Sebastian van der Linden

University of Greifswald · Department of Geography and Geology

Peatlands contribute to a wide range of ecosystem services. They play an important role as carbon sinks in their natural state, but when they are drained, they cause carbon emissions. Rewetting drained peatlands is required to reduce carbon emissions and create new carbon sinks. However, drained peatlands are commonly used as grassland or croplands...

Built structures increasingly dominate the Earth’s landscapes; their surging mass is currently overtaking global biomass. We here assess built structures in the conterminous US by quantifying the mass of 14 stock-building materials in eight building types and nine types of mobility infrastructures. Our high-resolution maps reveal that built structu...

Detailed maps on the spatial and temporal distribution of crops are key for a better understanding of agricultural practices and for food security management. Multi-temporal remote sensing data and deep learning (DL) have been extensively studied for deriving accurate crop maps. However, strategies to solve the problem of transferring crop classifi...

Monitoring the Earth by annually mapping land cover (LC) fractions helps to better understand the ongoing processes and changes of land use and land management. At 10 to 30 m spatial resolution, the combination of time-series data aggregation, specifically spectral-temporal metrics (STM), and regression-based unmixing models has been shown to be hi...

Peatland degradation causes a number of environmental problems ranging from greenhouse gas (GHG) emissions to subsidence and ecosystem loss. Degraded peatlands, covering just 0.3 % of Earth's land area (500,000 km²), disproportionately contribute 5 % of GHG emissions, exacerbating the climate crisis. Once degraded, restoring peatland ecosystem func...

We present detailed annual land cover maps for the Baltic Sea region, spanning more than two decades (2000–2022). The maps provide information on eighteen land cover (LC) classes, including eight general LC types, eight major crop types and grassland, and two peat bog-related classes. Our maps represent the first homogenized annual dataset for the...

Mapping land cover in highly heterogeneous landscapes is challenging, and classifications have inherent limitations where the spatial resolution of remotely sensed data exceeds the size of small objects. For example, classifications based on 30-m Landsat data do not capture urban or other heterogeneous environments well. This limitation may be over...

While mapping peatlands worldwide remains an important task, capturing their status using earth observation technologies has received less attention. Approximately 500,000 km² of degraded peatland worldwide contribute an excessive 5% of global greenhouse gas emissions. Most human use of peatlands remains unsustainable and can disrupt the balance of...

Functioning Peatlands are important carbon sinks that play a crucial role in mitigating climate change. However, the degradation of peatlands has become a major environmental issue worldwide, resulting in the loss of their carbon storage potential. In Germany, of the estimated 14.800 km² of peatland, approximately 95 % have been disturbed and conve...

High-resolution maps of material stocks in buildings and infrastructures are of key importance for studies of societal resource use (social metabolism, circular economy, secondary resource potentials) as well as for transport studies and land system science. So far, such maps were only available for specific years but not in time series. Even for s...

Global societal material stock in buildings and infrastructure have accumulated rapidly within the last decades, along with population growth. Recently, an approach for nation‐wide mapping of material stock at 10 m spatial resolution, using freely available and globally consistent Earth Observation (EO) imagery, has been introduced as an alternativ...

Peatlands in the European Union are largely drained for agriculture and emit 25% of the total agricultural greenhouse gas emissions. Drainage-based peatland use has also negative impacts on water quality, drinking water provision and biodiversity. Consequently, key EU environmental policy objectives include the rewetting of all drained peatlands as...

Underpinning EO-based findings with field-based evidence is often indispensable. However, especially in field work, there are countless situations where access to web-based services like Collect Earth or the Google Earth Engine (GEE) is limited or even impossible, such as in rainforests or deserts across the globe. Being able to visualize Earth obs...

Presentation from the EnMAP Session at ESA's Living Planet Symposium

In the second half of the twenty-first century, a strong growth of global human population and economic activity went along with a rapid accumulation of societal material stock. Societal material stock encompasses all long-lived materials contained in buildings, infrastructure and other durable goods. Material stocks are the basis for human-living...

Open and analysis-ready data, as well as methodological and technical advancements have resulted in an unprecedented capability for observing the Earth’s land surfaces. Over 10 years ago, Landsat time series analyses were inevitably limited to a few expensive images from carefully selected acquisition dates. Yet, such a static selection may have in...

Gridded population data is widely used to map fine scale population patterns and dynamics to understand associated human-environmental processes for global change research, disaster risk assessment and other domains. This study mapped gridded population across Germany using weighting layers from building density, building height (both from previous...

Peatlands have been drained for land use for a long time and on a large scale, turning them from carbon and nutrient sinks into respective sources, diminishing water regulation capacity, causing surface height loss and destroying biodiversity. Over the last decades, drained peatlands have been rewetted for biodiversity restoration and, as it strong...

Building libraries of reference spectra for detailed mapping of urban areas at the level of building materials or plant species requires substantial effort. While in the last 15 years many approaches have been proposed to automatically extract pure material spectra from airborne hyperspectral imagery, the labeling of such spectra remains a tedious...

Spaceborne imaging spectrometers are expected to facilitate regional-scale vegetation analyses with multi-season hyperspectral imagery. However, we still lack a better understanding on both whether multi-season hyperspectral approaches are favorable over single-season approaches, as well as on the benefits of hyperspectral compared to multispectral...

Forest aboveground biomass (AGB) is a critical measure of ecosystem structure and plays a key role in global carbon cycling. Due to its widespread availability, optical remotely sensed data are key for regional- and global-scale AGB assessment, and with the planned and recent launches of spaceborne imaging spectroscopy missions such as the Environm...

Gridded population data is widely used to map fine scale population patterns and dynamics to understand associated human-environmental processes for global change research, disaster risk assessment and other domains. This study mapped gridded population across Germany using weighting layers from building density, building height (both from previous...

The dynamics of societal material stocks such as buildings and infrastructures and their spatial patterns drive surging resource use and emissions. Two main types of data are currently used to map stocks, night-time lights (NTL) from Earth-observing (EO) satellites and cadastral information. We present an alternative approach for broad-scale materi...

The EnMAP-Box is a free and open source QGIS plugin. It integrates the strength of Python-based image processing and machine learning with graphical interfaces for handling hyperspectral images and spectral libraries in a GIS environment.

Urban areas and their vertical characteristics have a manifold and far-reaching impact on our environment. However, openly accessible information at high spatial resolution is still missing at large for complete countries or regions. In this study, we combined Sentinel-1A/B and Sentinel-2A/B time series to map building heights for entire Germany on...

Both compact and dispersed green cities are considered sustainable urban forms, yet some developments accompanied with these planning paradigms seem problematic in times of urban growth. A compact city might lose urban green spaces due to infill and a dispersed-green city might lose green in its outskirts through suburbanisation. To study these sto...

The increasing impact of humans on land and ongoing global population growth requires an improved understanding of land cover (LC) and land use (LU) processes related to settlements. The heterogeneity of built-up areas and infrastructures as well as the importance of not only mapping, but also characterizing anthropogenic structures suggests using...

The next generation of spaceborne imaging spectrometers will enable hyperspectral analysis of vegetation cover across large spatial extents. Spectral unmixing provides a means to assess subpixel vegetation composition in such imagery. Here we implement a regression-based unmixing approach to generate fractional vegetation cover on a regional scale...

This dataset is composed of simulated EnMAP mosaics for the San Francisco Bay Area, USA. Hyperspectral imagery used for the EnMAP simulation was collected across three time periods (Spring, Summer, and Fall) in 2013 with the AVIRIS-Classic sensor flown as part of the HyspIRI Preparatory Campaign. Flight lines were simulated to EnMAP-like data using...

This dataset is composed of simulated EnMAP mosaics for the San Francisco Bay Area, USA. Hyperspectral imagery used for the EnMAP simulation was collected across three time periods (Spring, Summer, and Fall) in 2013 with the AVIRIS-Classic sensor flown as part of the HyspIRI Preparatory Campaign. Flight lines were simulated to EnMAP-like data using...

The Landsat archive offers great potential for monitoring forest cover change, and new approaches moving from categorical towards continuous change products emerge rapidly. Most approaches, however, require vast amounts of high-quality reference data, limiting their applicability across space and time. We here propose the use of a generalized regre...

Multi-spectral spaceborne sensors with different spatial resolutions produce Earth observation (EO) time series (TS) with global coverage. The interactive visualization and interpretation of TS is essential to better understand changes in land-use and land-cover and to extract reference information for model calibration and validation. However, ava...

We evaluated the effectiveness of different approaches to compensate for across-track brightness gradients within a hyperspectral image mosaic comprised of multiple flight lines in the San Francisco Bay Area. We calculated the spectral consistency of adjacent flight lines and conducted regression-based unmixing of woody- and non-woody vegetation fr...

An improved trade-off between resolution, coverage and revisit time, makes Sentinel-2 multispectral imagery an interesting data source for mapping the composition and spatial-temporal dynamics of urban land cover. To fully realize the potential of Sentinel-2′s high amount of available data, efficient urban mapping workflows are required. Machine le...

The EnMAP-Box 3 is a toolbox for visualising and processing imaging spectroscopy data and spectral libraries, and is particularly developed to handle data from the upcoming EnMAP (Environmental Mapping and Analysis Program) mission. The integration as a python-based plug-in into the free and open source geographic information system QGIS 3 makes th...

Future spaceborne imaging spectroscopy data will offer new possibilities for mapping ecosystems globally, including urban environments. The high spectral information content of such data is expected to improve accuracies and thematic detail of maps on urban composition and urban environmental condition. This way, urgently needed information for env...

The regression-based unmixing approach using synthetically mixed training data from spectral libraries is now implemented as application in the EnMAP-Box. Check-out our tutorial to learn more .... https://enmap-box.readthedocs.io/en/latest/tutorials/tutorial_1.html#

The Landsat archive presents a unique source for mapping and monitoring of shrublands. Still, efficient and accurate mapping approaches are needed that provide shrub cover fraction estimates over space and time. The spectral signal of shrubs is composed of green vegetation and non-photosynthetic vegetation as well as varying fractions of soil, gras...

PDF slides on the presentation of the EO Time Series Viewer on ESA Earth Observation Φ-week 2018. The EO Time Series Viewer is an open source QGIS Plugin to visualise and describe multi-sensor Earth Observation time series data.

Forthcoming spaceborne imaging spectrometers will provide novel opportunities for mapping urban composition globally. To move from case studies for single cities towards comparative and more operational analyses, generalized models that may be transferred throughout space are desired. In this study, we investigated how single regression models can...

In times of rapid global change, ecosystem monitoring is of utmost importance. Combined field and remote sensing data enable large‐scale ecosystem assessments, while maintaining local relevance and accuracy. In heterogeneous landscapes, however, the integration of field‐collected data with remote sensing image pixels is not a trivial matter. Indeed...

Rapid urban population growth in Sub-Saharan Western Africa has important environmental, infrastructural and social impacts. Due to the low availability of reliable urbanization data, remote sensing techniques become increasingly popular for monitoring land use change processes in that region. This study aims to quantify land cover for the Ouagadou...

Increasing attention is being directed at mapping the fractional woody cover of savannahs using Earth-observation data. In this study, we test the utility of Landsat TM/ ETM-based spectral-temporal variability metrics for mapping regional-scale woody cover in the Limpopo Province of South Africa, for 2010. We employ a machine learning framework to...

Remotely sensed observations of built environments are controlled by the physical properties of the materials and the structural form of the objects used to construct the environment. When using remote sensing to map and monitor built environments, it is important to understand how different sensors respond to the objects and materials. We give a b...

Intensification of cattle ranching has the potential to reduce deforestation rates in the Brazilian Amazon by decreasing the demand for new agricultural land. Explicit spatial knowledge on where, when and how pastures are managed and intensification takes place is needed to better estimate potentials of more sustainable management. Monitoring the f...

The EnMAP-Box is designed to process imaging spectroscopy data and particularly developed to handle data from the upcoming EnMAP (Environmental Mapping and Analysis Program) sensor. It serves as a platform for sharing and distributing algorithms and methods among scientists and potential end-users. Starting with version 3.0 the EnMAP-Box is designe...

Local climate zone (LCZ) mapping is an emerging field in urban climate research. LCZs potentially provide an objective framework to assess urban form and function worldwide. The scheme is currently being used to globally map LCZs as a part of the World Urban Database and Access Portal Tools (WUDAPT) initiative. So far, most of the LCZ maps lack pro...

Spectral unmixing of urban land cover relies on representative endmember libraries. For repeated mapping of multiple cities, the use of a generic spectral library, capturing the vast spectral variability of urban areas, would constitute a more operational alternative to the tedious development of image-specific libraries prior to mapping. The size...

Global warming and the increasing world population will only put more pressure on the living conditions in urban environments. From a thermal comfort point of view, it is clear that there is a need for sustainable urban planning in which the thermal behavior of new developments can be accounted for. Mapping the city into local climate zones (LCZs),...

Generating synthetically mixed data from library spectra provides a direct means to train empirical regression models for subpixel mapping. In order to best represent the subpixel composition of image data, the generation of synthetic mixtures must incorporate a multitude of mixing possibilities. This can lead to an excessive amount of training sam...

Most plant species feature similar biochemical compositions and thus similar spectral signals. Still, empirical evidence suggests that the spectral discrimination of species and plant assemblages is possible. Success depends on the presence or absence of faint but detectable differences in biochemical (e.g., pigments, leaf water and dry matter cont...

Remote sensing based land cover classification in urban areas generally requires the use of subpixel classification algorithms to take into account the high spatial heterogeneity. These spectral unmixing techniques often rely on spectral libraries, i.e. collections of pure material spectra (endmembers, EM), which ideally cover the large EM variabil...

Berlin-Urban-Gradient is a ready-to-use imaging spectrometry dataset for multi-scale unmixing and hard classification analyses in urban environments. The dataset comprises two airborne HyMap scenes at 3.6 and 9 m resolution, a simulated spaceborne EnMAP scene at 30 m resolution, an im-age endmember spectral library and detailed land cover reference...

In times of global environmental change, the sustainability of human–environment systems is only possible through a better understanding of ecosystem processes. An assessment of anthropogenic environmental impacts depends upon monitoring natural ecosystems. These systems are intrinsically complex and dynamic, and are characterized by ecological gra...

The EnMAP-Box is a toolbox that is developed for the processing and analysis of data acquired by the German spaceborne imaging spectrometer EnMAP (Environmental Mapping and Analysis Program). It is developed with two aims in mind in order to guarantee full usage of future EnMAP data, i.e., (1) extending the EnMAP user community and (2) providing ac...

Monitoring natural ecosystems and ecosystem transitions is crucial for a better understanding of land change processes. By providing synoptic views in space and time, remote sensing data have proven to be valuable sources for such purposes. With the forthcoming Environmental Mapping and Analysis Program (EnMAP), frequent and area-wide mapping of na...

Imaging spectroscopy, also known as hyperspectral remote sensing, is based on the characterization of Earth surface materials and processes through spectrally-resolved measurements of the light interacting with matter. The potential of imaging spectroscopy for Earth remote sensing has been demonstrated since the 1980s. However, most of the developm...

Global environmental change is occurring at unprecedented rates. Triggered by climate change impacts, population growth, changes in life style and, thus, increasing demands for food, feed, fiber and fuel, rapid changes in global land use can be observed. A better understanding of change processes on the land surface, e.g. land degradation and aband...

Global population growth, changing lifestyles and related consumption patterns create an increasing demand for goods and services related to global land use. Human land use hence is a major driver of global change, interacting with and often amplifying effects of climate change. Land use change and land use intensification are multi-faceted, includ...

The high information redundancy in hyperspectral and hypertemporal earth observation data can limit the performance of supervised learning algorithms. Traditional sequential feature selection approaches start the search on the full set of correlated features, which is a computationally expensive task and impedes the search and discovery of spectral...

The upcoming hyperspectral satellite mission Environmental Mapping and Analysis Program (EnMAP) will provide timely and globally sampled imaging spectrometer data on a frequent basis. This will create unprecedented opportunities for a variety of environmental research fields and lead to manifold novel applications. These opportunities specifically...

1. Spatial patterns of community composition turnover (beta diversity) may be mapped through generalised dissimilarity modelling (GDM). While remote sensing data are adequate to describe these patterns, the often high-dimensional nature of these data poses some analytical challenges, potentially resulting in loss of generality. This may hinder the...