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Tobias Kuemmerle

Researcher at Humboldt University of Berlin

Publications -  267
Citations -  19605

Tobias Kuemmerle is an academic researcher from Humboldt University of Berlin. The author has contributed to research in topics: Land use & Land use, land-use change and forestry. The author has an hindex of 72, co-authored 240 publications receiving 15200 citations. Previous affiliations of Tobias Kuemmerle include Montana State University & Potsdam Institute for Climate Impact Research.

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A review of the application of optical and radar remote sensing data fusion to land use mapping and monitoring

TL;DR: This study reviewed 112 studies on fusing optical and radar data, which offer unique spectral and structural information, for land cover and use assessments, and concluded that fusion improved results compared to using single data sources.
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Land management and land-cover change have impacts of similar magnitude on surface temperature

TL;DR: In this paper, the authors investigated the biophysical effects of temperate land-management changes and revealed a net warming effect of similar magnitude to that driven by changing land cover, and found that potential surface cooling from increased albedo is typically offset by warming from decreased sensible heat fluxes.
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Mapping farmland abandonment and recultivation across Europe using MODIS NDVI time series.

TL;DR: In this paper, the authors developed a methodology to map active and fallow land using MODIS Normalized Differenced Vegetation Index (NDVI) time series and provided the first European-wide map of the extent of abandoned farmland (cropland and grassland) and recultivation.
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Land Sparing Versus Land Sharing: Moving Forward

TL;DR: In this paper, a framework has been proposed that distinguishes between the integration (land sharing) and separation (land sparing) of conservation and production to address the challenges of biodiversity conservation and commodity production.
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Patterns and drivers of post-socialist farmland abandonment in Western Ukraine

TL;DR: In this article, the authors map post-socialist farmland abandonment in Western Ukraine using Landsat images from 1986 to 2008, and identify spatial determinants of abandonment using a combination of best-subsets linear regression models and hierarchical partitioning.