A new view on EU agricultural landscapes: Quantifying patchiness to assess farmland heterogeneity
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作者:
Weissteiner, Christof J.
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Commiss European Communities, Joint Res Ctr, Inst Environm & Sustainabil, I-21027 Ispra, VA, ItalyCommiss European Communities, Joint Res Ctr, Inst Environm & Sustainabil, I-21027 Ispra, VA, Italy
Weissteiner, Christof J.
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Garcia-Feced, Celia
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Commiss European Communities, Joint Res Ctr, Inst Environm & Sustainabil, I-21027 Ispra, VA, ItalyCommiss European Communities, Joint Res Ctr, Inst Environm & Sustainabil, I-21027 Ispra, VA, Italy
Garcia-Feced, Celia
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Paracchini, Maria Luisa
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Commiss European Communities, Joint Res Ctr, Inst Environm & Sustainabil, I-21027 Ispra, VA, ItalyCommiss European Communities, Joint Res Ctr, Inst Environm & Sustainabil, I-21027 Ispra, VA, Italy
Paracchini, Maria Luisa
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机构:
[1] Commiss European Communities, Joint Res Ctr, Inst Environm & Sustainabil, I-21027 Ispra, VA, Italy
Mapping and assessment of ecosystem services in agricultural landscapes as required by the EU biodiversity policy need a better characterization of the given landscape typology according to its ecological and cultural values. Such need should be accommodated by a better discrimination of the landscape characteristics linked to the capacity of providing ecosystem services and socio-cultural benefits. Often, these key variables depend on the degree of farmland heterogeneity and landscape patterns. We employed segmentation and landscape metrics (edge density and image texture respectively), derived from a pan-European multi-temporal and multi-spectral remote sensing dataset, to generate a consistent European indicator of farmland heterogeneity, the Farmland Heterogeneity Indicator (FHI). We mapped five degrees of FHI on a wall-to-wall basis (250 m spatial resolution) over European agricultural landscapes including natural grasslands. Image texture led to a clear improvement of the indicator compared to the pure application of Edge Density, in particular to a better detection of small patches. In addition to deriving a qualitative indicator we attributed an approximate patch size to each class, allowing an indicative assessment of European field sizes. Based on CORINE land cover, we identified pastures and heterogeneous land cover classes as classes with the highest degree of FHI, while agroforestry and olive groves appeared less heterogeneous on average. We performed a verification based on a continental and regional scale, which resulted in general good agreement with independently derived data. (C) 2015 The Authors. Published by Elsevier Ltd.
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Carleton Univ, Geomat & LandsCape Ecol Res Lab GLEL, 1125 Colonel By Dr, Ottawa, ON K1S 5B6, Canada
POB 520, Port Rowan, ON N0E 1M0, CanadaCarleton Univ, Geomat & LandsCape Ecol Res Lab GLEL, 1125 Colonel By Dr, Ottawa, ON K1S 5B6, Canada
Monck-Whipp, Liv
Martin, Amanda E.
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Carleton Univ, Geomat & LandsCape Ecol Res Lab GLEL, 1125 Colonel By Dr, Ottawa, ON K1S 5B6, CanadaCarleton Univ, Geomat & LandsCape Ecol Res Lab GLEL, 1125 Colonel By Dr, Ottawa, ON K1S 5B6, Canada
Martin, Amanda E.
Francis, Charles M.
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Environm & Climate Change Canada, Natl Wildlife Res Ctr, Canadian Wildlife Serv, 1125 Colonel By Dr, Ottawa, ON K1A 0H3, CanadaCarleton Univ, Geomat & LandsCape Ecol Res Lab GLEL, 1125 Colonel By Dr, Ottawa, ON K1S 5B6, Canada
Francis, Charles M.
Fahrig, Lenore
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Carleton Univ, Geomat & LandsCape Ecol Res Lab GLEL, 1125 Colonel By Dr, Ottawa, ON K1S 5B6, CanadaCarleton Univ, Geomat & LandsCape Ecol Res Lab GLEL, 1125 Colonel By Dr, Ottawa, ON K1S 5B6, Canada