Mapping tree dieback using Sentinel-2 time series and generalized regression-based unmixing models reveals species-specific patterns across Germany - Jonas Alsleben; Dirk Pflugmacher; Rasmus Rehwaldt; Akpona Okujeni; Patrick Hostert (Remote Sensing of Environment, 2026)

Mowing detection intercomparison exercise (MODCiX) – Evaluation of grassland mowing detection algorithms across Europe - Marcel Schwieder; Felix Lobert; Dominique Weber; Sophie Reinermann; Sarah Asam; Filippo Sarvia; Samuele De Petris; Enrico Borgogno-Mondino; Arnab Muhuri; Natascha Oppelt; Clement Atzberger; Iason Tsardanidis; et al. (Remote Sensing of Environment, 2026)

Leveraging multidecadal satellite time series to estimate grassland age on national scale - Lukas Blickensdörfer; Tom Broeg; Felix Lobert; Marcel Schwieder; Patrick Hostert; Stefan Erasmi (Remote Sensing of Environment, 2026)

The next Landsat: Mission turning point? - David P. Roy; Michael A. Wulder; Noel Gorelick; Matthew Hansen; Sean Healey; Patrick Hostert; Justin Huntington; Volker C. Radeloff; Ted Scambos; Crystal Schaaf; Curtis E. Woodcock; Zhe Zhu (Remote Sensing of Environment, 2026)

Evolving Earth observation capabilities for recent land-related EU policies - Katja Berger; Saskia Foerster; Zoltan Szantoi; Patrick Hostert; Michael Foerster; Ruben Van De Kerchove; Christelle Vancutsem; Christian Schweitzer; Robert Masolele; Johannes Reiche; Mark Dowell; Fabian Enssle; et al. (Land Use Policy, 2025)

Impact of data density and endmember definitions on long-term trends in ground cover fractions across European grasslands - Katarzyna Ewa Lewińska; Akpona Okujeni; Katja Kowalski; Fabian Lehmann; Volker C. Radeloff; Ulf Leser; Patrick Hostert (Remote Sensing of Environment, 2025)

Mapping fractional vegetation cover in Sub-Saharan rangelands using phenological feature spaces - Lasse Harkort; Akpona Okujeni; Vistorina Amputu; Jari Mahler; Leon Nill; Dirk Pflugmacher; Achim Röder; Patrick Hostert (Remote Sensing of Environment, 2025)

Unveiling year-round cropland cover by soil-specific spectral unmixing of Landsat and Sentinel-2 time series - Felix Lobert; Marcel Schwieder; Jonas Alsleben; Tom Broeg; Katja Kowalski; Akpona Okujeni; Patrick Hostert; Stefan Erasmi (Remote Sensing of Environment, 2025)

Weighing the global built environment: High‐resolution mapping and quantification of material stocks in buildings - Helmut Haberl; André Baumgart; Julian Zeidler; Franz Schug; David Frantz; Daniela Palacios‐Lopez; Tomer Fishman; Yoav Peled; Bowen Cai; Doris Virág; Patrick Hostert; Dominik Wiedenhofer; et al. (Journal of Industrial Ecology, 2025)
Buildings provide indispensable services for human well‐being, but their construction and use are responsible for a substantial fraction of societies’ resource requirements and greenhouse gas emissions. Mapping and quantifying the material stocks in buildings is a key research frontier in industrial ecology. Reliable and spatially highly resolved maps of material stocks in buildings worldwide are so far not available. Existing approaches based on nighttime light data allow large‐scale coverage, but their spatial resolution is usually ∼0.5–1 km. Other methods using light detection and ranging (LiDAR) and cadaster data achieve higher resolution and accuracy, but do not allow wall‐to‐wall mapping of large regions. Based on high‐resolution Earth Observation data combined with material intensity factors (kg per m 3 of building volume), we quantify and map material stocks in buildings at the unprecedented resolution of 90 m globally. We distinguish 18 types of materials in five types of buildings. We find that global material stocks in buildings amount to 547 (391–672) Gt, approximately half of total global societal material stocks. We find highly unequal distributions of material stocks in buildings per capita and per unit area of each country. Our results agree well with previous detailed estimates of material stocks in buildings in dedicated regions or individual cities. Improved and harmonized material intensity factors emerge as a key research area for improving the accuracy of material stock maps. Our results are available as data products with high spatial and thematic resolution to facilitate future studies; for example, of secondary resource potentials. This article met the requirements for a gold‐gold JIE data openness badge described at http://jie.click/badges .

The EnMAP spaceborne imaging spectroscopy mission: Initial scientific results two years after launch - Sabine Chabrillat; Saskia Foerster; Karl Segl; Alison Beamish; Maximilian Brell; Saeid Asadzadeh; Robert Milewski; Kathrin J. Ward; Arlena Brosinsky; Katrin Koch; Daniel Scheffler; Stephane Guillaso; et al. (Remote Sensing of Environment, 2024)

Large‐scale remote sensing analysis reveals an increasing coupling of grassland vitality to atmospheric water demand - Katja Kowalski; Cornelius Senf; Akpona Okujeni; Patrick Hostert (Global Change Biology, 2024)
Grasslands provide important ecosystem services to society, including biodiversity, water security, erosion control, and forage production. Grasslands are also vulnerable to droughts, rendering their future vitality under climate change uncertain. Yet, the grassland response to drought is not well understood, especially for heterogeneous Central European grasslands. We here fill this gap by quantifying the spatiotemporal sensitivity of grasslands to drought using a novel remote sensing dataset from Landsat/Sentinel‐2 paired with climate re‐analysis data. Specifically, we quantified annual grassland vitality at fine spatial scale and national extent (Germany) from 1985 to 2021. We analyzed grassland sensitivity to drought by testing for statistically robust links between grassland vitality and common drought indices. We furthermore explored the spatiotemporal variability of drought sensitivity for 12 grassland habitat types given their different biotic and abiotic features. Grassland vitality maps revealed a large‐scale reduction of grassland vitality during past droughts. The unprecedented drought of 2018–2019 stood out as the largest multi‐year vitality decline since the mid‐1980s. Grassland vitality was consistently coupled to drought ( R 2 = .09–.22) with Vapor Pressure Deficit explaining vitality best. This suggests that high atmospheric water demand, as observed during recent compounding drought and heatwave events, has major impacts on grassland vitality in Central Europe. We found a significant increase in drought sensitivity over time with highest sensitivities detected in periods of extremely high atmospheric water demand, suggesting that drought impacts on grasslands are becoming more severe with ongoing climate change. The spatial variability of grassland drought sensitivity was linked to different habitat types, with declining sensitivity from dry and mesic to wet habitats. Our study provides the first large‐scale, long‐term, and spatially explicit evidence of increasing drought sensitivities of Central European grasslands. With rising compound droughts and heatwaves under climate change, large‐scale grassland vitality loss, as in 2018–2019, will thus become more likely in the future.

National tree species mapping using Sentinel-1/2 time series and German National Forest Inventory data - Lukas Blickensdörfer; Katja Oehmichen; Dirk Pflugmacher; Birgit Kleinschmit; Patrick Hostert (Remote Sensing of Environment, 2024)

Multidecadal grassland fractional cover time series retrieval for Germany from the Landsat and Sentinel-2 archives - Akpona Okujeni; Katja Kowalski; Katarzyna Ewa Lewińska; Shawn Schneidereit; Patrick Hostert (Remote Sensing of Environment, 2024)

Need and vision for global medium-resolution Landsat and Sentinel-2 data products - Volker C. Radeloff; David P. Roy; Michael A. Wulder; Martha Anderson; Bruce Cook; Christopher J. Crawford; Mark Friedl; Feng Gao; Noel Gorelick; Matthew Hansen; Sean Healey; Patrick Hostert; et al. (Remote Sensing of Environment, 2024)

A deep learning approach for deriving winter wheat phenology from optical and SAR time series at field level - Felix Lobert; Johannes Löw; Marcel Schwieder; Alexander Gocht; Michael Schlund; Patrick Hostert; Stefan Erasmi (Remote Sensing of Environment, 2023)

Understanding the robustness of spectral-temporal metrics across the global Landsat archive from 1984 to 2019 – a quantitative evaluation - David Frantz; Philippe Rufin; Andreas Janz; Stefan Ernst; Dirk Pflugmacher; Franz Schug; Patrick Hostert (Remote Sensing of Environment, 2023)

Beyond “greening” and “browning”: Trends in grassland ground cover fractions across Eurasia that account for spatial and temporal autocorrelation - Katarzyna Ewa Lewińska; Anthony R. Ives; Clay J. Morrow; Natalia Rogova; He Yin; Paul R. Elsen; Kirsten de Beurs; Patrick Hostert; Volker C. Radeloff (Global Change Biology, 2023)
Grassland ecosystems cover up to 40% of the global land area and provide many ecosystem services directly supporting the livelihoods of over 1 billion people. Monitoring long‐term changes in grasslands is crucial for food security, biodiversity conservation, achieving Land Degradation Neutrality goals, and modeling the global carbon budget. Although long‐term grassland monitoring using remote sensing is extensive, it is typically based on a single vegetation index and does not account for temporal and spatial autocorrelation, which means that some trends are falsely identified while others are missed. Our goal was to analyze trends in grasslands in Eurasia, the largest continuous grassland ecosystems on Earth. To do so, we calculated Cumulative Endmember Fractions (annual sums of monthly ground cover fractions) derived from MODIS 2002–2020 time series, and applied a new statistical approach PARTS that explicitly accounts for temporal and spatial autocorrelation in trends. We examined trends in green vegetation, non‐photosynthetic vegetation, and soil ground cover fractions considering their independent change trajectories and relations among fractions over time. We derived temporally uncorrelated pixel‐based trend maps and statistically tested whether observed trends could be explained by elevation, land cover, SPEI3, climate, country, and their combinations, all while accounting for spatial autocorrelation. We found no statistical evidence for a decrease in vegetation cover in grasslands in Eurasia. Instead, there was a significant map‐level increase in non‐photosynthetic vegetation across the region and local increases in green vegetation with a concomitant decrease in soil fraction. Independent environmental variables affected trends significantly, but effects varied by region. Overall, our analyses show in a statistically robust manner that Eurasian grasslands have changed considerably over the past two decades. Our approach enhances remote sensing‐based monitoring of trends in grasslands so that underlying processes can be discerned.

A generalized framework for drought monitoring across Central European grassland gradients with Sentinel-2 time series - Katja Kowalski; Akpona Okujeni; Patrick Hostert (Remote Sensing of Environment, 2023)

High‐resolution mapping of 33 years of material stock and population growth in Germany using Earth Observation data - Franz Schug; David Frantz; Dominik Wiedenhofer; Helmut Haberl; Doris Virág; Sebastian van der Linden; Patrick Hostert (Journal of Industrial Ecology, 2023)
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 alternative to cost‐intensive cadastral data or broad‐scale but thematically limited nighttime light‐based mapping. This study assessed the potential of EO data archives to create spatially explicit time series data of material stock dynamics and their relation to population in Germany, at a spatial resolution of 30 m. We used Landsat imagery with a change‐aftereffect‐trend analysis to derive yearly masks of land surface change from 1985 onward. Those served as an input to an annual reverse calculation of six material stock types and building volume‐based annual gridded population, based on maps for 2018. Material stocks and population in Germany grew by 13% and 4%, respectively, showing highly variable spatial patterns. We found a minimum building stock of ca. 180 t/cap across all municipalities and growth processes characterized by sprawl. A rapid growth of stocks per capita occurred in East Germany after the reunification in 1990, with increased building activity but population decline. Possible over‐ or underestimations of stock growth cannot be ruled out due to methodological assumptions, requiring further research.

Post-Soviet Land-Use Change Affected Fire Regimes on the Eurasian Steppes - Andrey Dara; Matthias Baumann; Norbert Hölzel; Patrick Hostert; Johannes Kamp; Daniel Müller; Benjamin Ullrich; Tobias Kuemmerle (Ecosystems, 2020)

Synthesizing dam-induced land system change - Philippe Rufin; Florian Gollnow; Daniel Müller; Patrick Hostert (Ambio, 2019)

Historical carbon fluxes in the expanding deforestation frontier of Southern Brazilian Amazonia (1985–2012) - Letícia de Barros Viana Hissa; Hannes Müller; Ana Paula Dutra Aguiar; Patrick Hostert; Tobia Lakes (Regional Environmental Change, 2018)

Carbon emissions from agricultural expansion and intensification in the Chaco - Matthias Baumann; Ignacio Gasparri; María Piquer‐Rodríguez; Gregorio Gavier Pizarro; Patrick Griffiths; Patrick Hostert; Tobias Kuemmerle (Global Change Biology, 2017)
Carbon emissions from land‐use changes in tropical dry forest systems are poorly understood, although they are likely globally significant. The South American Chaco has recently emerged as a hot spot of agricultural expansion and intensification, as cattle ranching and soybean cultivation expand into forests, and as soybean cultivation replaces grazing lands. Still, our knowledge of the rates and spatial patterns of these land‐use changes and how they affected carbon emissions remains partial. We used the Landsat satellite image archive to reconstruct land‐use change over the past 30 years and applied a carbon bookkeeping model to quantify how these changes affected carbon budgets. Between 1985 and 2013, more than 142 000 km 2 of the Chaco's forests, equaling 20% of all forest, was replaced by croplands (38.9%) or grazing lands (61.1%). Of those grazing lands that existed in 1985, about 40% were subsequently converted to cropland. These land‐use changes resulted in substantial carbon emissions, totaling 824 Tg C between 1985 and 2013, and 46.2 Tg C for 2013 alone. The majority of these emissions came from forest‐to‐grazing‐land conversions (68%), but post‐deforestation land‐use change triggered an additional 52.6 Tg C. Although tropical dry forests are less carbon‐dense than moist tropical forests, carbon emissions from land‐use change in the Chaco were similar in magnitude to those from other major tropical deforestation frontiers. Our study thus highlights the urgent need for an improved monitoring of the often overlooked tropical dry forests and savannas, and more broadly speaking the value of the Landsat image archive for quantifying carbon fluxes from land change.

Changes in the spatial patterns of human appropriation of net primary production (HANPP) in Europe 1990–2006 - Christoph Plutzar; Christine Kroisleitner; Helmut Haberl; Tamara Fetzel; Claudia Bulgheroni; Tim Beringer; Patrick Hostert; Thomas Kastner; Tobias Kuemmerle; Christian Lauk; Christian Levers; Marcus Lindner; et al. (Regional Environmental Change, 2016)

A high‐resolution approach to estimating ecosystem respiration at continental scales using operational satellite data - Jonas Jägermeyr; Dieter Gerten; Wolfgang Lucht; Patrick Hostert; Mirco Migliavacca; Ramakrishna Nemani (Global Change Biology, 2014)
A better understanding of the local variability in land‐atmosphere carbon fluxes is crucial to improving the accuracy of global carbon budgets. Operational satellite data backed by ground measurements at Fluxnet sites proved valuable in monitoring local variability of gross primary production at highly resolved spatio‐temporal resolutions. Yet, we lack similar operational estimates of ecosystem respiration (Re) to calculate net carbon fluxes. If successful, carbon fluxes from such a remote sensing approach would form an independent and sought after measure to complement widely used dynamic global vegetation models ( DGVM s). Here, we establish an operational semi‐empirical Re model, based only on data from the Moderate Resolution Imaging Spectroradiometer ( MODIS ) with a resolution of 1 km and 8 days. Fluxnet measurements between 2000 and 2009 from 100 sites across North America and Europe are used for parameterization and validation. Our analysis shows that Re is closely tied to temperature and plant productivity. By separating temporal and intersite variation, we find that MODIS land surface temperature ( LST ) and enhanced vegetation index ( EVI ) are sufficient to explain observed Re across most major biomes with a negligible bias [ R ² = 0.62, RMSE = 1.32 (g C m −2 d −1 ), MBE = 0.05 (g C m −2 d −1 )]. A comparison of such satellite‐derived Re with those simulated by the DGVM LPJ mL reveals similar spatial patterns. However, LPJ mL shows higher temperature sensitivities and consistently simulates higher Re values, in high‐latitude and subtropical regions. These differences remain difficult to explain and they are likely associated either with LPJ mL parameterization or with systematic errors in the Fluxnet sampling technique. While uncertainties remain with Re estimates, the model formulated in this study provides an operational, cross‐validated and unbiased approach to scale Fluxnet Re to the continental scale and advances knowledge of spatio‐temporal Re variability.

Remote sensing of sun‐induced fluorescence to improve modeling of diurnal courses of gross primary production (GPP) - ALEXANDER DAMM; JAN ELBERS; ANDRÉ ERLER; BENIAMINO GIOLI; KARIM HAMDI; RONALD HUTJES; MARTINA KOSVANCOVA; MICHELE MERONI; FRANCO MIGLIETTA; ANDRÉ MOERSCH; JOSE MORENO; ANKE SCHICKLING; et al. (Global Change Biology, 2010)
Terrestrial gross primary production (GPP) is an important parameter to explore and quantify carbon fixation by plant ecosystems at various scales. Remote sensing (RS) offers a unique possibility to investigate GPP in a spatially explicit fashion; however, budgeting of terrestrial carbon cycles based on this approach still remains uncertain. To improve calculations, spatio‐temporal variability of GPP must be investigated in more detail on local and regional scales. The overarching goal of this study is to enhance our knowledge on how environmentally induced changes of photosynthetic light‐use efficiency (LUE) are linked with optical RS parameters. Diurnal courses of sun‐induced fluorescence yield ( F Syield ) and the photochemical reflectance index of corn were derived from high‐resolution spectrometric measurements and their potential as proxies for LUE was investigated. GPP was modeled using Monteith's LUE‐concept and optical‐based GPP and LUE values were compared with synoptically acquired eddy covariance data. It is shown that the diurnal response of complex physiological regulation of photosynthesis can be tracked reliably with the sun‐induced fluorescence. Considering structural and physiological effects, this research shows for the first time that including sun‐induced fluorescence into modeling approaches improves their results in predicting diurnal courses of GPP. Our results support the hypothesis that air‐ or spaceborne quantification of sun‐induced fluorescence yield may become a powerful tool to better understand spatio‐temporal variations of fluorescence yield, photosynthetic efficiency and plant stress on a global scale.

Cross-border Comparison of Post-socialist Farmland Abandonment in the Carpathians - Tobias Kuemmerle; Patrick Hostert; Volker C. Radeloff; Sebastian van der Linden; Kajetan Perzanowski; Ivan Kruhlov (Ecosystems, 2008)