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Thorsten Behrens

Thorsten Behrens
KOBO | Soilution

Dr. rer. nat. Dipl.-Ing. arg.
Integrating spatio-temporal contextual modeling with spectroscopy and field pedology for a new generation of soil maps

About

110
Publications
52,833
Reads
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4,879
Citations
Introduction
I am a soil and data scientist focusing on spatial contextual modeling, pedology, interpretable machine learning, and spectroscopy.
Additional affiliations
January 2019 - December 2019
University of Tuebingen
Position
  • Senior Researcher
August 2018 - December 2018
University of Tuebingen
Position
  • Senior Researcher
June 2012 - July 2018
University of Tuebingen
Position
  • Principal Investigator
Description
  • DFG Pedoscale project
Education
January 2001 - December 2004
Justus-Liebig-Universität Gießen
Field of study
  • Soil science, Geographic information science, Geomorphology, Digital terrain analysis
April 1994 - December 1999
Justus-Liebig-Universität Gießen
Field of study
  • Agricultural science and environmental protection, Soil science

Publications

Publications (110)
Article
Full-text available
We compared different methods of multi-scale terrain feature construction and their relative effectiveness for digital soil mapping with a Deep Learning algorithm. The most common approach for multi-scale feature construction in DSM is to filter terrain attributes based on different neighborhood sizes, however results can be difficult to interpret...
Article
Full-text available
Soil organic carbon (C) is an essential component of the global C cycle. Processes that control its composition and dynamics over large scales are not well understood. Thus, our understanding of C cycling is incomplete, which makes it difficult to predict C gains and losses due to changes in climate, land use and management. Here we show that contr...
Article
Full-text available
Two important theories in spatial modelling relate to structural and spatial dependence. Structural dependence refers to environmental state-factor models, where an environmental property is modelled as a function of the states and interactions of environmental predictors, such as climate, parent material or relief. Commonly, the functions are regr...
Article
Full-text available
The recent article in this journal by McBride, under the heading ‘Opinion’, criticized reflectance spectroscopy for estimating the concentrations of soil constituents. Some of that criticism is fair; many exponents have exaggerated claims about the technology. Other aspects of McBride's opinion are outdated, incorrect or otherwise misleading. We co...
Article
Full-text available
Soil visible-near infrared (vis–NIR) spectra are complex and modeling soil properties can be challenging. They can suffer from additive and multiplicative noise, they are hyper-dimensional and highly collinear, making their analyses and interpretation sometimes difficult. Here, we introduce the Gaussian pyramid scale space as a multi-resolution app...
Article
Full-text available
Multi-scale contextual modelling is an important toolset for environmental mapping. It accounts for spatial dependence by using covariates on multiple spatial scales and incorporates spatial context and structural dependence to environmental properties into machine learning models. For spatial soil modelling, three relevant scales or ranges of scal...
Article
Soil fungi are vital for ecosystem functioning, but an understanding of their ecology is still growing. A better appreciation of their ecological preferences and the controls on the composition and distribution of fungal communities at macroecological scales is needed. Here, we used one of the most extensive continental-scale datasets on soil fungi...
Article
Full-text available
There is global interest in spectroscopy and the development of large and diverse soil spectral libraries (SSL) to model soil organic carbon (SOC) and monitor, report, and verify (MRV) its changes. The reason is that increasing SOC can improve food production and mitigate climate change. However, 'global' modelling of SOC with such diverse and hype...
Article
Full-text available
We need measurements of soil water retention (SWR) and available water capacity (AWC) to assess and model soil functions, but methods are time‐consuming and expensive. Our aim here was to investigate the modelling of AWC and SWR with visible–near‐infrared spectra (vis–NIR) and the machine‐learning method cubist. We used soils from 54 locations acro...
Article
The low potential of agricultural productivity in the majority of central Iran is mainly attributed to high levels of soil salinity. To increase agricultural productivity, while preventing any further salinization, and implement effective soil reclamation programs, precise information about the spatial patterns and magnitude of soil salinity is ess...
Presentation
Area-wide high resolution information of organic layer properties is required for assessing the current nutrient availability in forest stands. Together with climate, location, parent material and terrain predictors, vegetation is known to have a direct impact on the characteristics of the organic surface layer of forest soils and therefore plays a...
Conference Paper
Full-text available
In this study, we predicted and mapped soil salinity using machine learning (ML) and digital soil mapping (DSM) approaches. Support vector regression (SVR) and the hybrid of SVR with wavelet transformation (W-SVR) where applied to correlate soil salinity of the upper 200 cm of soil to a wide range of environmental covariates derived from a digital...
Article
Full-text available
Abstract: Understanding the spatial distribution of soil organic carbon (SOC) content over different climatic regions will enhance our knowledge of carbon gains and losses due to climatic change. However, little is known about the SOC content in the contrasting arid and sub-humid regions of Iran, whose complex SOC–landscape relationships pose a cha...
Article
Full-text available
Most common machine learning (ML) algorithms usually work well on balanced training sets, i.e. data sets in which all classes are approximately represented equally. Otherwise, the accuracy estimates may be unreliable and classes with only a few values are often misclassified or neglected. This is known as class imbalance problem in machine learning...
Article
Full-text available
Soil organic C (SOC) and soil moisture (SM) affect the agricultural productivity of soils. For sustainable food production, knowledge of the horizontal as well as vertical variability of SOC and SM at field scale is crucial. Machine learning models using depth‐related data from multiple electromagnetic induction (EMI) sensors and a gamma‐ray spectr...
Article
Full-text available
Spatial autocorrelation in the residuals of spatial environmental models can be due to missing covariate information. In many cases, this spatial autocorrelation can be accounted for by using covariates from multiple scales. Here, we propose a data-driven, objective and systematic method for deriving the relevant range of scales, with distinct uppe...
Presentation
Full-text available
Die praxisnahe Darstellung von Zustands- bzw. Humuseigenschaften in Karten ist Verfahrensbestandteil der Forstlichen Standortskartierung in den ostdeutschen Bundesländern. Dabei ist die Humusform bodenchemisch über pH-Wert, C/N-Verhältnis und Basensättigung in der Humusauflage und der obersten Mineralbodenschicht definiert. Während im nordostdeutsc...
Article
Full-text available
As limited resources, soils are the largest terrestrial sinks of organic carbon. In this respect, 3D modelling of soil organic carbon (SOC) offers substantial improvements in the understanding and assessment of the spatial distribution of SOC stocks. Previous three-dimensional SOC modelling approaches usually averaged each depth increment for multi...
Article
In pedology, spatial context is relevant to soil-landscape systems on at least three different scales: i) the scale of quasi-local processes, which are independent of influence from the direct or wider neighborhood, ii) the scale of short-range processes for example on the local hillslope or catena, and iii) the scale of long-range processes, or te...
Conference Paper
Full-text available
Neben der klassischen Standortskartierung nach dem ostdeutschen Verfahren werden in Sachsen seit mehreren Jahren Methoden des Digital Soil Mapping angewendet. Einen Schwerpunkt bildet die kontinuierliche Aufarbeitung von Altdaten. Deren Georeferenzierung, Harmonisierung und Verfügbarmachung erfolgt sowohl in modernen Dokument-Management-Systemen au...
Article
Soil bacteria play a critical role in the functioning of ecosystems but are challenging to investigate. We developed state-factor models with machine learning to understand better and to predict the abundance of 10 dominant phyla and bacterial diversities in Australian soils, the latter expressed by the Chao and Shannon indices. In the models, we u...
Article
Full-text available
Biodiversity experiments have shown that species loss reduces ecosystem functioning in grassland. To test whether this result can be extrapolated to forests, the main contributors to terrestrial primary productivity, requires large-scale experiments.We manipulated tree species richness by planting more than 150,000 trees in plots with 1 to 16 speci...
Article
This study introduces a hybrid spatial modelling framework, which accounts for spatial non‐stationarity, spatial autocorrelation and environmental correlation. A set of geographic spatially autocorrelated Euclidean distance fields (EDF) was used to provide additional spatially relevant predictors to the environmental covariates commonly used for ma...
Article
Full-text available
Predicting taxonomic classes can be challenging with dataset subject to substantial irregularities due to the involvement of many surveyors. A data pruning approach was used in the present study to reduce such source errors by exploring whether different data pruning methods, which result in different subsets of a major reference soil groups (RS...
Article
We present a contextual spatial modelling (CSM) framework, as a methodology for multiscale, hierarchical mapping and analysis. The aim is to propose and evaluate a practical method that can account for the complex interactions of environmental covariates across multiple scales and their influence on soil formation. Here we derived common terrain at...
Article
Traditional soil maps have helped us to better understand soil, to form our concepts and to teach and transfer our ideas about it, and so they have been used for many purposes. Although, soil maps are available in many countries, there is a need for them to be updated because they are often deficient in that their spatial delineations and their des...
Preprint
Forest ecosystems contribute substantially to global terrestrial primary productivity and climate regulation, but, in contrast to grasslands, experimental evidence for a positive biodiversity-productivity relationship in highly diverse forests is still lacking ¹ . Here, we provide such evidence from a large forest biodiversity experiment with a nov...
Article
Most calibration sampling designs for Digital Soil Mapping (DSM) demarcate spatially distinct sample sites. In practical applications major challenges are often limited field accessibility and the question on how to integrate legacy soil samples to cope with usually scarce resources for field sampling and laboratory analysis. The study focuses on t...
Article
Full-text available
Soil provides ecosystem services, supports human health and habitation, stores carbon and regulates emissions of greenhouse gases. Unprecedented pressures on soil from degradation and urbanization are threatening agro- ecological balances and food security. It is important that we learn more about soil to sustainably manage and preserve it for futu...
Article
Full-text available
Soil provides ecosystem services, supports human health and habitation, stores carbon and regulates emissions of greenhouse gases. Unprecedented pressures on soil from degradation and urbanization are threatening agro-ecological balances and food security. It is important that we learn more about soil to sustainably manage and preserve it for futur...
Article
Full-text available
Large dam projects attract worldwide scientific attention due to their environmental impacts and socioeconomic consequences. One prominent example is the Three Gorges Dam (TGD) at the Yangtze River in China. Due to considerable resettlements, large-scale expansion of infrastructure and shifts in land use and management, the TGD project has irrevers...
Article
Full-text available
Recent advances in wireless sensor technology allow monitoring of soil moisture dynamics with high temporal resolution at varying spatial scales. The objectives of this study were to: i) develop an efficient strategy for monitoring soil moisture dynamics at the hillslope scale using a wireless sensor network; ii) characterize spatial patterns of so...
Article
Existing predictive soil mapping (PSM) methods often require soil sample data to be sufficient to represent soil–environment relationships throughout the study area. However, in many parts of the world with only a limited quantity of soil sample data to represent the study area, this is still an issue for PSM application. This paper presents a meth...
Article
Recent advances in wireless sensor technology allow monitoring of soil moisture dynamics with high temporal resolution at varying spatial scales. The objectives of this study were to: (i) develop an efficient strategy for monitoring soil moisture dynamics at the hillslope scale using a wireless sensor network; and (ii) characterize spatial patterns...
Article
High-resolution digital soil sensing and mapping is an important and emerging new technology that helps meet the strong and growing global demand for high-resolution soil property data. However, the combination of geophysical sensing and pedometrical techniques to produce soil property maps is complex and requires a well-structured design, from the...
Article
Full-text available
Due to resettlements, construction of new infrastructure, and new land reclamation the rapid agricultural changes in the Three Georges Area (TGA) in Central China are expected to force the degradation of the cultivated terraced landscape. Consequently, increased soil erosion can hamper a sustainable land management in the mountainous TGA. This pape...
Conference Paper
Full-text available
The Three Gorges Dam at the Yangtze River in Central China outlines a prominent example of human-induced environmental impacts. Throughout one year the water table at the main river fluctuates about 30m due to impoundment and drainage activities. The dynamic water table implicates a range of georisks such as soil erosion, mass movements, sediment t...
Article
Full-text available
Knowledge of soil water dynamics at the field scale is an important issue e.g. for water management, understanding runoff generation processes, and for calibration and validation of soil water balance models. There is a clear need for robust and flexible monitoring technologies which are able to capture high-resolution information over large areas....
Article
Recent advances in digital soil mapping, soil sensing and machine learning methods represent a great potential to produce (spatially) dense SOC information in a cost-effective way. However there is lack of research on the integration of soil sensing and digital soil mapping techniques for three dimensional monitoring of SOC at the regional scale. I...
Article
Full-text available
In densely populated countries like China, clean water is one of the most challenging issues of prospective politics and environmental planning. Water pollution and eutrophication by excessive input of nitrogen and phosphorous from nonpoint sources is mostly linked to soil erosion from agricultural land. In order to prevent such water pollution by...