Will remote sensing shape the next generation of species distribution models?-Reference-Cited by-同舟云学术

Will remote sensing shape the next generation of species distribution models?

Published:2015-10 Issue:1 Volume:1 Page:4-18
ISSN:2056-3485
Container-title:Remote Sensing in Ecology and Conservation
language:en
Short-container-title:Remote Sens Ecol Conserv

Author:

He Kate S.¹,Bradley Bethany A.²,Cord Anna F.³,Rocchini Duccio⁴,Tuanmu Mao‐Ning⁵,Schmidtlein Sebastian⁶,Turner Woody⁷,Wegmann Martin⁸⁹,Pettorelli Nathalie¹⁰

Affiliation:

1. Department of Biological Sciences Murray State University Murray Kentucky 42071

2. Department of Environmental Conservation University of Massachusetts Amherst Massachusetts 01003

3. Department of Computational Landscape Ecology Helmholtz Centre for Environmental Research – UFZ Permoserstraße 15 04318 Leipzig Germany

4. GIS and Remote Sensing Unit Department of Biodiversity and Molecular Ecology Research and Innovation Center Fondazione Edmund Mach Via E. Mach 1 S. Michele all'Adige Trento 38010 Italy

5. Department of Ecology and Evolutionary Biology Yale University New Haven Connecticut 06520

6. Institute of Geography and Geoecology Karlsruhe Institute of Technology (KIT) 76131 Karlsruhe Germany

7. Earth Science Division NASA Washington District of Columbia

8. Department of Remote Sensing University of Wuerzburg 97074 Wurzburg Germany

9. CEOS Biodiversity at German Remote Sensing Data Centre German Aerospace Centre DLR 82234 Wessling Germany

10. Institute of Zoology Zoological Society of London Regent's Park London NW1 4RY UK

Publisher

Wiley

Subject

Nature and Landscape Conservation,Computers in Earth Sciences,Ecology,Ecology, Evolution, Behavior and Systematics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/rse2.7

Reference147 articles.

1. Urban tree species mapping using hyperspectral and lidar data fusion

2. Lightweight unmanned aerial vehicles will revolutionize spatial ecology

3. The role of environmental context in mapping invasive plants with hyperspectral image data

4. Habitat suitability modelling of an invasive plant with advanced remote sensing data

5. Validation of species-climate impact models under climate change

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