TY - GEN A1 - Wagner, Kathrin A1 - Oswald, Sascha A1 - Frick, Annett T1 - Multitemporal soil moisture monitoring by use of optical remote sensing data in a dike relocation area T2 - Remote Sensing for Agriculture, Ecosystems, and Hydrology XX N2 - The nature restoration project ‘Lenzener Elbtalaue’, realised from 2002 to 2011 at the river Elbe, included the first large scale dike relocation in Germany (420 ha). Its aim was to initiate the development of endangered natural wetland habitats and processes, accompanied by greater biodiversity in the former grassland dominated area. The monitoring of spatial and temporal variations of soil moisture in this dike relocation area is therefore particularly important for estimating the restoration success. The topsoil moisture monitoring from 1990 to 2017 is based on the Soil Moisture Index (SMI)1 derived with the triangle method2 by use of optical remotely sensed data: land surface temperature and Normalized Differnce Vegetation Index are calculated from Landsat 4/5/7/8 data and atmospheric corrected by use of MODIS data. Spatial and temporal soil moisture variations in the restored area of the dike relocation are compared to the agricultural and pasture area behind the new dike. Ground truth data in the dike relocation area was obtained from field measurements in October 2017 with a FDR device. Additionally, data from a TERENO soil moisture sensor network (SoilNet) and mobile cosmic ray neutron sensing (CRNS) rover measurements are compared to the results of the triangle method for a region in the Harz Mountains (Germany). The SMI time series illustrates, that the dike relocation area has become significantly wetter between 1990 and 2017, due to restructuring measurements. Whereas the SMI of the dike hinterland reflects constant and drier conditions. An influence of climate is unlikely. However, validation of the dimensionless index with ground truth measurements is very difficult, mostly due to large differences in scale. KW - soil moisture KW - time series KW - SMI KW - triangle method KW - Landsat KW - restoration Y1 - 2018 SN - 978-1-5106-2150-3 U6 - https://doi.org/10.1117/12.2325319 SN - 0277-786X SN - 1996-756X VL - 10783 PB - SPIE-INT Soc Optical Engineering CY - Bellingham ER - TY - JOUR A1 - Schrön, Martin A1 - Rosolem, Rafael A1 - Köhli, Markus A1 - Piussi, L. A1 - Schröter, I. A1 - Iwema, J. A1 - Kögler, S. A1 - Oswald, Sascha A1 - Wollschläger, U. A1 - Samaniego, Luis A1 - Dietrich, Peter A1 - Zacharias, Steffen T1 - Cosmic-ray Neutron Rover Surveys of Field Soil Moisture and the Influence of Roads JF - Water resources research N2 - Measurements of root-zone soil moisture across spatial scales of tens to thousands of meters have been a challenge for many decades. The mobile application of Cosmic Ray Neutron Sensing (CRNS) is a promising approach to measure field soil moisture noninvasively by surveying large regions with a ground-based vehicle. Recently, concerns have been raised about a potentially biasing influence of local structures and roads. We employed neutron transport simulations and dedicated experiments to quantify the influence of different road types on the CRNS measurement. We found that roads introduce a substantial bias in the CRNS estimation of field soil moisture compared to off-road scenarios. However, this effect becomes insignificant at distances beyond a few meters from the road. Neutron measurements on the road could overestimate the field value by up to 40 % depending on road material, width, and the surrounding field water content. The bias could be largely removed with an analytical correction function that accounts for these parameters. Additionally, an empirical approach is proposed that can be used without prior knowledge of field soil moisture. Tests at different study sites demonstrated good agreement between road-effect corrected measurements and field soil moisture observations. However, if knowledge about the road characteristics is missing, measurements on the road could substantially reduce the accuracy of this method. Our results constitute a practical advancement of the mobile CRNS methodology, which is important for providing unbiased estimates of field-scale soil moisture to support applications in hydrology, remote sensing, and agriculture. Plain Language Summary Measurements of root-zone soil moisture across spatial scales of tens to thousands of meters have been a challenge for many decades. The mobile application of Cosmic Ray Neutron Sensing (CRNS) is a promising approach to measure field soil moisture noninvasively by surveying large regions with a ground-based vehicle. Recently, concerns have been raised about a potentially biasing influence of roads. We employed physics simulations and dedicated experiments to quantify the influence of different road types on the CRNS measurement. We found that the presence of roads biased the CRNS estimation of field soil moisture compared to nonroad scenarios. Neutron measurements could overestimate the field value by up to 40 % depending on road material, width, surrounding field water content, and distance from the road. We proposed a correction function that successfully removed this bias and works even without prior knowledge of field soil moisture. Tests at different study sites demonstrated good agreement between corrected measurements and other field soil moisture observations. Our results constitute a practical advancement of the mobile CRNS methodology, which is important for providing unbiased estimates of field-scale soil moisture to support applications in hydrology, remote sensing, and agriculture. KW - road effect KW - field-scale KW - soil moisture KW - cosmic ray neutrons KW - mobile survey KW - COSMOS rover Y1 - 2018 U6 - https://doi.org/10.1029/2017WR021719 SN - 0043-1397 SN - 1944-7973 VL - 54 IS - 9 SP - 6441 EP - 6459 PB - American Geophysical Union CY - Washington ER -