Mean values and standard deviations of green LAI of agricultural fields in the Rur catchment (Germany) from remote sensing for seven dates in 2011
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Title: | Main Title: Mean values and standard deviations of green LAI of agricultural fields in the Rur catchment (Germany) from remote sensing for seven dates in 2011 |
Description: | Abstract: Field mean LAI from remote sensing used in Reichenau et. al (2016), "Spatial Heterogeneity of Leaf Area Index (LAI) and its Temporal Course on Arable Land: Combining Field Measurements, Remote Sensing and Simulation in a Comprehensive Data Analysis Approach (CDAA)". Name of the dataset in the article: rsfm. The table contains data on mean values and standard deviations of LAI for 24712 agricultural fields in the fertile loess plain of the Rur catchment. The data is based on LAI data generated from RapidEye remote sensing data (5 m resolution) using the method shown in Reichenau at al. (2016) based on Hasan et al. (2014). Fields were defined as continuous areas with uniform land use. Pixels with potential heterogeneous vegetation were excluded from the evaluation. For this means, pixels from a 15 m resolution land use dataset (Lussem and Waldhoff, 2014), that are not surrounded by the same land use type were marked as potentially mixed. Corresponding pixels from the LAI dataset were removed prior to the calculation of the mean values and standard deviations. Data is given for seven dates in 2011 where cloud-free scenes were recorded for (almost) the entirety of the Rur-catchment. Since the remote sensing scenes do not always cover the entirety of each field, the area of each field is given separately for each date. RapidEye data were provided by the RapidEye Science Archive (RESA). |
Identifier: | 10.5880/TR32DB.22 (DOI) |
Related Resources: | References 10.5880/TR32DB.20 (DOI) References 10.5880/TR32DB.21 (DOI) References 10.5880/TR32DB.23 (DOI) References 10.5880/TR32DB.7 (DOI) |
Responsible Party
Creators: | Tim G. Reichenau (Author), Carsten Montzka (Author), Florian Wilken (Author), Wolfgang Korres (Author), Karl Schneider (Author) |
Contributors: | University of Cologne (Institute of Geography) (Producer), Transregional Collaborative Research Centre 32 (Meteorological Institute, University of Bonn) (Producer) |
Funding Reference: | Deutsche Forschungsgemeinschaft (DFG): CRC/TRR 32: Patterns in Soil-Vegetation-Atmosphere Systems: Monitoring, Modelling and Data Assimilation |
Publisher: | CRC/TR32 Database (TR32DB) |
Publication Year: | 2016 |
Topic
TR32 Topic: | Vegetation |
Related Subprojects: | C3, C6 |
Subjects: | Keywords: Agriculture, Crop/s, LAI, Remote Sensing |
Geogr. Information Topic: | Farming |
File Details
Filename: | rsfm.zip |
Data Type: | Dataset - Dataset |
Size: | 7 Datasets |
File Size: | 1.5 MB |
Date: | Available: 03.06.2016 |
Mime Type: | application/zip |
Data Format: | CSV |
Language: | English |
Status: | Completed |
Archive Content
Constraints
Download Permission: | Free |
Download Information: | Download of the data underlies [Creative Commons] - Attribution 4.0 International (CC BY 4.0). Any other information is not valid and can be ignored. |
General Access and Use Conditions: | According to CC BY 4.0 |
Access Limitations: | According to CC BY 4.0 |
Licence: | [Creative Commons] Attribution 4.0 International (CC BY 4.0) |
Geographic
Specific Information - Data
Temporal Extent: | 22.02.2011, 00:00:00 - 22.10.2011, 23:59:00 |
Subtype: | Natural Science Data |
Metadata Details
Metadata Creator: | Tim G. Reichenau |
Metadata Created: | 06.06.2016 |
Metadata Last Updated: | 06.06.2016 |
Subproject: | C3 |
Funding Phase: | 3 |
Metadata Language: | English |
Metadata Version: | V50 |
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Dataset Statistics
Page Visits: | 841 |
Metadata Downloads: | 0 |
Dataset Downloads: | 12 |
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Adequate reference when this dataset will be discussed or used in any publication or presentation is mandatory. In this case please contact the dataset creator.
Adequate reference when this dataset will be discussed or used in any publication or presentation is mandatory. In this case please contact the dataset creator.