TY - JOUR A1 - Kaiser, Thomas A1 - Wehrhan, Marc A1 - Werner, Armin A1 - Sommer, Michael T1 - Regionalizing ecological moisture levels and groundwater levels in grassland areas using thermal remote sensing JF - Grassland science N2 - Site-specific soil moisture and groundwater levels are key input parameters for ecological modeling. Obtaining such information in a comprehensive manner is difficult for large regions. We studied a floodplain region in the Federal State of Brandenburg, Germany, to examine the degree to which the average depth of groundwater tables can be derived from surface temperatures obtained by the ASTER radiospectrometer (spatial resolution of 90 m per pixel). A floristic ecological indicator representing the site-specific moisture level was applied to develop a proxy between the thermal satellite data and groundwater table depth. The use of spring scenes (late April to early May) from 2 years proved to be well suited for minimizing the effects of weather and land use. Vegetation surveys along transects that were 2 m wide across the pixel diagonals allowed for the calculation of average ecological moisture values of pixel-sites by applying Ellenberg-numbers. These values were used to calibrate the satellite data locally. There was a close relationship between surface temperature and the average ecological moisture value (R2 = 0.73). Average ecological moisture values were highly indicative of the average groundwater levels during a 7-year measurement series (R2 = 0.93). Satellite-supported thermal data from spring were suitable for estimating the average groundwater levels of low-lying grasslands on a larger scale. Ecological moisture values from the transect surveys effectively allowed the incorporation of relief heterogeneity within the thermal grid and the establishment of the correlation between thermal data and average groundwater table depth. Regression functions were used to produce a map of groundwater levels at the study site. KW - Ellenberg indicator values KW - groundwater table KW - satellite data KW - soil moisture Y1 - 2012 U6 - https://doi.org/10.1111/j.1744-697X.2011.00240.x SN - 1744-6961 VL - 58 IS - 1 SP - 42 EP - 52 PB - Wiley-Blackwell CY - Malden ER - TY - JOUR A1 - Kühn, Jürgen A1 - Brenning, Alexander A1 - Wehrhan, Marc A1 - Koszinski, Sylvia A1 - Sommer, Michael T1 - Interpretation of electrical conductivity patterns by soil properties and geological maps for precision agriculture N2 - Precision farming needs management rules to apply spatially differentiated treatments in agricultural fields. Digital soil mapping (DSM) tools, for example apparent soil electrical conductivity, corrected to 25A degrees C (EC25), and digital elevation models, try to explain the spatial variation in soil type, soil properties (e.g. clay content), site and crop that are determined by landscape characteristics such as terrain, geology and geomorphology. We examined the use of EC25 maps to delineate management zones, and identified the main factors affecting the spatial pattern of EC25 at the regional scale in a study area in eastern Germany. Data of different types were compared: EC25 maps for 11 fields, soil properties measured in the laboratory, terrain attributes, geological maps and the description of 75 soil profiles. We identified the factors that influence EC25 in the presence of spatial autocorrelation and field-specific random effects with spatial linear mixed-effects models. The variation in EC25 could be explained to a large degree (R (2) of up to 61%). Primarily, soil organic matter and CaCO3, and secondarily clay and the presence of gleyic horizons were significantly related to EC25. Terrain attributes, however, had no significant effect on EC25. The geological map unit showed a significant relationship to EC25, and it was possible to determine the most important soil properties affecting EC25 by interpreting the geological maps. Including information on geology in precision agriculture could improve understanding of EC25 maps. The EC25 maps of fields should not be assumed to represent a map of clay content to form a basis for deriving management zones because other factors appeared to have a more important effect on EC25. Y1 - 2009 UR - http://www.springerlink.com/content/103317 U6 - https://doi.org/10.1007/s11119-008-9103-z SN - 1385-2256 ER - TY - JOUR A1 - Reiche, Matthias A1 - Funk, Roger A1 - Zhang, Zhuodong A1 - Hoffmann, Carsten A1 - Reiche, Johannes A1 - Wehrhan, Marc A1 - Li, Yong A1 - Sommer, Michael T1 - Application of satellite remote sensing for mapping wind erosion risk and dust emission-deposition in Inner Mongolia grassland, China JF - Grassland science N2 - Intensive grazing leads to land degradation and desertification of grassland ecosystems followed by serious environmental and social problems. The Xilingol steppe grassland in Inner Mongolia, China, which has been a sink area for dust for centuries, is strongly affected by the negative effects of overgrazing and wind erosion. The aim of this study is the provision of a wind erosion risk map with a spatial high resolution of 25 m to identify actual source and sink areas. In an integrative approach, field measurements of vegetation features and surface roughness length z0 were combined with Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) image data for a land use classification. To determine the characteristics of the different land use classes, a field observation (ground truth) was performed in April 2009. The correlation of vegetation height and z0 (R2 = 0.8, n = 55) provided the basis for a separation of three main classes, grassland, non-vegetation and other. The integration of the soil-adjusted vegetation index (SAVI) and the spectral information from the atmospheric corrected ASTER bands 1, 2 and 3 (visible to near-infrared) led to a classification of the overall accuracy (OA) of 0.79 with a kappa () statistic of 0.74, respectively. Additionally, a digital elevation model (DEM) was used to identify topographical effects in relation to the main wind direction, which enabled a qualitative estimation of potential dust deposition areas. The generated maps result in a significantly higher description of the spatial variability in the Xilingol steppe grassland reflecting the different land use intensities on the current state of the grassland less, moderately and highly degraded. The wind erosion risk map enables the identification of characteristic mineral dust sources, sinks and transition zones. KW - Advanced Spaceborne Thermal Emission and Reflection Radiometer data KW - dust emission and deposition KW - soil-adjusted vegetation index KW - semiarid grassland KW - wind erosion Y1 - 2012 U6 - https://doi.org/10.1111/j.1744-697X.2011.00235.x SN - 1744-6961 VL - 58 IS - 1 SP - 8 EP - 19 PB - Wiley-Blackwell CY - Malden ER - TY - JOUR A1 - Wehrhan, Marc A1 - Rauneker, Philipp A1 - Sommer, Michael T1 - UAV-Based Estimation of Carbon Exports from Heterogeneous Soil Landscapes-A Case Study from the CarboZALF Experimental Area JF - SENSORS N2 - The advantages of remote sensing using Unmanned Aerial Vehicles (UAVs) are a high spatial resolution of images, temporal flexibility and narrow-band spectral data from different wavelengths domains. This enables the detection of spatio-temporal dynamics of environmental variables, like plant-related carbon dynamics in agricultural landscapes. In this paper, we quantify spatial patterns of fresh phytomass and related carbon (C) export using imagery captured by a 12-band multispectral camera mounted on the fixed wing UAV Carolo P360. The study was performed in 2014 at the experimental area CarboZALF-D in NE Germany. From radiometrically corrected and calibrated images of lucerne (Medicago sativa), the performance of four commonly used vegetation indices (VIs) was tested using band combinations of six near-infrared bands. The highest correlation between ground-based measurements of fresh phytomass of lucerne and VIs was obtained for the Enhanced Vegetation Index (EVI) using near-infrared band b(899). The resulting map was transformed into dry phytomass and finally upscaled to total C export by harvest. The observed spatial variability at field- and plot-scale could be attributed to small-scale soil heterogeneity in part. KW - VI KW - soil landscape KW - carbon export KW - agriculture KW - multispectral KW - UAV Y1 - 2016 U6 - https://doi.org/10.3390/s16020255 SN - 1424-8220 VL - 16 PB - MDPI CY - Basel ER -