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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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The wildland-urban interface in the United States

TL;DR: A spatially detailed assessment of the wildland-urban interface across the United States is conducted to provide a framework for scientific inquiries into housing growth effects on the environment and to inform both national policymakers and local land managers about the WUI and associated issues.
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Projected land-use change impacts on ecosystem services in the United States.

TL;DR: This work project land-use change from 2001 to 2051 for the contiguous United States under two scenarios reflecting continuation of 1990s trends and high crop demand more reflective of the recent past, and three policy alternatives that provide incentives to maintain and expand forest cover, conserve natural habitats, and limit urban sprawl.
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Rapid growth of the US wildland-urban interface raises wildfire risk

TL;DR: The wildland-urban interface (WUI) is the area where houses and wildland vegetation meet or intermingle, and where wildfire problems are most pronounced, and grew rapidly from 1990 to 2010, making it the fastest-growing land use type in the conterminous United States.
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Human influence on california fire regimes

TL;DR: Understanding wildfire as a function of the spatial arrangement of ignitions and fuels on the landscape, in addition to nonlinear relationships, will be important to fire managers and conservation planners because fire risk may be related to specific levels of housing density that can be accounted for in land use planning.
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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.