Remote sensing of vegetation and land-cover change in Arctic Tundra Ecosystems

2004 ◽  
Vol 89 (3) ◽  
pp. 281-308 ◽  
Author(s):  
Douglas A Stow ◽  
Allen Hope ◽  
David McGuire ◽  
David Verbyla ◽  
John Gamon ◽  
...  
2013 ◽  
Vol 19 ◽  
pp. 912-921 ◽  
Author(s):  
M.Minwer Alkharabsheh ◽  
T.K. Alexandridis ◽  
G. Bilas ◽  
N. Misopolinos ◽  
N. Silleos

2021 ◽  
Vol 125 ◽  
pp. 107447 ◽  
Author(s):  
Rehana Rasool ◽  
Abida Fayaz ◽  
Mifta ul Shafiq ◽  
Harmeet Singh ◽  
Pervez Ahmed

2021 ◽  
Vol 13 (19) ◽  
pp. 3951
Author(s):  
Kim André Vanselow ◽  
Harald Zandler ◽  
Cyrus Samimi

Greening and browning trends in vegetation have been observed in many regions of the world in recent decades. However, few studies focused on dry mountains. Here, we analyze trends of land cover change in the Western Pamirs, Tajikistan. We aim to gain a deeper understanding of these changes and thus improve remote sensing studies in dry mountainous areas. The study area is characterized by a complex set of attributes, making it a prime example for this purpose. We used generalized additive mixed models for the trend estimation of a 32-year Landsat time series (1988–2020) of the modified soil adjusted vegetation index, vegetation data, and environmental and socio-demographic data. With this approach, we were able to cope with the typical challenges that occur in the remote sensing analysis of dry and mountainous areas, including background noise and irregular data. We found that greening and browning trends coexist and that they vary according to the land cover class, topography, and geographical distribution. Greening was detected predominantly in agricultural and forestry areas, indicating direct anthropogenic drivers of change. At other sites, greening corresponds well with increasing temperature. Browning was frequently linked to disastrous events, which are promoted by increasing temperatures.


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