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Thomas Jagdhuber

Thomas Jagdhuber
German Aerospace Center (DLR) - University of Augsburg

Dr.

About

278
Publications
44,272
Reads
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2,896
Citations
Introduction
If you are interested, several full texts of the here listed publications are freely, but only available via our DLR publication library (http://elib.dlr.de). Have fun exploring! Moreover, please contact me directly for collaboration and literature via email (thomas.jagdhuber@dlr.de). I do not find time organizing this via researchgate. Thank you very much. Best regards & keep citing :) Thomas
Additional affiliations
November 2020 - present
Universität Augsburg
Position
  • Lecturer
January 2007 - December 2020
German Aerospace Center (DLR)
Position
  • Researcher

Publications

Publications (278)
Article
Full-text available
An approach for estimating vertically continuous soil moisture profiles under varying vegetation covers by combining remote sensing with soil (hydrological) modeling is proposed. The approach uses decomposed soil scattering components, after the removal of the vegetation scattering components from fully polarimetric P-band SAR observations. By comp...
Article
Full-text available
High temporal soil moisture at field scale resolution (10 m - 100 m) is important for smart farming decisions. Although, medium and coarse resolution (1 km - 50 km) soil moisture information is operationally available on a large scale, high resolution (field scale) data sets are not. This study propose a data assimilation approach to downscale medi...
Article
Full-text available
The Gravity Recovery and Climate Experiment (GRACE, 2003‐2017) and its Follow‐On mission GRACE‐FO (2018‐now) provide global estimates of the vertically integrated Terrestrial Water Storage Changes (TWSC). Since 2015, the Soil Moisture Active Passive (SMAP) radiometer observes global L‐band brightness temperatures, which are sensitive to near‐surfac...
Article
Full-text available
The retrieval of soil moisture information with spatially and temporally high resolution from Synthetic Aperture Radar (SAR) observations is still a challenge. By using multi-orbit Sentinel-1 C-band time series, we present a novel approach for estimating volumetric soil moisture content for agricultural areas with a temporal resolution of one to tw...
Article
Full-text available
Understanding forest decline under drought pressure is receiving research attention due to the increasing frequency of large-scale heat waves and massive tree mortality events. However, since assessing mortality on the ground is challenging and costly, this study explores the capability of satellite-borne Copernicus Sentinel-1 (S-1) C-band radar da...
Article
Full-text available
Recent research indicates an inverse relation between Synthetic Aperture Radar (SAR) signal and near-surface soil moisture (SM) over very dry sediments, arid to hyper-arid soils resp., caused by subsurface scattering effects. This phenomenon can lead to large errors when it comes to modelling and remote sensing-based estimation of SM. While the eff...
Article
Full-text available
Forests’ ecosystems are an essential part of the global carbon cycle with vast carbon storage potential. These systems are currently under external pressures showing increasing change due to climate change. A better understanding of the biophysical properties of forests is, therefore, of paramount importance for research and monitoring purposes. Wh...
Conference Paper
Soil moisture is a key hydrological variable with great influence on various processes of land-atmosphere interactions, like infiltration or subsurface flow [1]. Depending on the frequency, microwave remote sensing can be used to estimate soil moisture near the surface (~0-5 cm, L-band) [2] or at deeper layers (~20-30 cm, P-band) [3]. However, typi...
Conference Paper
In literature, a variety of models, representations and formalisms exist that describe electromagnetic waves and their interaction with media. The choice of model often depends on the required properties of the electromagnetic wave, e.g. the \textit{degree of polarization} or whether the modeled electromagnetic wave is described coherently (amplitu...
Article
Full-text available
The precise information on fuel characteristics is essential for wildfire modelling and management. Satellite remote sensing can provide accurate and timely measurements of fuel characteristics. However, current estimates of fuel load changes from optical remote sensing are obstructed by seasonal cloud cover that limits their continuous assessments...
Article
Full-text available
A P-band SAR moisture estimation method is introduced for complex soil permittivityand penetration depth estimation using fully polarimetric P-band SAR signals. This methodcombines eigen- and model-based decomposition techniques for separation of the totalbackscattering signal into three scattering components (soil, dihedral, and volume). Theincorp...
Article
Incidence angle diversity of space-borne radiometer and radar systems operating at low microwave frequencies needs to be taken into consideration to accurately estimate soil moisture (SM) across spatial scales. In this study, the single channel algorithm (SCA) is first applied to Soil Moisture and Ocean Salinity (SMOS) brightness temperatures at ve...
Article
Full-text available
Remote sensing (RS) enables a cost-effective, extensive, continuous and standardized monitoring of traits and trait variations of geomorphology and its processes, from the local to the continental scale. To implement and better understand RS techniques and the spectral indicators derived from them in the monitoring of geomorphology, this paper pres...
Article
Full-text available
Deriving soil moisture content (SMC) at the regional scale with different spatial and temporal land cover changes is still a challenge for active and passive remote sensing systems, often coped with machine learning methods. So far, the reference measurements of the data-driven approaches are usually based on point data, which entails a scale gap t...
Article
Full-text available
The vegetation optical depth (VOD) variable contains information on plant water content and biomass. It can be estimated alongside soil moisture from currently operating satellite radiometer missions, such as SMOS (ESA) and SMAP (NASA). The estimation of water fluxes, such as plant water uptake (PWU) and transpiration rate (TR), from these earth sy...
Article
Soil Moisture and Ocean Salinity mapping by Earth observation satellites has contributed significantly toward a better understanding of the Earth system, such as its hydrosphere or climate. Nevertheless, an increased spatial resolution below 10 km with a radiometric resolution in the range of 2 K–3 K of radiometric data could yield a more complete...
Article
Surface soil moisture and vegetation optical depth (VOD), as an indicator of vegetation wet biomass, from passive microwave remote sensing have been increasingly applied in global ecology and climate research. Both soil moisture and VOD are retrieved from satellite brightness temperature measurements assuming a zeroth order radiative transfer model...
Article
The NASA Soil Moisture Active Passive (SMAP) satellite mission aims to produce enhanced resolution surface soil moisture products by combining coincident but multiresolution L-band active and passive microwave measurements. Since the SMAP radar ceased operations early in the mission, Copernicus Sentinel-1 C-band radar observations are used in the c...
Article
Vegetation optical depth (VOD), as a microwave-based vegetation index for vegetation water and biomass content, is increasingly used to study the impact of global climate and environmental changes on vegetation. Currently, VOD is mainly retrieved from passive microwave data and few studies focused on VOD retrievals from active microwave data. The A...
Conference Paper
The attenuation of microwave emissions through the canopy is quantified by the vegetation optical depth (VOD), which is related to the amount of water, the biomass and the structure of vegetation. To provide microwave-derived plant water estimates, one must account for biomass/structure contributions in order to extract the water component from the...
Conference Paper
A method for estimating complex soil permittivity (or moisture) and penetration depth based on SAR decomposition is presented. By combining model- and eigenbased decomposition techniques in a non-iterative way, SAR observations are separated into single scattering components (soil, vegetation). The proposed method incorporates a multilayer rough su...
Conference Paper
Full-text available
In this study, a dense Copernicus Sentinel-1 time series is analyzed to gain a better understanding of the influence of undergrowthvegetation, in particular of eagle fern (Pteridium aquilinum), on the C-band SAR signal in a temperate forest in the Free State ofThuringia, Germany. Even if signals from the ground below the canopy may not be expected...
Article
Full-text available
In this study, a dense Copernicus Sentinel-1 time series is analyzed to gain a better understanding of the influence of undergrowth vegetation, in particular of eagle fern (Pteridium aquilinum), on the C-band SAR signal in a temperate forest in the Free State of Thuringia, Germany. Even if signals from the ground below the canopy may not be expecte...
Article
Full-text available
This study evaluates a temporally dense VV-polarized Sentinel-1 C-band backscatter time series (revisit time of 1.5 days) for wheat fields near Munich (Germany). A dense time series consisting of images from different orbits (varying acquisition) is analyzed, and Radiative Transfer (RT)-based model combinations are adapted and evaluated with the us...
Preprint
Full-text available
The vegetation optical depth (VOD) parameter contains information on plant water content and biomass, and can be estimated alongside soil moisture from currently operating satellite radiometer missions, such as SMOS (ESA) and SMAP (NASA). The estimation of water fluxes, such as plant water uptake (PWU) and transpiration rate (TR), from these Earth...
Article
Full-text available
With the upcoming L-band Synthetic Aperture Radar (SAR) satellite mission Radar Observing System for Europe L-band SAR (ROSE-L) and its integration into existing C-band satellite missions such as Sentinel-1, multi-frequency SAR observations with high temporal and spatial resolution will become available. The SARSense campaign was conducted between...
Conference Paper
The upcoming launch of the L-band Synthetic Aperture Radar (SAR) satellite mission Radar Observing System for Europe L-band SAR (ROSE-L) will enable multi-frequency SAR observations when combined with existing C-band satellite missions (e.g., Sentinel-1). Due to the different penetration depths of the SAR signals, multi-frequency SAR offers great p...
Conference Paper
With the upcoming L-band Synthetic Aperture Radar (SAR) satellite mission Radar Observing System for Europe at L-band (ROSE-L) and its combination with existing C-band satellite missions such as Sentinel-1, multi-frequency SAR observations with high temporal and spatial resolution will become available. To investigate the potential for estimating s...
Preprint
Full-text available
The ESA's SMOS and the NASA's SMAP missions, launched in 2009 and 2015, respectively, are the first two missions having on-board L-band microwave sensors, which are very sensitive to the water content in soils and vegetation. Focusing on the vegetation signal at L-band, we have implemented an inversion approach for SMAP that allows deriving vegetat...
Preprint
Full-text available
In this study the framework of the $\tau$-$\omega$ model is used to derive vegetation loss coefficients and canopy penetration depths from SMAP multi-temporal retrievals of vegetation optical depth, single scattering albedo and ICESat lidar vegetation heights. The vegetation loss coefficients serve as a global indicator of how strong absorption and...
Article
An active–passive microwave retrieval algorithm for simultaneous determination of soil surface roughness parameters [vertical root-mean-square (RMS) height ( ${s}$ ) and horizontal correlation length ( ${l}$ )] is presented for bare soils. The algorithm is based on active–passive microwave covariation, including the improved Integral Equation Met...
Article
Full-text available
Climate variability and change along with anthropogenic water use have affected the (re)distribution of water storage and fluxes across the Contiguous United States (CONUS). Available hydrological models, however, do not represent recent changes in the water cycle. Therefore, in this study, a novel Bayesian Markov Chain Monte Carlo-based Data Assim...
Conference Paper
Soil moisture and ocean salinity mapping by earth observation satellites has contributed significantly towards a better understanding of the earth’s climate and hydrosphere. Nevertheless, an increased spatial resolution of radiometric data could yield a more complete picture of global hydrological and climate processes. High-resolution radiometers,...
Article
Full-text available
The status, changes, and disturbances in geomorphological regimes can be regarded as controlling and regulating factors for biodiversity. Therefore, monitoring geomorphology at local, regional, and global scales is not only necessary to conserve geodiversity, but also to preserve biodiversity, as well as to improve biodiversity conservation and eco...
Article
Full-text available
An accurate radiative transfer model (RTM) is essential for the retrieval of soil moisture (SM) from microwave remote sensing data, such as the passive microwave measurements from the Soil Moisture Active Passive (SMAP) mission. This mission delivers soil moisture products based upon L-band brightness temperature data, via retrieval algorithms for...
Article
Full-text available
With new Earth Observation (EO) and Geoinformation (GI) data sources increasingly becoming available, evermore new skills for data collection, processing, analysis and application are required. They are needed not only from scientists, but also from practitioners working in businesses, public and private EO*GI and related sectors. Aligning the cont...
Article
The estimation of soil permittivity under fully covered grassland is a challenging task that can be approached by either model-based polarimetric decomposition techniques or data-driven machine-learning (ML) methods. In this study, we test the benefits and limitations of those techniques when individually or jointly applied to estimate the permitti...