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HighlightsGlobal patterns of land use intensity are poorly understood, particularly in the developing world.The multidimensionality of land use intensity should be considered by jointly using input, output, and system metrics.A range of cropland intensity metrics exist, but existing data are often uncertain.Large data gaps remain for grazing and forestry intensity.Research priorities should include first, better integration of satellite-based and ground based data, second, validating and better documentation of datasets, and third, creation of consistent time series.

Assessing changes in the extent and management intensity of land use is crucial to understanding land-system dynamics and their environmental and social outcomes. Yet, changes in the spatial patterns of land management intensity, and thus how they might relate to changes in the extent of land uses, remains unclear for many world regions. We compiled and analyzed high-resolution, spatiallyexplicit land-use change indicators capturing changes in both the extent and management intensity of cropland, grazing land, forests, and urban areas for all of Europe for the period 1990-2006. Based on these indicators, we identified hotspots of change and explored the spatial concordance of area versus intensity changes. We found a clear East-West divide with regard to agriculture, with stronger cropland declines and lower management intensity in the East compared to the West. Yet, these patterns were not uniform and diverging patterns of intensification in areas highly suitable for farming, and disintensification and cropland contraction in more marginal areas emerged. Despite the moderate overall rates of change, many regions in Europe fell into at least one land-use change hotspot during 1990-2006, often related to a spatial reorganization of land use (i.e., co-occurring area decline and intensification or co-occurring area increase and disintensification). Our analyses highlighted the diverse spatial patterns and heterogeneity of land-use changes in Europe, and the importance of jointly considering changes in the extent and management intensity of land use, as well as feedbacks among land-use sectors. Given this spatial differentiation of land-use change, and thus its environmental impacts, spatially-explicit assessments of land-use dynamics are important for context-specific, regionalized land-use policy making.

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Global agricultural production will likely need to increase in the future due to population growth, changing diets, and the rising importance of bioenergy. Intensifying already existing cropland is often considered more sustainable than converting more natural areas. Unfortunately, our understanding of cropping patterns and intensity is weak, especially at broad geographic scales. We characterized and mapped cropping systems in Europe, a region containing diverse cropping systems, using four indicators: (a) cropping frequency (number of cropped years), (b) multi-cropping (number of harvests per year), (c) fallow cycles, and (d) crop duration ratio (actual time under crops) based on the MODIS Normalized Difference Vegetation Index (NDVI) time series from 2000 to 2012. Second, we used these cropping indicators and self-organizing maps to identify typical cropping systems. The resulting six clusters correspond well with other indicators of agricultural intensity (e.g., nitrogen input, yields) and reveal substantial differences in cropping intensity across Europe. Cropping intensity was highest in Germany, Poland, and the eastern European Black Earth regions, characterized by high cropping frequency, multi-cropping and a high crop duration ratio. Contrarily, we found lowest cropping intensity in eastern Europe outside the Black Earth region, characterized by longer fallow cycles. Our approach highlights how satellite image time series can help to characterize spatial patterns in cropping intensity-information that is rarely surveyed on the ground and commonly not included in agricultural statistics: our clustering approach also shows a way forward to reduce complexity when measuring multiple indicators. The four cropping indicators we used could become part of continental-scale agricultural monitoring in order to identify target regions for sustainable intensification, where trade-offs between intensification and the environmental should be explored.

Knowledge of the spatial distribution of agricultural abandonment following the collapse of the Soviet Union is highly uncertain. To help improve this situation, we have developed a new map of arable and abandoned land for 2010 at a 10 arc-second resolution. We have fused together existing land cover and land use maps at different temporal and spatial scales for the former Soviet Union (fSU) using a training data set collected from visual interpretation of very high resolution (VHR) imagery. We have also collected an independent validation data set to assess the map accuracy. The overall accuracies of the map by region and country, i.e. Caucasus, Belarus, Kazakhstan, Republic of Moldova, Russian Federation and Ukraine, are 90±2%, 84±2%, 92±1%, 78±3%, 95±1%, 83±2%, respectively. This new product can be used for numerous applications including the modelling of biogeochemical cycles, land-use modelling, the assessment of trade-offs between ecosystem services and land-use potentials (e.g., agricultural production), among others.

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The world's grasslands, both natural and managed, provide food and many non-provisioning ecosystem services. Although most grasslands today are used for livestock grazing or fodder production, little is known about the spatial patterns of grassland management intensity, especially at broad geographic scales. Using the European Union as a case study, we mapped mowing frequency as a key indicator of grassland management intensity. We used MODIS NDVI time series from 2000-2012 to map mowing frequency using a spline-fitting algorithm that detects up to five mowing events within a single growing season. We combined mowing frequency maps with existing maps of livestock distribution and grassland management frequency to identify clusters of similar grassland management intensity across Europe. Our results highlight generally high mowing frequency in areas of high grassland productivity, especially in Ireland, northern and central France, and the Netherlands. Our analyses also show distinct clusters of similar grassland management, representing different grassland-management intensity regimes. High intensity clusters occurred particularly in western and southern Europe, especially in Ireland, in the northern and central parts of France and Spain, and the Netherlands but also in northern and southern Germany and eastern Poland. Low intensity clusters were found mainly in central and eastern Europe and in mountainous regions but also in Extremadura in Spain, Wales and western England (UK). Generally, our analyses emphasize the usefulness of jointly using satellite time series and agricultural statistics to monitor grassland intensity across broad geographic extents. Our maps allow for a new, spatially-detailed view of management intensity in grassland systems and may help to improve regionally targeted land-use and conservation policies.