Hyper-temporal remote sensing helps in relating epiphyllous liverworts and evergreen forests-Reference-Cited by-同舟云学术

Hyper-temporal remote sensing helps in relating epiphyllous liverworts and evergreen forests

Published:2012-08-03 Issue:2 Volume:24 Page:214-226
ISSN:1100-9233
Container-title:Journal of Vegetation Science
language:en
Short-container-title:J Veg Sci

Author:

Jiang Yanbin,de Bie C.A.J.M.¹,Wang Tiejun¹,Skidmore A.K.¹,Liu Xuehua²,Song Shanshan³,Shao Xiaoming³

Affiliation:

1. Department of Natural Resources; Faculty of Geo-information Science and Earth Observation (ITC); University of Twente; PO Box 217; 7500; AE; Enschede; The Netherlands

2. School of Environmental Science and Engineering; Tsinghua University; Beijing; 100084; China

3. College of Biological Sciences; China Agricultural University; Beijing; 100193; China

Publisher

Wiley

Subject

Plant Science,Ecology

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1111/j.1654-1103.2012.01453.x/fullpdf

Reference66 articles.

1. Patch size and isolation effects on epiphytic and epiphyllous bryophytes in the fragmented Brazilian Atlantic forest;Alvarenga;Biological Conservation,2007

2. Relations between regional-local habitat loss and metapopulation properties of Epiphyllous Bryophytes in the Brazilian Atlantic Forest;Alvarenga;Biotropica,2009

3. A new epiphyllous species of Cololejeunea (Lejeuneaceae) from India;Asthana;Cryptogamie Bryologie,2010

4. Land cover classification using moderate resolution imaging spectrometer-enhanced vegetation index time-series data and self-organizing map neural network in inner Mongolia, China;Bagan;Journal of Applied Remote Sensing,2007

5. A ground-validated NDVI dataset for monitoring vegetation dynamics and mapping phenology in Fennoscandia and the Kola peninsula;Beck;International Journal of Remote Sensing,2007

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