127 documents found in 386ms
# 1
Food and Agricultural Organisation (FAO)
Abstract: Soil map of the Baikal region from the FAO/IIASA digital soil data base of North and Central Asia (available on CD-ROM). The polygon data were transformed to UTM Z48, WGS 84. * pedology (FAO agro-economical soil types)
# 2
Heim, Birgit • Klump, Jens • Fagel, Natalie • Oberhänsli, Hedi
Abstract: Supplementary material to B. Heim et al. (2008): Assembly and concept of a web-based GIS within the paleoclimate project CONTINENT (Lake Baikal, Siberia)
# 3
Schaphoff (Ed.), Sibyll • von Bloh, Werner • Thonicke, Kirsten • Biemans, Hester • Forkel, Matthias • (et. al.)
Abstract: LPJmL4 is a process-based model that simulates climate and land-use change impacts on the terrestrial biosphere, the water and carbon cycle and on agricultural production. The LPJmL4 model combines plant physiological relations, generalized empirically established functions and plant trait parameters. The model incorporates dynamic land use at the global scale and is also able to simulate the production of woody and herbaceous short-rotation bio-energy plantations. Grid cells may contain one or several types of natural or agricultural vegetation. A comprehensive description of the model is given by Schaphoff et al. (2017a, http://doi.org/10.5194/gmd-2017-145). We here present the LPJmL4 model code described and used by the publications in GMD: LPJmL4 - a dynamic global vegetation model with managed land: Part I – Model description and Part II – Model evaluation (Schaphoff et al. 2018a and b, http://doi.org/10.5194/gmd-2017-145 and http://doi.org/10.5194/gmd-2017-146). The model code of LPJmL4 is programmed in C and can be run in parallel mode using MPI. Makefiles are provided for different platforms. Further informations on how to run LPJmL4 is given in the INSTALL file. Additionally to the publication a html documentation and man pages are provided. Additionally, LPJmL4 can be download from the Gitlab repository: https://gitlab.pik-potsdam.de/lpjml/LPJmL. Further developments of LPJmL will be published through this Gitlab repository regularly.
# 4
Rufin, Philippe • Levers, Christian • Baumann, Matthias • Jägermeyr, Jonas • Krueger, Tobias • (et. al.)
Abstract: The spatial distribution of irrigation dam benefits is poorly understood at the global scale due to a scarcity of spatial information on irrigation dam command areas. Several studies aimed at mapping irrigated lands globally, but the spatially explicit attribution of irrigated lands to dams has rarely been undertaken. First approaches attributing changes in agricultural production to dams were based on aggregated areal units, such as administrative districts (Duflo and Pande, 2007), or watershed boundaries (Strobl and Strobl, 2011). These approaches represent only indirect approximations of command areas, and may be improved by considering spatially explicit dam- and location-specific parameters (e.g. reservoir storage capacity or topography). Such a refined dataset is required for better understanding the spatial distribution and properties of irrigation dam command areas. We approximated irrigation dam command areas for 1,370 dams with irrigation function which were commissioned across 71 countries since 1985. We approximated a) the extent and b) the location of irrigation dam command areas at 500m spatial resolution using global-scale assumptions motivated by existing literature. We first estimated command area extent [ha] based on reservoir storage capacity [m³], while accounting for country-level variations in the ratio of land irrigated with surface water per unit of total national reservoir storage capacity [ha/m³]. We then spatially allocated the estimated command area extent for each dam, accounting for parameters representing: irrigated cropland abundance (P1), topography relative to the dam (P2), watershed boundaries (P3), reservoir size (P4), national borders (P5), and distance to the dam (P6). To understand the sensitivity of the allocation towards the assumptions underlying the selected parameters, we tested 24 different allocation schemes with varying parameter settings. An overview of the datasets used for the command area extent estimation and the spatial allocation procedure, as well as an illustration of an exemplary allocation is included in the download. For a detailed description of the methods used to produce these data, please see Rufin et al. (2018).
The CA1985 dataset includes two raster datasets in geographic coordinates (WGS1984, EPSG: 4326) in GeoTiff format: 1) CA1985_binary.tif: The spatial dataset of irrigation dam command areas commissioned since 1985 used for the analyses in Rufin et al. (under review). Command areas (value 1) are here defined as irrigated areas, within watershed delineations scaled according to the reservoir storage capacity, located topographically below, but at maximum 10 m above the impoundment and within the national borders of the dam location. A detailed description of the parameters and underlying assumptions is provided in Rufin et al. (2018). 2) CA1985_sensitivity.tif: An overlay of 24 allocation schemes with varying parametrizations to inform about the uncertainty associated with each allocated pixel. The data values range between 0 (not identified as a command area in any allocation scheme) and 24 (this pixel was identified as a command area in all 24 allocation schemes). A detailed description of the parameters used in the sensitivity analysis is provided in Rufin et al. (2018).
# 5
von Bloh, Werner • Schaphoff, Sibyll • Müller, Christoph • Rolinski, Susanne • Waha, Katharina • (et. al.)
Abstract: LPJmL5 is a dynamical global vegetation model that simulates climate and land-use change impacts on the terrestrial biosphere, the water, carbon and nitrogen cycle and on agricultural production. In particular, processes of soil nitrogen dynamics, plant uptake, nitrogen allocation, response of photosynthesis and maintenance respiration to varying nitrogen concentrations in plant organs, and agricultural nitrogen management are included into the model. A comprehensive description of the model is given by von Bloh et al. (2017,http://doi.org/10.5194/gmd-2017-228). We here present the LPJmL5 model code described and used by the publications in GMD: Implementing the Nitrogen cycle into the dynamic global vegetation, hydrology and crop growth model LPJmL (version 5) (von Bloh et al., 2017) The model code of LPJmL5 is programmed in C and can be run in parallel mode using MPI. Makefiles are provided for different platforms. Further informations on how to run LPJmL5 is given in the INSTALL file. Additionally to the publication a html documentation and manual pages are provided. The LPJmL5 version is based on LPJmL3.5 that is not publicly available. The LPJmL4 version without nitrogen cycle but with an updated phenology scheme can be found on github (https://github.com/PIK-LPJmL/LPJmL).
# 6
Hank, Tobias Benedikt • Locherer, Matthias • Richter, Katja • Mauser, Wolfram
Abstract: 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.
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.
# 7
Hank, Tobias Benedikt • Richter, Katja • Locherer, Matthias • Frank, Toni • Mauser, Wolfram
Abstract: 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.
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.
# 8
Schmidt, Marius
Abstract: TERENO Eifel-Rur Observatory. TERENO (TERrestrial ENvironmental Observatories) spans an Earth observation network across Germany that extends from the North German lowlands to the Bavarian Alps. This unique large-scale project aims to catalogue the longterm ecological, social and economic impact of global change at regional level.The central monitoring site of the TERENO Eifel/Lower Rhine Valley Observatory is the catchment area of the River Rur. It covers a total area of 2354 km² and exhibits a distinct land use gradient: The lowland region in the northern part is characterised by urbanisation and intensive agriculture whereas the low mountain range in the southern part is sparsely populated and includes several drinking water reservoirs. Furthermore, the Eifel National Park is situated in the southern part of the Rur catchment serving as a reference site. Intensive test sites are placed along a transect across the Rur catchments in representative land cover, soil, and geologic settings.The Rollesbroich site is located in the low mountain range “Eifel” near the German-Belgium border and covers the area of the small Kieselbach catchment (40 ha) with altitudes ranging from 474 to 518 m.a.s.l.. The climate is temperate maritime with a mean annual air temperature and precipitation of 7.7 °C and 1033 mm, respectively, for the period from 1981 to 2001. Soils are dominated by (stagnic) Cambisols and Stagnosols on Devonian shales with occasional sandstone inclusions that are covered by a periglacial solifluction clay–silt layer. The mountainous grassland vegetation is dominated by perennial ryegrass (Lolium perenne) and smooth meadow grass (Poa pratensis).The study site is highly instrumented. All components of the water balance (e.g. precipitation, evapotranspiration, runoff, soil water content) are continuously monitored using state-of-the-art instrumentation, including weighable lysimeters, runoff gauges, cosmic-ray soil moisture sensors, a wireless sensor network that monitors soil temperature, and soil moisture at 189 locations in different depths (5, 20 and 50 cm) throughout the study site. Periodically also different chamber measurements were made to access soil or plant gas exchange.This data set contains weekly updated flux-, meteorological and soil measurements of the permanent operating EC/Climate station Rollesbroich 1 (50.621° N, 6.304° E, 515 m a.s.l.), which was installed in spring 2011 at the border of two fields of grassland (5.8 and 7.8 ha) within the study site. Management of both fields is typical for the low mountain range of the Eifel region with one fertilizer application and three cuts per year. The area within the fetch of the eddy covariance tower is relatively flat with slopes ranging between 0.35° and 3.12°. The station is equipped with a CSAT3 sonic anemometer and LI7500 gas analyser. Besides flux measurements and typical climate parameters (radiation, air temperature, air humidity, soil moisture, soil temperature etc.) also the plant height and farming activities are recorded.Meteorological and soil data was at least controlled by visual inspection by using common plausibility ranges and cross checks with nearby stations. Afterwards the data was flagged according to it's quality (O.K., suspect, moderate, bad etc.). Flux data was processed and checked according to the TERENO QC scheme (Mauder,et al., 2013, doi:10.1016/j.agrformet.2012.09.006).
# 9
Hank, Tobias Benedikt • Locherer, Matthias • Richter, Katja • Mauser, Wolfram
Abstract: 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.Version History: Correct Acquisition date of the second HySpex flight was August 14th 2012, not August 12th 2012.
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.
# 10
Jarmer, Thomas • Siegmann, Bastian
Abstract: The dataset is composed of hyperspectral imagery acquired during airplane overflights on May 10th, 2011, June 27th, 2011 and May 24th, 2012 consisting of 367 and 368 spectral bands, respective-ly, ranging from VIS to SWIR (400 - 2500 nm) wavelength regions. The hyperspectral image data was acquired in the framework of the EnMAP preparation project HyLand (Hyperspectral remote sensing for the assessment of crop and soil parameters in precision farming and yield estimation). Within the project, innovative techniques were developed to derive crop and soil parameters from hyper-spectral remote sensing and terrestrial laser scanning data, which served as input parameters for novel yield estimation models.
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 extract-ing 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=flightbeta).
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