward modeling the waveforms and updating the model parameters to match it with recorded data. This allowed us to determine the density and the liquid water content for each layer in the snowpack. Both approaches show a high potential for alpine management tasks.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Conference , NonPeerReviewed
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  • 8
    Publication Date: 2016-11-25
    Description: Abstract
    Description: This data collection contains airborne hyperspectral data as well as accompanying in-situ data acquired in autumn 2009 in the Neusling test area near Landau a.d. Isar in Southern Germany. The dataset is composed of a) two airborne hyperspectral image strips acquired during an overflight on July 27th, 2009 with the HyMap instrument over two areas; “Neusling” and “Steinbeissen”. The airborne data consists of 125 spectral bands, ranging from VIS to SWIR (455 - 2478 nm); b) spectral reference measurements acquired with a portable ASD FieldSpec 3 JR spectroradiometer in 2150 spectral bands (350 - 2500nm) taken parallel to the overflight; c) spatially comprehensive land use/land cover maps for both flight strips generated from in-situ observations during the days next to the overflight; d) Flight-parallel in-situ point-measurements consisting of: i) destructively measured aboveground dry biomass and canopy water content of maize, sugar beet and winter wheat (58 measurements), ii) non-destructive measurements of LAI of sugar beet and maize (52 measurements), iii) TDR soil moisture measurements covering the main land cover types in the area (250 measurements), iv) 249 measurements of canopy height, v) 199 observations of plant phenology. The dataset was intended to be used in an educational context and was collected with an agricultural focus.
    Description: Other
    Description: The Environmental Mapping and Analysis Program (EnMAP) is a German hyperspectral satellite mission that aims at monitoring and characterizing the Earth’s environment on a global scale. EnMAP serves to measure and model key dynamic processes of the Earth’s ecosystems by extracting geochemical, biochemical and biophysical parameters, which provide information on the status and evolution of various terrestrial and aquatic ecosystems. In the frame of the EnMAP preparatory phase, pre-flight campaigns including airborne and in-situ measurements in different environments and for several application fields are being conducted. The main purpose of these campaigns is to support the development of scientific applications for EnMAP. In addition, the acquired data are input in the EnMAP end-to-end simulation tool (EeteS) and are employed to test data pre-processing and calibration-validation methods. The campaign data are made freely available to the scientific community under a Creative Commons Attribution-ShareAlike 4.0 International License. An overview of all available data is provided in in the EnMAP Flight Campaigns Metadata Portal http://www.enmap.org/?q=flights.
    Keywords: Hyperspectral Imagery ; Field Spectroscopy ; Agriculture ; Biomass ; Canopy Water Content ; LAI
    Language: English
    Type: Dataset , Dataset
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  • 9
    Publication Date: 2016-11-25
    Description: Abstract
    Description: This data collection contains airborne hyperspectral data as well as accompanying in-situ data acquired in autumn 2011 in the Neusling test area near Landau a.d. Isar in Southern Germany. The dataset is composed of a) three airborne hyperspectral image strips acquired during an overflight on September 10th, 2011 with the APEX instrument. The airborne data consists of 288 spectral bands, ranging from VIS to SWIR (413 - 2449 nm). A mosaic of the three image strips covering the Neusling test area is also provided; b) spectral reference and control measurements acquired with a portable ASD FieldSpec 3 JR spectroradiometer in 2150 spectral bands (350 - 2500nm) taken parallel to the overflight; c) a spatially comprehensive land use/land cover map generated from in-situ observations during the days next to the overflight; d) Flight-parallel in-situ point-measurements consisting of: i) non-destructively measured leaf area index of sugar beet, maize, grassland and legumes (105 measurements incl. standard deviations), ii) SPAD chlorophyll measurements (106 measurements incl. standard deviations), iii) 106 measurements of canopy height (incl. standard deviations). The dataset was collected with an agricultural focus.
    Description: Other
    Description: The Environmental Mapping and Analysis Program (EnMAP) is a German hyperspectral satellite mission that aims at monitoring and characterizing the Earth’s environment on a global scale. EnMAP serves to measure and model key dynamic processes of the Earth’s ecosystems by extracting geochemical, biochemical and biophysical parameters, which provide information on the status and evolution of various terrestrial and aquatic ecosystems. In the frame of the EnMAP preparatory phase, pre-flight campaigns including airborne and in-situ measurements in different environments and for several application fields are being conducted. The main purpose of these campaigns is to support the development of scientific applications for EnMAP. In addition, the acquired data are input in the EnMAP end-to-end simulation tool (EeteS) and are employed to test data pre-processing and calibration-validation methods. The campaign data are made freely available to the scientific community under a Creative Commons Attribution-ShareAlike 4.0 International License. An overview of all available data is provided in in the EnMAP Flight Campaigns Metadata Portal http://www.enmap.org/?q=flights.
    Keywords: Hyperspectral Imagery ; Field Spectroscopy ; Agriculture ; LAI
    Language: English
    Type: Dataset , Dataset
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  • 10
    Publication Date: 2016-11-25
    Description: Abstract
    Description: This data collection contains a multitemporal series of six airborne hyperspectral image mosaics acquired during the growing season of 2012 over the Neusling test area near Landau a.d. Isar in Southern Germany. The airborne hyperspectral data is complemented by accompanying in-situ data acquired parallel to the overflights. The dataset is composed of a) four airborne hyperspectral image mosaics acquired during overflights on April 28th 2012, May 25th 2012, June 16th 2012 and September 8th 2012 with the AVIS-3 imaging spectrometer. The AVIS data consists of 197 spectral bands, ranging from VIS to SWIR (477 - 1704 nm); b) two airborne hyperspectral image mosaics acquired during overflights, which were conducted by the DLR user service OpAiRS (www.dlr.de/opairs) on May 8th 2012 and August 14th 2012 with a HySpex imaging spectrometer. The HySpex data consists of 332 spectral bands, ranging from VIS to SWIR (417 - 2496 nm); c) spatially comprehensive land use/land cover maps generated from in-situ observations for two time-windows during the growing season of 2012 (May and August); d) Flight-parallel in-situ point-measurements consisting of: i) non-destructively measured leaf area index of winter wheat, winter barley, sugar beet, maize and rapeseed (561 measurements incl. standard deviations), ii) SPAD chlorophyll measurements (522 measurements incl. standard deviations), iii) 557 soil moisture measurements incl. standard deviations iv) 539 phenological observations v) 499 measurements of canopy height incl. standard deviations and vi) 38 measurements of plant density. The dataset was collected in order to cover the seasonal dynamics in the development of agricultural crops in Southern Germany.Erratum: Correct Acquisition date of the second HySpex flight was August 14th 2012, not August 12th 2012.
    Description: Other
    Description: The Environmental Mapping and Analysis Program (EnMAP) is a German hyperspectral satellite mission that aims at monitoring and characterizing the Earth’s environment on a global scale. EnMAP serves to measure and model key dynamic processes of the Earth’s ecosystems by extracting geochemical, biochemical and biophysical parameters, which provide information on the status and evolution of various terrestrial and aquatic ecosystems. In the frame of the EnMAP preparatory phase, pre-flight campaigns including airborne and in-situ measurements in different environments and for several application fields are being conducted. The main purpose of these campaigns is to support the development of scientific applications for EnMAP. In addition, the acquired data are input in the EnMAP end-to-end simulation tool (EeteS) and are employed to test data pre-processing and calibration-validation methods. The campaign data are made freely available to the scientific community under a Creative Commons Attribution-ShareAlike 4.0 International License. An overview of all available data is provided in in the EnMAP Flight Campaigns Metadata Portal http://www.enmap.org/?q=flights.
    Keywords: Hyperspectral Imagery ; Field Spectroscopy ; Agriculture ; LAI
    Language: English
    Type: Dataset , Dataset
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