Predicting species diversity in agricultural environments using Landsat TM imagery-Reference-Cited by-同舟云学术

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Predicting species diversity in agricultural environments using Landsat TM imagery

Published:2014-03 Issue: Volume:144 Page:214-225
ISSN:0034-4257
Container-title:Remote Sensing of Environment
language:en
Short-container-title:Remote Sensing of Environment

Author:

Duro Dennis C.,Girard Jude,King Douglas J.,Fahrig Lenore,Mitchell Scott,Lindsay Kathryn,Tischendorf Lutz

Funder

Natural Sciences and Engineering Research Council of Canada (NSERC) Strategic Project

Canada Foundation for Innovation

Environment Canada (EC)

Agriculture and Agri-Food Canada (AAFC)

Publisher

Elsevier BV

Subject

Computers in Earth Sciences,Geology,Soil Science

Reference119 articles.

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2. Local indicators of spatial association—LISA;Anselin;Geographical Analysis,1995

3. Uninformative parameters and model selection using Akaike's information criterion;Arnold;The Journal of Wildlife Management,2010

4. Ecological research needs from multiangle remote sensing data;Asner;Remote Sensing of Environment,1998

5. Geostatistical modelling of regional bird species richness: Exploring environmental proxies for conservation purpose;Bacaro;Biodiversity and Conservation,2011

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