Browsing by Author "Hostert, Patrick"
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Publication 2023-03-01ZeitschriftenartikelA generalized framework for drought monitoring across Central European grassland gradients with Sentinel-2 time series(Mathematisch-Naturwissenschaftliche Fakultät) Kowalski, Katja; Okujeni, Akpona; Hostert, PatrickFractional cover time series of photosynthetic vegetation (PV), non-photosynthetic vegetation (NPV), and soil from remote sensing provide essential detail to understand how grasslands are affected by recent and future drought periods in the 21st century. In this regard, Sentinel-2A/B offer frequent large-area observations, which have not yet been fully exploited for a spatially continuous drought monitoring of highly dynamic Central European grasslands. In this study, we developed a generalized drought monitoring framework for Central European grasslands linking Sentinel-2 data, field survey information, and spectral unmixing. We first implemented a consistent and repeatable strategy to obtain a grassland spectral library supported by the Europe-wide Land Use/Cover Area frame statistical Survey (LUCAS) and multitemporal Sentinel-2 data. Our library captured the spectral variability of PV, NPV, and soil cover from 12 grassland areas distributed along typical environmental and land use gradients of Central Europe. We trained a generalized regression-based unmixing model with synthetic data generated from the spectral library and compared fractional cover estimates to a multitemporal reference dataset. PV, NPV, and soil were estimated with good accuracy, achieving MAEs of 6.54%, 13.7%, and 12.2%, respectively. Local unmixing models trained on area-specific library subsets were overall outperformed by the generalized model highlighting the value of a comprehensive grassland library for generalized spectral unmixing. Based on fractional cover time series from 2017 to 2021, we calculated time series of the grassland-specific Normalized Difference Fraction Index (NDFI) capturing proportions of NPV and soil relative to PV. Comparison of annual growing season drought metrics derived from the NDFI to annual meteorological drought statistics from the Standardized Precipitation Evapotranspiration Index (SPEI) as well as the Soil Moisture Index (SMI) revealed widespread drought impacts on grasslands during the persistent drought period in Central Europe from 2018 to 2020. While impacts on grasslands overall closely followed meteorological and soil drought conditions, regionally varying drought metrics underline that local to regional environmental and hydrological conditions shaped the drought response of Central European grasslands. Our study emphasizes the value of combining Sentinel-2 data, field survey information, and spectral unmixing to enable drought monitoring across grassland gradients of Central Europe with Sentinel-2 time series.Publication 2019-01-28ZeitschriftenartikelA Global MODIS Water Vapor Database for the Operational Atmospheric Correction of Historic and Recent Landsat Imagery(Mathematisch-Naturwissenschaftliche Fakultät) Frantz, David; Stellmes, Marion; Hostert, PatrickAnalysis Ready Data (ARD) have undergone the most relevant pre-processing steps to satisfy most user demands. The freely available software FORCE (Framework for Operational Radiometric Correction for Environmental monitoring) is capable of generating Landsat ARD. An essential step of generating ARD is atmospheric correction, which requires water vapor data. FORCE relies on a water vapor database obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS). However, two major drawbacks arise from this strategy: (1) The database has to be compiled for each study area prior to generating ARD; and (2) MODIS and Landsat commissioning dates are not well aligned. We have therefore compiled an application-ready global water vapor database to significantly increase the operational readiness of ARD production. The free dataset comprises daily water vapor data for February 2000 to July 2018 as well as a monthly climatology that is used if no daily value is available. We systematically assessed the impact of using this climatology on surface reflectance outputs. A global random sample of Landsat 5/7/8 imagery was processed twice (i) using daily water vapor (reference) and (ii) using the climatology (estimate), followed by computing accuracy, precision, and uncertainty (APU) metrics. All APU measures were well below specification, thus the fallback usage of the climatology is generally a sound strategy. Still, the tests revealed that some considerations need to be taken into account to help quantify which sensor, band, climate, and season are most or least affected by using a fallback climatology. The highest uncertainty and bias is found for Landsat 5, with progressive improvements towards newer sensors. The bias increases from dry to humid climates, whereas uncertainty increases from dry and tropic to temperate climates. Uncertainty is smallest during seasons with low variability, and is highest when atmospheric conditions progress from a dry to a wet season (and vice versa).Publication 2017-07-01ZeitschriftenartikelAROSICS: An Automated and Robust Open-Source Image Co-Registration Software for Multi-Sensor Satellite Data(Mathematisch-Naturwissenschaftliche Fakultät) Scheffler, Daniel; Hollstein, André; Diedrich, Hannes; Segl, Karl; Hostert, PatrickAbstract Geospatial co-registration is a mandatory prerequisite when dealing with remote sensing data. Inter- or intra-sensoral misregistration will negatively affect any subsequent image analysis, specifically when processing multi-sensoral or multi-temporal data. In recent decades, many algorithms have been developed to enable manual, semi- or fully automatic displacement correction. Especially in the context of big data processing and the development of automated processing chains that aim to be applicable to different remote sensing systems, there is a strong need for efficient, accurate and generally usable co-registration. Here, we present AROSICS (Automated and Robust Open-Source Image Co-Registration Software), a Python-based open-source software including an easy-to-use user interface for automatic detection and correction of sub-pixel misalignments between various remote sensing datasets. It is independent of spatial or spectral characteristics and robust against high degrees of cloud coverage and spectral and temporal land cover dynamics. The co-registration is based on phase correlation for sub-pixel shift estimation in the frequency domain utilizing the Fourier shift theorem in a moving-window manner. A dense grid of spatial shift vectors can be created and automatically filtered by combining various validation and quality estimation metrics. Additionally, the software supports the masking of, e.g., clouds and cloud shadows to exclude such areas from spatial shift detection. The software has been tested on more than 9000 satellite images acquired by different sensors. The results are evaluated exemplarily for two inter-sensoral and two intra-sensoral use cases and show registration results in the sub-pixel range with root mean square error fits around 0.3 pixels and better.Publication 2007-03-20ZeitschriftenartikelAuf elektronischem Wege nach BolognaGrune, Christian; Vetter, Danilo; Wapenhans, Heike; Gerwien, Johannes; Groß, Martin; Strietz, Monika; Schumacher, Nicole; Hostert, Patrick; Palácsik, Sandra; Scheuschner, Thomas; Lohse, Tillmann; Schirmbacher, PeterDer Bologna-Prozess ist in seinen strukturellen Auswirkungen eng verbunden mit der Nutzung digitaler Technologien. Die damit verbundenen Fragen werden unter dem Stichwort E-Bologna diskutiert. Zwei Themen stehen dabei im Vordergrund: Wie müssen die vorhandenen Systeme an Hochschulen aus einer organisatorischen und administrativen Perspektive integriert und erweitert werden und welche Möglichkeiten bieten digitale Technologien in der Lehre, die Förderung von Mobilität, lebenslangem Lernen und Aufbau von Schlüsselkompetenzen zu unterstützen? Der Beitrag zeigt praxisnahe Beispiele, wie an den Instituten der Humboldt-Universität flexibel mit den neuen Herausforderungen umgegangen wird. Die präsentierten Lösungen sind eng an konkreten Herausforderungen entwickelt worden und haben nicht den Anspruch eine umfassende Lösung zu erarbeiten. Sie sind vielmehr strikt pragmatisch angelegt und damit alltagstauglich im fachlichen Kontext. Der Beitrag will Anregungen und Beispiele geben, wie die mit Bologna verbundenen Herausforderungen mit Hilfe digitaler Technologien gemeistert werden.Publication 2019-10-28ZeitschriftenartikelBrightness gradient-corrected hyperspectral image mosaics for fractional vegetation cover mapping in northern California(Mathematisch-Naturwissenschaftliche Fakultät) Jänicke, Clemens; Okujeni, Akpona; Cooper, Sam; Clark, Matthew; Hostert, Patrick; Linden, Sebastian van derWe 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 fractions to assess the comparative benefits of the methods. Results showed that a class-wise empirical approach produced the most spectrally consistent, nearly seamless image mosaics and led to accurate vegetation fraction maps (mean absolute error = 12.6%). Overall, a class-wise empirical approach is recommended as a simple, flexible and transferable technique to compensate for brightness gradients over a global empirical approach, brightness normalization or continuum removal.Publication 2018-11-26ZeitschriftenartikelCanopy mortality has doubled in Europe’s temperate forests over the last three decades(Mathematisch-Naturwissenschaftliche Fakultät) Senf, Cornelius; Pflugmacher, Dirk; Zhiqiang, Yang; Sebald, Julius; Knorn, Jan; Neumann, Mathias; Hostert, Patrick; Seidl, RupertMortality is a key indicator of forest health, and increasing mortality can serve as bellwether for the impacts of global change on forest ecosystems. Here we analyze trends in forest canopy mortality between 1984 and 2016 over more than 30 Mill. ha of temperate forests in Europe, based on a unique dataset of 24,000 visually interpreted spectral trajectories from the Landsat archive. On average, 0.79% of the forest area was affected by natural or human-induced mortality annually. Canopy mortality increased by +2.40% year–1, doubling the forest area affected by mortality since 1984. Areas experiencing low-severity mortality increased more strongly than areas affected by stand-replacing mortality events. Changes in climate and land-use are likely causes of large-scale forest mortality increase. Our findings reveal profound changes in recent forest dynamics with important implications for carbon storage and biodiversity conservation, highlighting the importance of improved monitoring of forest mortality.Publication 2013-06-29ZeitschriftenartikelChallenges and opportunities in mapping land use intensity globally(Mathematisch-Naturwissenschaftliche Fakultät) Kuemmerle, Tobias; Erb, Karlheinz; Meyfroidt, Patrick; Müller, Daniel; Verburg, Peter H; Hostert, Patrick; Jepsen, Martin R.; Kastner, Thomas; Levers, Christian; Lindner, Marcus; Plutzar, Christoph; Verkerk, Pieter Johannes; van der Zanden, Emma H; Reenberg, AnetteFuture increases in land-based production will need to focus more on sustainably intensifying existing production systems. Unfortunately, our understanding of the global patterns of land use intensity is weak, partly because land use intensity is a complex, multidimensional term, and partly because we lack appropriate datasets to assess land use intensity across broad geographic extents. Here, we review the state of the art regarding approaches for mapping land use intensity and provide a comprehensive overview of available global-scale datasets on land use intensity. We also outline major challenges and opportunities for mappinglanduseintensityfor cropland, grazing, and forestry systems, and identify key issues for future research.Publication 2020-06-11ZeitschriftenartikelCharacterizing spring phenology of temperate broadleaf forests using Landsat and Sentinel-2 time series(Mathematisch-Naturwissenschaftliche Fakultät) Kowalski, Katja; Senf, Cornelius; Hostert, Patrick; Pflugmacher, DirkVegetation phenology has a great impact on land-atmosphere interactions like carbon cycling, albedo, and water and energy exchanges. To understand and predict these critical land-atmosphere feedbacks, it is crucial to measure and quantify phenological responses to climate variability, and ultimately climate change. Coarse-resolution sensors such as MODIS and AVHRR have been useful to study vegetation phenology from regional to global scales. These sensors are, however, not capable of discerning phenological variation at moderate spatial scales. By offering increased observation density and higher spatial resolution, the combination of Landsat and Sentinel-2 time series might provide the opportunity to overcome this limitation. In this study, we analyzed the potential of combined Sentinel-2 and Landsat time series for estimating start of season (SOS) of broadleaf forests across Germany for the year 2018. We tested two common statistical modeling approaches (logistic and generalized additive models using thin plate splines) and the two most commonly used vegetation indices, the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI). We found strong agreement between SOS estimates from logistic and spline models (rEVI = 0.86; rNDVI = 0.65), whereas agreement was higher for EVI than for NDVI (RMSDEVI = 3.07, RMSDNDVI = 5.26 days). The choice of vegetation index thus had a higher impact on the results than the fitting method. The EVI-based SOS also showed higher correlation with ground observations compared to NDVI (rEVI = 0.51, rNDVI = 0.42). Data density played an important role in estimating land surface phenology. Models combining Sentinel-2A/B, with an average cloud-free observation frequency of 12 days, were largely consistent with the combined Landsat and Sentinel-2 models, suggesting that Sentinel-2A/B may be sufficient to capture SOS for most areas in Germany in 2018. However, in non-overlapping swath areas and mountain areas, observation frequency was significantly lower, underlining the need to combine Landsat and Sentinel-2 for consistent SOS estimates over large areas. Our study demonstrates that estimating SOS of temperate broadleaf forests at medium spatial resolution has become feasible with combined Landsat and Sentinel-2 time series.Publication 2012-12-10ZeitschriftenartikelContinued loss of temperate old-growth forests in the Romanian Carpathians despite an increasing protected area network(Mathematisch-Naturwissenschaftliche Fakultät) Knorn, Jan; Kuemmerle, Tobias; Radeloff, Volker C; Keeton, S. Keeton; Gancz, Vladimir; Biris, Iovu-Adrian; Svoboda, Miroslav; Griffiths, Patrick; Hagatis, Adrian; Hostert, PatrickOld-growth forests around the world are vanishing rapidly and have been lost almost completely from the European temperate forest region. Poor management practices, often triggered by socioeconomic and institutional change, are the main causes of loss. Recent trends in old-growth forest cover in Romania, where some of the last remaining tracts of these forests within Europe are located, are revealed by satellite image analysis. Forest cover declined by 1.3 % from 2000 to 2010. Romania's protected area network has been expanded substantially since the country's accession to the European Union in 2007, and most of the remaining old-growth forests now are located within protected areas. Surprisingly though, 72% of the old-growth forest disturbances are found within protected areas, highlighting the threats still facing these forests. It appears that logging in old-growth forests is, at least in part, related to institutional reforms, insufficient protection and ownership changes since the collapse of communism in 1989. The majority of harvesting activities in old-growth forest areas are in accordance with the law. Without improvements to their governance, the future of Romania's old-growth forests and the important ecosystem services they provide remains uncertain.Publication 2023-04-09ZeitschriftenartikelDeforestation and agricultural fires in South-West Pará, Brazil, under political changes from 2014 to 2020(Mathematisch-Naturwissenschaftliche Fakultät) Jakimow, Benjamin; Baumann, Matthias; Salomão, Caroline ; Bendini, Hugo; Hostert, PatrickThe increasing deforestation and fires since 2019 raises concerns about the irreversible destruction of the Brazilian Amazon. Our goal was to better understand these changes in south-west Pará across different land-tenure and farm systems and between the terms of President Rousseff, Temer, and Bolsonaro. We reconstructed deforestation and fire history using all Landsat and Sentinel-2 observations from 2014 to 2020 and assessed, using quasi-experimental methods, the average treatment effects of each presidency on deforestation and fires across land-tenure and farm types. Deforestation nearly quadrupled to 1,201 km2, particularly during Bolsonaro in undesignated areas and conservation units and on medium-sized farms (p < 0.001). Burning increased to 4,805 km2 and in all tenure types (p < 0.001). The increase was strongest in agrarian settlements and conservation units and on medium and large farms. Our observations show the importance of clarifying land-tenure and re-strengthening disincentives of environmental infractions, which have been weakened specifically under President Bolsonaro.Publication 2020-08-05ZeitschriftenartikelEstimating Grassland Parameters from Sentinel‑2: A Model Comparison Study(Mathematisch-Naturwissenschaftliche Fakultät) Schwieder, Marcel; Buddeberg, M.; Kowalski, K.; Pfoch, K.; Bartsch, J.; Bach, H.; Pickert, J.; Hostert, PatrickGrassland plays an important role in German agriculture. The interplay of ecological processes in grasslands secures important ecosystem functions and, thus, ultimately contributes to essential ecosystem services. To sustain, e.g., the provision of fodder or the filter function of soils, agricultural management needs to adapt to site-specific grassland characteristics. Spatially explicit information derived from remote sensing data has been proven instrumental for achieving this. In this study, we analyze the potential of Sentinel-2 data for deriving grassland-relevant parameters. We compare two well-established methods to calculate the aboveground biomass and leaf area index (LAI), first using a random forest regression and second using the soil–leaf-canopy (SLC) radiative transfer model. Field data were recorded on a grassland area in Brandenburg in August 2019, and were used to train the empirical model and to validate both models. Results confirm that both methods are suitable for mapping the spatial distribution of LAI and for quantifying aboveground biomass. Uncertainties generally increased with higher biomass and LAI values in the empirical model and varied on average by a relative RMSE of 11% for modeling of dry biomass and a relative RMSE of 23% for LAI. Similar estimates were achieved using SLC with a relative RMSE of 30% for LAI retrieval, and a relative RMSE of 47% for the estimation of dry biomass. Resulting maps from both approaches showed comprehensible spatial patterns of LAI and dry biomass distributions. Despite variations in the value ranges of both maps, the average estimates and spatial patterns of LAI and dry biomass were very similar. Based on the results of the two compared modeling approaches and the comparison to the validation data, we conclude that the relationship between Sentinel-2 spectra and grassland-relevant variables can be quantified to map their spatial distributions from space. Future research needs to investigate how similar approaches perform across different grassland types, seasons and grassland management regimes.Publication 2019-05-20ZeitschriftenartikelForest Stand Species Mapping Using the Sentinel-2 Time Series(Mathematisch-Naturwissenschaftliche Fakultät) Grabska, Ewa; Hostert, Patrick; Pflugmacher, Dirk; Ostapowicz, KatarzynaAccurate information regarding forest tree species composition is useful for a wide range of applications, both for forest management and scientific research. Remote sensing is an efficient tool for collecting spatially explicit information on forest attributes. With the launch of the Sentinel-2 mission, new opportunities have arisen for mapping tree species owing to its spatial, spectral, and temporal resolution. The short revisit cycle (five days) is crucial in vegetation mapping because of the reflectance changes caused by phenological phases. In our study, we evaluated the utility of the Sentinel-2 time series for mapping tree species in the complex, mixed forests of the Polish Carpathian Mountains. We mapped the following nine tree species: common beech, silver birch, common hornbeam, silver fir, sycamore maple, European larch, grey alder, Scots pine, and Norway spruce. We used the Sentinel-2 time series from 2018, with 18 images included in the study. Different combinations of Sentinel-2 imagery were selected based on mean decrease accuracy (MDA) and mean decrease Gini (MDG) measures, in addition to temporal phonological pattern analysis. Tree species discrimination was performed using the Random Forest classification algorithm. Our results showed that the use of the Sentinel-2 time series instead of single date imagery significantly improved forest tree species mapping, by approximately 5–10% of overall accuracy. In particular, combining images from spring and autumn resulted in better species discrimination.Publication 2018-08-22ZeitschriftenartikelFrom sample to pixel: multi-scale remote sensing data for upscaling aboveground carbon data in heterogeneous landscapes(Mathematisch-Naturwissenschaftliche Fakultät) Pedro J., Leitão; Schwieder, Marcel; Pötzschner, Florian; Pinto, José R. R.; Teixeira, Ana M. C.; Pedroni, Fernando; Sanchez, Maryland; Rogass, Christian; van der Linden, Sebastian; Bustamante, Mercedes M. C.; Hostert, PatrickIn 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, much of the uncertainty in models that use remote sensing to map larger areas lies on the field data integration. In this study, we propose to use fine spatial resolution (5 × 5 m2) remote sensing data as auxiliary data for upscaling field‐sampled aboveground carbon data to target (meso‐scale, i.e., 30 × 30 m2) image pixels. In this process, we assess the effects of field data disaggregation and extrapolation, with and without the auxiliary data. We test this on three study sites in heterogeneous landscapes of the Brazilian savanna. We thus compare two methods that use auxiliary data—surface method, which uses a weighting layer, and regression method, which applies a regression model—with one method without auxiliary data—cartographic method. To evaluate our results, we compared observed vs. estimated aboveground carbon values (for known samples) at the pixel level. Additionally, we fitted a random forest regression model with the assigned carbon estimates and the target satellite imagery and assessed the influence of the fraction of extrapolated vs. sampled carbon values on model performance. We observed that, in heterogeneous landscapes, the use of fine spatial resolution remote sensing data improves the upscaling of field‐based aboveground carbon data to coarser image pixels. We also show that a surface method is more suitable for spatial disaggregation, while a regression approach is preferable for extrapolating non‐sampled pixel fractions. In our study, larger datasets, which included a higher proportion of estimated values, generally delivered better models of aboveground carbon than smaller datasets that are assumed to more reliably reflect reality. Our approach enables to link field and remote sensing data, which in turn enables the detailed mapping of aboveground carbon in heterogeneous landscapes over large areas through the optimized integration of field data and multi‐scale remote sensing data.Publication 2016ZeitschriftenartikelFrom teleconnection to telecoupling(Philosophische Fakultät) Friis, Cecilie; Nielsen, Jonas Østergaard; Otero, Iago; Haberl, Helmut; Niewöhner, Jörg; Hostert, PatrickLand use change is influenced by a complexity of drivers that transcend spatial, institutional and temporal scales. The analytical framework of telecoupling has recently been proposed in land system science to address this complexity, particularly the increasing importance of distal connections, flows and feedbacks characterising change in land systems. This framework holds important potential for advancing the analysis of land system change. In this article, we review the state of the art of the telecoupling framework in the land system science literature. The article traces the development of the framework from teleconnection to telecoupling and presents two approaches to telecoupling analysis currently proposed in the literature. Subsequently, we discuss a number of analytical challenges related to categorisation of systems, system boundaries, hierarchy and scale. Finally, we propose approaches to address these challenges by looking beyond land system science to theoretical perspectives from economic geography, social metabolism studies, political ecology and cultural anthropology.Publication 2021-03-26ZeitschriftenartikelGridded population mapping for Germany based on building density, height and type from Earth Observation data using census disaggregation and bottom-up estimates(Mathematisch-Naturwissenschaftliche Fakultät) Schug, Franz; Frantz, David; van der Linden, Sebastian; Hostert, PatrickGridded 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 studies) and building type datasets, all created from freely available, temporally and globally consistent Copernicus Sentinel-1 and Sentinel-2 data. We first produced and validated a nation-wide dataset of predominant residential and non-residential building types. We then examined the impact of different weighting layers from density, type and height on top-down dasymetric mapping quality across scales. We finally performed a nation-wide bottom-up population estimate based on the three datasets. We found that integrating building types into dasymetric mapping is helpful at fine scale, as population is not redistributed to non-residential areas. Building density improved the overall quality of population estimates at all scales compared to using a binary building layer. Most importantly, we found that the combined use of density and height, i.e. volume, considerably increased mapping quality in general and with regard to regional discrepancy by largely eliminating systematic underestimation in dense agglomerations and overestimation in rural areas. We also found that building density, type and volume, together with living floor area per capita, are suitable to produce accurate large-area bottom-up population estimates.Publication 2023-03-03ZeitschriftenartikelHigh-resolution data and maps of material stock, population, and employment in Austria from 1985 to 2018(Mathematisch-Naturwissenschaftliche Fakultät) Schug, Franz; Wiedenhofer, Dominik; Haberl, Helmut; Frantz, David; Virág, Doris; van der Linden, Sebastian; Hostert, PatrickHigh-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 single years, data covering entire countries with high resolution, or using remote-sensing data are rare. Instead, they often have local extent (e.g., [1]), are lower resolution (e.g., [2]), or are based on other geospatial data (e.g., [3]). We here present data on the material stocks in three types of buildings (commercial and industrial, single- and multifamily houses) and three types of infrastructures (roads, railways, other infrastructures) for a 33-year time series for Austria at a spatial resolution of 30 m. The article also presents data on population and employment in Austria for the same time period, at the same spatial resolution. Data were derived with the same method applied in a recent study for Germany [4].Publication 2022-10-25ZeitschriftenartikelHigh-resolution mapping of 33 years of material stock and population growth in Germany using Earth Observation data(Mathematisch-Naturwissenschaftliche Fakultät) Schug, Franz; Frantz, David; Wiedenhofer, Dominik; Haberl, Helmut; Virág, Doris; van der Linden, Sebastian; Hostert, PatrickGlobal 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.Publication 2021-02-17ZeitschriftenartikelImpacts of cutting frequency and position to tree line on herbage accumulation in silvopastoral grassland reveal potential for grassland conservation based on land use and cover information(Mathematisch-Naturwissenschaftliche Fakultät) Schmiedgen, Andrea; Komainda, Martin; Kowalski, Katja; Hostert, Patrick; Tonn, Bettina; Kayser, Manfred; Isselstein, JohannesIn agricultural grassland, high herbage utilisation efficiency (HEFF), which is the proportion of gross live-green herbage production that is utilised before entering senescence, is ensured by frequent defoliation. The decision upon which defoliation frequency to apply depends on the farming intensity. Assuming a reduced total herbage accumulation near trees in silvopastoral systems, frequent defoliations with high HEFF become less worthwhile—at least in specific spatial configurations. This makes an extensive management near trees an interesting option because it promotes other grassland-related ecosystem services such as biodiversity. The present study first analysed the interaction between defoliation frequency and position to trees on the total, dead and live herbage accumulation and the HEFF at two silvopastoral sites with short-rotation coppices in Germany. In addition, the total grassland–tree interface in Germany was assessed from land use and land cover maps of Germany based on satellite data to approximate the potential of grassland extensification near trees. The total herbage accumulation near trees declined by up to 41% but the HEFF was not affected by the position. Consequently, any intensification is not paid-off by adequate productivity and herbage quality in terms of HEFF and tree-related losses in herbage accumulation are expected up to a distance of 4.5–6 m. Applying a 4.5 m border on satellite data, we found that up to 4.4% (approximately 2200 km2) of the total grassland area in Germany is at a tree interface and potentially suitable for extensification. These findings indicate substantial potential for biodiversity conservation in grasslands with low trade-off for high-quality yield.Publication 2020-01-13ZeitschriftenartikelImpacts of Public and Private Sector Policies on Soybean and Pasture Expansion in Mato Grosso—Brazil from 2001 to 2017(Mathematisch-Naturwissenschaftliche Fakultät) Picoli, Michelle; Rorato Vitor, Ana Claudia; Leitão, Pedro; Camara, Gilberto; Marinho Maciel, Adeline; Hostert, Patrick; Sanches, IedaDemand for agricultural exports in Brazil has stimulated the expansion of crop production and cattle raising, which has caused environmental impacts. In response, Brazil developed public policies such as the new Forest Code (FC) and supply chain arrangements such the Soy and the Cattle Moratoriums. This paper analyzes the effectiveness of these policies, considering the trajectories of agricultural expansion in the state of Mato Grosso in three years: 2005 (pre-moratorium and before the new FC), 2010 (post-moratorium and before the new FC) and 2017 (post-moratorium and post-new FC). Our analysis uses a detailed land use change data for both the Amazon and Cerrado biomes in Mato Grosso. In all the years considered, soybean expansion occurred in consolidated production areas and by conversion of pastures. Pasture expansion is influenced by existence of pastures nearby, by areas of secondary vegetation and deforestation. Our data and models show the effectiveness of public policies and private arrangements to reduce direct conversion from forests to crop production. However, our results also provide evidence that soybean expansion has caused indirect impacts by replacing pasture areas and causing pasture expansion elsewhere. Evidence from our work indicates that Brazil needs broader-ranging land use policies than what was done in the 2010s to be able to reach the land use goals stated in its Nationally Determined Contribution (NDC) to the Paris Agreement.Publication 2016Teil eines BuchesLand Use Competition(Integrative Forschungsinstitute) Niewöhner, Jörg; Bruns, Antje; Haberl, Helmut; Hostert, Patrick; Krueger, Patrick; Lauk, Christian; Lutz, Juliana; Müller, Daniel; Nielsen, Jonas ØstergaardThis chapter introduces competition as a heuristic concept to analyse how specific land use practices establish themselves against possible alternatives. We briefly outline the global importance of land use practices as the material and symbolic basis for people’s livelihoods, particularly the provision of food security and well-being. We chart the development over time from research on land cover towards research on drivers of land use practices as part of an integrated land systems science. The increasingly spatially, temporally and functionally distributed nature of these drivers poses multiple challenges to research on land use practices. We propose the notion of ‘competition’ to respond to some of these challenges and to better understand how alternative land use practices are negotiated. We conceive of competition as a relational concept. Competition asks about agents in relation to each other, about the mode or the logic in which these relations are produced and about the material environments, practices and societal institutions through which they are mediated. While this has centrally to do with markets and prices, we deliberately open the concept to embrace more than economic perspectives. As such competition complements a broadening of analytical attention from the ‘who’, ‘what’ and ‘when’ to include prominently the ‘how’ and ‘why’ of particular land use practices and the question to whom this matters and ought to matter. We suggest that competition is an analytically productive concept, because it does not commit the analyst to a particular epistemological stance. It addresses reflexivity and feed-back, emergence and downward causation, history and response rates—concepts that all carry very different conceptual and analytical connotations in different disciplines. We propose to make these differences productive by putting them alongside each other through the notion of competition. Last not least, the heuristic lens of competition affords the combination of empirical and normative aspects, thus addressing land use practices in material, social and ethical terms.