V
Volker C. Radeloff
Researcher at University of Wisconsin-Madison
Publications - 347
Citations - 22574
Volker C. Radeloff is an academic researcher from University of Wisconsin-Madison. The author has contributed to research in topics: Species richness & Land use, land-use change and forestry. The author has an hindex of 76, co-authored 317 publications receiving 18345 citations. Previous affiliations of Volker C. Radeloff include Amherst College.
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Journal ArticleDOI
Forest disturbances, forest recovery, and changes in forest types across the Carpathian ecoregion from 1985 to 2010 based on Landsat image composites
Patrick Griffiths,Tobias Kuemmerle,Matthias Baumann,Volker C. Radeloff,Ioan Vasile Abrudan,Juraj Lieskovsky,Catalina Munteanu,Katarzyna Ostapowicz,Katarzyna Ostapowicz,Patrick Hostert +9 more
TL;DR: In this article, the authors analyzed changes in forest types, forest disturbances, and forest recovery for the Carpathian ecoregion in Eastern Europe using the Landsat archive.
Journal ArticleDOI
Remote sensing of vegetation 3-D structure for biodiversity and habitat: Review and implications for lidar and radar spaceborne missions
Kathleen M. Bergen,Scott J. Goetz,Ralph Dubayah,Geoffrey M. Henebry,Carolyn T. Hunsaker,Marc L. Imhoff,Ross Nelson,Geoffrey G. Parker,Volker C. Radeloff +8 more
TL;DR: In this article, a review of the state of the art for incorporating information on vegetation 3D structure into biodiversity and habitat science and management approaches, with emphasis on use of lidar and radar data.
Journal ArticleDOI
Mapping abandoned agriculture with multi-temporal MODIS satellite data
Camilo Alcántara,Tobias Kuemmerle,Tobias Kuemmerle,Alexander V. Prishchepov,Volker C. Radeloff +4 more
TL;DR: In this paper, the authors used Support Vector Machines (SVM) to classify abandoned agriculture for one MODIS tile in Eastern Europe, where abandoned agriculture was widespread and showed that it is possible to map abandoned agriculture from MODIS data with an overall classification accuracy of 65%.
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Land cover mapping of large areas using chain classification of neighboring Landsat satellite images
Jan Knorn,Andreas Rabe,Volker C. Radeloff,Tobias Kuemmerle,Tobias Kuemmerle,Jacek Kozak,Patrick Hostert +6 more
TL;DR: It is noted that chain classification can only be applied when land cover classes are well represented in the overlap area of neighboring Landsat scenes, but as long as this constraint is met, chain classification is a powerful approach for large area land cover classifications, especially in areas of varying training data availability.
Journal ArticleDOI
Eastern Europe's forest cover dynamics from 1985 to 2012 quantified from the full Landsat archive
Peter Potapov,Svetlana Turubanova,Alexandra Tyukavina,Alexander Krylov,Jessica L. McCarty,Volker C. Radeloff,Matthew C. Hansen +6 more
TL;DR: In this article, the authors developed an algorithm to simultaneously process data from different Landsat platforms and sensors (TM and ETM+) to map annual forest cover loss and decadal forest cover gain.