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000884858 1001_ $$00000-0002-5062-6218$$aReichenau, Tim G.$$b0$$eCorresponding author
000884858 245__ $$aA comprehensive dataset of vegetation states, fluxes of matter and energy, weather, agricultural management, and soil properties from intensively monitored crop sites in western Germany
000884858 260__ $$aKatlenburg-Lindau$$bCopernics Publications$$c2020
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000884858 520__ $$aThe development and validation of hydroecological land-surface models to simulate agricultural ar-eas require extensive data on weather, soil properties, agricultural management, and vegetation states and fluxes.However, these comprehensive data are rarely available since measurement, quality control, documentation, andcompilation of the different data types are costly in terms of time and money. Here, we present a comprehensivedataset, which was collected at four agricultural sites within the Rur catchment in western Germany in the frame-work of the Transregional Collaborative Research Centre 32 (TR32) “Patterns in Soil–Vegetation–AtmosphereSystems: Monitoring, Modeling and Data Assimilation”. Vegetation-related data comprise fresh and dry biomass(green and brown, predominantly per organ), plant height, green and brown leaf area index, phenological devel-opment state, nitrogen and carbon content (overall>17 000 entries), and masses of harvest residues and regrowthof vegetation after harvest or before planting of the main crop (>250 entries). Vegetation data including LAIwere collected in frequencies of 1 to 3 weeks in the years 2015 until 2017, mostly during overflights of the Sen-tinel 1 and Radarsat 2 satellites. In addition, fluxes of carbon, energy, and water (>180 000 half-hourly records)measured using the eddy covariance technique are included. Three flux time series have simultaneous data fromtwo different heights. Data on agricultural management include sowing and harvest dates as well as informationon cultivation, fertilization, and agrochemicals (27 management periods). The dataset also includes gap-filledweather data (>200 000 hourly records) and soil parameters (particle size distributions, carbon and nitrogencontent;>800 records). These data can also be useful for development and validation of remote-sensing prod-ucts. The dataset is hosted at the TR32 database (https://www.tr32db.uni-koeln.de/data.php?dataID=1889, lastaccess: 29 September 2020) and has the DOI https://doi.org/10.5880/TR32DB.39 (Reichenau et al., 2020).
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000884858 536__ $$0G:(GEPRIS)15232683$$aDFG project 15232683 - TRR 32: Muster und Strukturen in Boden-Pflanzen-Atmosphären-Systemen: Erfassung, Modellierung und Datenassimilation (15232683)$$c15232683$$x1
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000884858 7001_ $$0P:(DE-HGF)0$$aKorres, Wolfgang$$b1
000884858 7001_ $$0P:(DE-Juel1)144420$$aSchmidt, Marius$$b2
000884858 7001_ $$0P:(DE-Juel1)129461$$aGraf, Alexander$$b3
000884858 7001_ $$00000-0002-6879-077X$$aWelp, Gerhard$$b4
000884858 7001_ $$0P:(DE-HGF)0$$aMeyer, Nele$$b5
000884858 7001_ $$0P:(DE-HGF)0$$aStadler, Anja$$b6
000884858 7001_ $$0P:(DE-Juel1)168418$$aBrogi, Cosimo$$b7
000884858 7001_ $$0P:(DE-HGF)0$$aSchneider, Karl$$b8
000884858 773__ $$0PERI:(DE-600)2475469-9$$a10.5194/essd-12-2333-2020$$gVol. 12, no. 4, p. 2333 - 2364$$n4$$p2333 - 2364$$tEarth system science data$$v12$$x1866-3516$$y2020
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