Wageningen UR BSc and MSc Project Database

BSc-MSc Thesis and Internship Projects, Wageningen University

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Uncertain data: Probability distribution of soil properties in selected regions of the United States
Information on the probability distribution and variability of soil properties in a region can help to gain understanding of the soil�s current state. Generally, the normal distribution is adopted to represent possible values of s ...
Supervisor: Cynthia van Leeuwen (SGL WUR / ISRIC) and Titia Mulder (SGL WUR)
Department: Soil Geography and Landscape

Constraining peat initiation by OSL-dating the pre-peat landscape
Large parts of the Pleistocene sand landscape in the Netherlands were once covered with peat. Most of these organic deposits were lost during peat reclamation and excavation during the past centuries. Many questions regarding the ...
Supervisor: Cindy Quik (SGL) and Jakob Wallinga (SGL, examinor)
Department: Soil Geography and Landscape

Digital Soil Mapping: model prediction using sampling from national maps to feed into a trans-national model
This project will explore methods to overcome borders effect for maps between countries. The project will explore how information from different national maps can be integrated among countries and with continental/global informati ...
Supervisor: Titia Mulder (SGL WUR) and Laura Poggio (ISRIC)
Department: Soil Geography and Landscape

Digital Soil Mapping: test and develop methods to (visually) communicate uncertainty
Uncertainty is important for modelers and scientific community. However it is not easy to communicate to stakeholders. This project will explore mathematical indices to summarize uncertainty but also visualization techniques to ma ...
Supervisor: Titia Mulder (SGL WUR) and Laura Poggio (ISRIC)
Department: Soil Geography and Landscape

Remote Sensing: Using the EM signature of the Earth surface for DSM
Remote and proximal sensing data are frequently used for predicting and mapping soil properties. Typically, the spectral bands are being used individually as predictors in statistical models to predict soil properties. However, th ...
Supervisor: Titia Mulder (SGL WUR) and Laura Poggio (ISRIC)
Department: Soil Geography and Landscape

Remote Sensing: Review and implement RS indices used in different DSM studies and other disciplines
This project will aim to explore and produce a stack of satellite information data that can be used for Digital soil mapping. In particular, a review of the existing indices will be carried out. The most promising indices will be ...
Supervisor: Titia Mulder (SGL WUR) and Laura Poggio (ISRIC)
Department: Soil Geography and Landscape

Spectral libraries: Comparison of MIR and NIR sensors
In this research you will compare the predictability of some key soil properties from both NIR and MIR sensors, with focus on the associated uncertainty, costs, time, repeatability. The outcome will highly depend on the instrument ...
Supervisor: Titia Mulder (SGL WUR) and Fenny van Egmond (ISRIC/WENR)
Department: Soil Geography and Landscape

Spectral libraries: Impact of sample preparation on MIR measurements and model predictions
Sample preparation is key to obtain accurate MIR measurements in the laboratory. Unfortunately, little is known about which protocol to follow and what the effect of sample preparation is on the accuracy and precision of derived s ...
Supervisor: Titia Mulder (SGL WUR) and Fenny van Egmond (ISRIC/WENR)
Department: Soil Geography and Landscape

Proximal sensing: Test (VIS-NIR) penetrologger for soil moisture and soil texture estimates
A new sensor has been developed by Cranfield Univeristy to simulataneously measure the penetration resistance and the VNIR signal of the soil profile. In this research you will use this sensor and test the suitability to predict v ...
Supervisor: Titia Mulder (SGL WUR) and Fenny van Egmond (WENR)
Department: Soil Geography and Landscape

Uncertain data: The impact of environmental and land use data on soil formation in the Netherlands: A temporal analysis (1960 - present)
Spatial soil data are among the top five types of data used by the Dutch government. Digital soil mapping (DSM) requires large sets of spatial data from variables such as climate, land use and management, relief and geology. Howev ...
Supervisor: Anatol Helfenstein (SGL WUR) and Titia Mulder (SGL WUR)
Department: Soil Geography and Landscape

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