Feasibility of tundra vegetation height retrieval from Sentinel-1 and Sentinel-2 data-Reference-Cited by-同舟云学术

Feasibility of tundra vegetation height retrieval from Sentinel-1 and Sentinel-2 data

Published:2020-02 Issue: Volume:237 Page:111515
ISSN:0034-4257
Container-title:Remote Sensing of Environment
language:en
Short-container-title:Remote Sensing of Environment

Author:

Bartsch Annett,Widhalm Barbara,Leibman Marina,Ermokhina Ksenia,Kumpula Timo,Skarin Anna,Wilcox Evan J.,Jones Benjamin M.,Frost Gerald V.,Höfler Angelika,Pointner Georg

Funder

Horizon 2020

Academy of Finland

National Science Foundation

National Fish and Wildlife Foundation

National Aeronautics and Space Administration

Austrian Science Fund

Russian Foundation for Basic Research

European Space Agency

Publisher

Elsevier BV

Subject

Computers in Earth Sciences,Geology,Soil Science

Reference89 articles.

1. Methods to remove the border noise from Sentinel-1 Synthetic Aperture Radar data: implications and importance for time-series analysis;Ali;IEEE J. Select. Topics. Appl. Earth Observ. Remote Sens.,2018

2. Activation of cryogenic processes in central Yamal as a result of regional and local change in climate and thermal state of permafrost;Babkina;Russ. Meteorol. Hydrol.,2019

3. Characterizing scattering behaviour and assessing potential for classification of arctic shore and near-shore land covers with fine quad-pol RADARSAT-2 data;Banks;Can. J. Remote Sens.,2014

4. Land cover mapping in northern high latitude permafrost regions with satellite data: achievements and remaining challenges;Bartsch;Remote Sens.,2016

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