Overview MSc Research Topics
Protected areas are useful governance tool to mitigate biodiversity loss and preserve threatened habitats and species.
Global production, transportation, and consumption of oil can cause inevitable spills into the environment (typically from pipelines, oil wells, and storage facilities) cont
Accurate measurements of solar irradiance (incoming sunlight) and radiance (light coming from a specific direction) are fundamental in Earth Observation (EO).
The rapid pace of urbanization underscores the need for stakeholders in sustainable development to view cities and their surrounding regions as interconnected systems rather than
This MSc topic develops a typology of Dutch regions that captures how remote work affects their spatial, economic and social characteristics (Extending Task 2.3 of R-Map1).
Grid-based travel friction grids represent travel cost for moving through each cell of a landscape, enabling flexible and spatially detailed travel-time calculations.
Generative AI and Digital Twins (DTs) are redefining how urban environments are conceptualized, designed, and managed.
For years, MODIS images have been instrumental in divers environmental and ecological studies such as monitoring deforestation, land-us/land-cover (LULC) changes, agriculture and epidemiology.
Green spaces are fundamental for the well-being of individuals and communities as they provide areas for recreation, which is essential for the quality of life in cities.
Urban slums are among the most vulnerable environments in terms of food access, dietary adequacy, and livelihood stability.
Natural hazards increasingly occur not as isolated events but as multiple, interacting phenomena (e.g., earthquakes followed by landslides, or compound flooding driven by storm surge and extreme ra
This study aims to investigate the environmental impacts of armed conflict in West Darfur, Sudan, with a particular focus on vegetation dynamics.
The decisions made on the spatial configurations and distributions in the built environments (urban or rural developments) directly affect the environment as well as the interests of various actors
Generative AI software development tools like Bolt.new enable the fast, efficient, and easy build of all kinds of web services and platforms.
Rainfall data series from climate models (i.e.
One of the greatest challenges in scientific research is bridging the gap of technical knowledge and practical solutions for communties.
Northern Kenya’s dryland ecosystems are socio-ecologically complex landscapes where vegetation, water availability and livestock mobility interact to support pastoral livelihoods.
The Antarctic ice sheet covers almost the whole area of the Antarctic continent. It is the largest ice mass on Earth, with an average ice thickness of about 2 kilometers [1].
Interest in the formal representation of citizen science comes from portals, platforms, and catalogues of citizen science projects; scientists using citizen science data for their research; and fun
This study examines soil health as a key indicator of rangeland restoration success in the semi-arid ecosystems of Samburu County.
LAI is one of the most critical vegetation biophysical variables as well as remote sensing- enabled essential biodiversity variables due to the controlling role of green leaves in biological and ph
In many rapidly growing cities across Sub-Saharan Africa, residents – especially those living in informal settlements – face multiple challenges from limited access to safe and r
More and more cities are developing digital twins of their critical public infrastructures.
Ethiopia’s diverse agricultural landscape is crucial to its economy and food security.
Based on research and consultation, a prototype of a project dashboard for healthcare will be developed and tested.
The presence of noises, clouds and another atmospheric phenomena represent an obstacle for optical remote sensing applications.
Brazil is the biggest coffee productors in the world, with millions of hectares of plantations.
Estimating aboveground biomass is essential for generating vegetation inventories and understanding carbon cycles.
An accurate method for automatically mapping deforested areas constitute an important tool to inform and enable deforestation containment policies.
The climate in cities and metropolitan areas (i.e., urban climate) is often different from the climate in the surrounding rural areas due to the presence of buildings, pavement, a
Mapping and monitoring slums is essential to ensure the sustainable development of the cities to ensure a quality of life for people.
To model air pollution in urban environments while accounting for urban forms using convolutional neural networks (CNN) or Vision Transformers (ViT), open access earth observation
Deep Neural Networks (DNN) is considered as a panacea for different problems in several application areas. But what about spatial modeling?
The goal of this study is to detect and map bark beetle infestation in a temperate forest in Germany using DESIS hyperspectral satellite data.
The goal of this study, as part of the larger BIOSPACE project, is to map and model foliar pigments, including chlorophyll and carotenoids and thei
Forest health worldwide is under pressure as a result of prolonged droughts.
In recent years, the Greater Horn of Africa has suffered from prolonged droughts, associated with forced migration and food and water security issues.
The challenge of this topic is to detect a change or trend on top of seasonal fluctuations.
Vietnam is one of the most disaster-prone countries in Southeast Asia, facing increasing pressure from natural hazards.
Clouds usually represent a big problem for optical remote sensing. A wide range of works have been developed in producing efficient cloud detection algorithms.
Digital Twins (DTs) are rapidly becoming one of the most exciting innovations in smart cities, bringing together 3D modelling, geospatial data, IoT sensors, and AI t
Nepal is highly vulnerable to natural hazards such as earthquakes, landslide and floods.
Urban systems consist of multiple interrelated components, including physical and social structures, among them people, organizations,
Drought has wreaked havoc to human societies throughout history. Drought is usually caused by a multitude of factors starting from the deficit of precipitation when compared to climatic mean.
ET is the water lost to the atmosphere through plant stomata during photosynthesis and from the surface following a we
Understanding the types of vegetation that composes the land cover on non-anthropic areas and the land use for anthropic areas is essential to understand ecosystems dynamic
Unsafe houses and natural hazards are increasingly common threats for citizens of low-income countries.
The past decades have seen rapid advancements in space-based monitoring of essential water cycle variables, providing products related to precipitation, evapotranspiration, and so
Anticipatory actions (AAs) are pre-emptive measures taken to mitigate the impacts of disasters based on forecasted hazards.
Mediterranean and temperate forests are being affected by intense and frequent droughts that will become more frequent and s
Urban environmental planning and management, both in theory and practice, have indicated the need for participatory inclusivity as much as possible.
In many parts of the world, agricultural monitoring is hindered by limited field data, inconsistent surveys, and highly heterogeneous landscapes.
Thermal remote sensing is a type of passive remote sensing since that detects naturally emitted radiation. Most thermal remote sensing for vegetation conducted in the 8-14 μm wavelengths.
UN-Habitat estimates that over one billion people around the world live in slums, which are often located in hazard-prone areas.
Geothermal systems are one of the sustainable sources of our future energy mix.
Forest health worldwide is increasingly deteriorated by droughts.
With down-looking satellite sensors, our three-dimensional (3D) world is commonly represented with 2D remote sensing images.
Beavers are often referred to as “ecosystem engineers” because their dam-building activity reshapes river corridors, alters local hydrology, and creates mosaics of ponds, wetland
Training a geospatial AI model is like setting up a game—the rules you choose for sampling data determine who wins and who loses.
Deep learning algorithms can achieve great accuracies, but there are also concerns about biases and generalizability to unseen data.
Generative AI has been used in many applications such as text generation and image generation such as (chatgpt, dall-e etc.) but can they generate realistic hazard scenario
Generative Design is an umbrella term for a variety of approaches to the derivation of topological-geometric configurations directly from the design requirements and goals in a feedforward process
Global prediction of anemia, stunting, and wasting using household surveys and geospatial covariates
This MSc project aims to generate high-resolution global maps of anemia, stunting, and wasting by combining biomarker and anthropometric data from DHS/MICS with globally consistent environmental, a
Heat hazard, in the form of heat waves principally affecting larger urban areas, has evolved into one of the most deadly hazard types, especially in the Global North that tends to se
Timely and accurate data on the extent of croplands and the types of cultivated crops are essential to addressing the food insecurity challenges that many African countries face.
Climate change leads to a increased frequency of extreme precipitation and prolonged drought period, both of which have a severe impact on the landslide initiation as they
Deep learning algorithms have gained increasing popularity in remote sensing due to their accuracy.
Individuals and the organisations in which they work need to cooperate in projects and research to withstand an increasing competition.
In close collaboration with colleagues from the University of Kwazulu Natal, we can offer a series of MSc research topics related to humanitarian and urban development related to
This thesis topic want to explore how the design of public spaces can facilitate social interaction, and how ICTs can be used to inform this design.
Identifying Socio-Spatial Potentials to Improve Liveability Using Street Network Centrality Analysis
In a time when wicked problems, such as biodiversity loss, climate breakdown, the housing crisis, and eroding social solidarity, are escalating, it is becoming increasingly impor
Improved quality of life is one of the New Urban Agenda (NUA) underlined sectors to be incorporated "in every urban development or renewal policy and strategy" (UN-Habitat, 2017).
The arid and semi-arid lands (ASALs) of northern Kenya face pressing challenges due to climate change, environmental degradation, and socio-economic vulner
Natural hazards such as earthquakes, floods, and landslides pose a persistent threat to the built environment, causing large economic losses and loss of life worldwide.
In the realm of artificial intelligence (AI), the advancement of large language models (LLM) like GPT-4, the base model of ChatGPT, has revolutionized natural language processing.
The estimation of canopy height, AGB and its changes is typically carried out using active Remote Sensing data such as LIDAR or Interferometric Synthetic Aperture Radars (InSAR)
Impervious surfaces are the Earth’s surfaces covered with mainly anthropogenic and artificial structures, such as built-up areas, roads and streets, and parking lots.
This project is part of a 2 year EU MSCA project.
A workflow is considered to be a combination of data and (software) operations.
Mediterranean thermophilous pines, which are the key, dominant, and characteristic species of this habitat, form some of the most drought-resilient woodlands in Europe.
Urban slum is often vulnerable to environmental changes such as subsidence, as it has densely populated informal settlements
Sufficient nutrition remains a major challenge for rural households in the Sub-saharan region of Africa.
The arid and semi-arid Lands (ASALs) of northern Kenya are characterized by extremes of poverty and climate.
Crop nutrient concentrations result from the interactions between soil fertility, plant nutrient uptake, and crop growth.
As a result of hardware miniaturization and ubiquitous internet access, there is a wealth of user- and sensor-generated geographic content available, from social media activity to private weather s
Humanitarian organizations such as the Red Cross Red Crecent and Unicef use risk models to identify vulnerable populations and mitigate the affects of natural disasters.
Aflatoxin contamination in grains is a significant health risk to humans and livestock as it causes human cancer, liver cirrhosis, stunting in children, and death.
Recently, mortality and reduction in forest stand densities for Brutia pine (Pinus brutia) have been found ov
Crop mapping plays an important role in agronomic planning and management both for farmers and policymakers. Satellite remote sensing sensors have become efficient tools for mapping croplands.
The rate of carbon uptake by vegetation is not fully known.
Measurement of the effect of regreening efforts can be done by using an index for the amount of green vegetation, and a measure of recovery.
Food insecurity is a big issue in eastern and southern Africa and projections are that this is going to get worse with climate change and variability.
Forests are among the most diverse ecosystems on our planet.
LINK TO RESEARCH PROJECTS
The MSc topics link to several ongoing larger research projects that allow being part of international research teams - both projects just started:
Monitoring forest dynamics is essential for identifying the area most at risk for forest degradation and deforestation, and
Coral reefs are vital ecosystems that provide ecological, economic, and cultural benefits—but they are under growing pressure from land-use change and marine tourism.
A wide range of topics are available (See below).
In order to be able to design appropriate risk reduction measures to reduce the increasing impact of multi-hazard events, it is important to have tools to estimate the losses of these compounding e
Understanding how crops and grasslands respond to drought and weather extremes requires observations at multiple scales.
Objective
To develop a deep learning model to estimate the timing of phenological events over large area
“Nature-based solutions” (NBS) or “building with nature” have received global attention as a multidimensional approach to reduce impacts of climate change and associated meteorological disaster ris
South-Limburg suffers from plvial floods ad flash floods occasionally. The last floods in 2021 caused immense damage in the river Geul.
Spatial autocorrelation is a property of any dataset that is linked to locations. So both raster and vector data have this property.
Behind the many different data sources available to innovate geospatial technologies and methodologies are large data infrastructures needed to produce and process geospatial data.
Urban heat stress is one of the most pressing climate risks in the Netherlands, with strong impacts on public health, infrastructure, and energy demand.
So far, more than 6.5 million people have died from COVID-19, and still, there are around 1000 deaths per day.
Food packaging is responsible for 5.4% of global food systems emissions in 2015 (Crippa et al., 2021).
Remote work is reshaping where people live, work and travel, with uneven impacts across the urban–rural continuum.
Nowdays, wildfire is one of the most important environmental problems in the world, affecting a wide range
As an essential part of food security, diet diversity often requires frequent household food security surveys to monitor.
Farmers, agronomists, private enterprise and policy-makers need to know field conditions with sufficient early-warning.
In cities, temperatures are often higher than in the surrounding areas and can also vary locally.
As a result of hardware miniaturization and ubiquitous internet access, there is a wealth of user- and sensor-generated geographic content available, from social media activity to private weather s
The goal of this study, as part of the larger BIOSPACE project, is to map and model leaf and canopy nitrogen content and their spatial variations in a bor
The goal of this study, as part of the larger BIOSPACE project, is to map and model Specific Leaf Area (SLA) and its spatial variation in a boreal forest
New and affordable sensors (e.g., Arduino Nano 33 BLE Sense, Sensebox) have greatly increased the potential to collect finer-grained environmental information, especially on topics impacting on hum
Recent research has shown that, in European cities, the quality of adaptation planning has improved over the last approximately 15 years; however, the focus on justice and vulnerability in climate
HANPP estimates the actual biomass production (Net Primary Productivity or NPP) following anthropogenic intervention.
Remote work is transforming mobility needs in knowledge regions such as Twente, where universities and high-tech firms attract workers and students from both the Netherlands and
About 75% of the Earth’s land surface has been altered and land use change has affected more than 30% of global
In many countries, shortage of drinking water is a problem.
To inform policymakers about the agricultural landscapes and food production, accurate and timely monitoring of crop type is required.
Primary production is the growth or accumulated rate of biomass in plants.
Mapping slums in different urban environments across the Globe is extremely important for locating and prioritizing hotspots of urban poor for urgent climate action to combat the impact of cl
This is a broad thesis topic that aims to develop additional data to support the characterizatio
Food packaging is responsible for 5.4% of global food systems emissions in 2015 (Crippa et al., 2021).
Understanding how soil moisture and groundwater systems respond to climate variability and extreme weather is crucial for drought management, water resources planning, and climat
The accurate prediction of crop yields is a critical element in ensuring global food security, managing agricultural markets and supporting the decision-making processes of farmers and
For a skyscraper to be stable, it must be built on a strong foundation. However, several factors such as persistent use, aging and deterioration, etc.
The growing public health concerns about ambient air quality such as particulate matter (PM) concentrations suggest the need for a holistic monitoring to guide interventions.
The new Surface Water and Ocean Topography (SWOT) satellite, launched in December 2022, aims to map Earth's water in unprecedented detail to help manage climate change and to shar
Geo-referenced time series are data describing the time-changing behavior of one or more attributes at fixed locations and consistent time intervals [1].
The goal of sustainable transport is to promote better and healthier ways for individuals and communities to meet their travel needs while reducing the negative social, environmental and economic i
A huge task is waiting to realize the global agenda in relation to tenure security as recognized by the sustainable development goals (SDGs) set by the UN.
Thermal remote sensing is a type of passive remote sensing that detects naturally emitted radiation.
The world’s human population has been tripled during the past 70 years, from 2.5 billion in 1950 to 7.7 billion now (UN-Habitat).
The livelihoods of many people in the East African drylands heavily depend on livestock.
Bark beetle outbreaks have transformed large areas of Central European spruce forests, including the Bavarian Forest National Park.
Environmental data is often rich and complex.
Vegetation is currently scarce on Greenland, and does not occur on the ice-sheet, as it grows around the edges.
Although large language models (LLM) have been around for a while, the public release of ChatGPT demonstrated a quantum leap in the abilities of these models to respond to natural
The economic and humanitarian impacts of tropical cyclones across the small island developing states (SIDS) in the Caribbean are very high; and greater than those of larger mainland cou
GLOFAS is an ensemble of 3 components: A Metrological Model and Forecast (Numerical Weather Prediction (NWP) forecasts of the ECMWF IFS), A hydrological model (LISFLOOD) and a web
Smallholder farming systems in Sub-Saharan Africa frequently involve intercropping, where multiple crops are grown together on the same parcel.
The fusion of UAV-based and satellite-based data has emerged as a powerful approach for plant health monitoring in agriculture.
Drones or UAVs are revolutionizing conservation and agricultural practices, offering cost-effective and safe methods for data collection over large, challe
How much could we know about cities by only inspecting their physical forms?
Droughts are exacerbated by climate change, which makes them more frequent, prolonged, and catastrophic.
The droughts of 2018-2020 in the Netherlands created great social distress, induced huge economic damages in agricultural production, disrupted river navigation and damaged buildi
Population growth around volcanoes exposes millions of people worldwide to the risks of volcanic activity.
Climate change is nowadays prominently present on the political and thus scientific agenda, which is reflected in the Dutch Delta-Programme for Spatial Adaptation (“Delta-Programma Ruimtelijke Adap
On 6 February 2023 a magnitude 7.8 earthquake affected the border region between Türkiye and Syria, killing an estimated 55,000 people and causing damage to more than 4 mil
To develop a model to estimate the timing of phenological events over large areas from time series of earth observation data using vision transformers, a fierce alternative to tra
Water level in lakes and rivers is a critical parameter to monitor for water managers. It captures the state of surface waters, and, if placed strategically, can be used in e.g.
Aside from flooding, agricultural areas in flat terrain suffer from seasonal water logging after excessive precipitation.