Salt marsh carbon stock estimation using deep learning with Sentinel-1 SAR of the Yangtze River estuary, China-Reference-Cited by-同舟云学术

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Salt marsh carbon stock estimation using deep learning with Sentinel-1 SAR of the Yangtze River estuary, China

Published:2024-09 Issue: Volume:133 Page:104138
ISSN:1569-8432
Container-title:International Journal of Applied Earth Observation and Geoinformation
language:en
Short-container-title:International Journal of Applied Earth Observation and Geoinformation

Author:

Li Yuying^ORCID,Yuan Lina^ORCID,Song Zijiang^ORCID,Yu Shanshan,Zhang Xiaowen^ORCID,Tian Bo^ORCID,Liu Min

Publisher

Elsevier BV

Reference69 articles.

1. A rule-based classification method for mapping saltmarsh land-cover in south-eastern Bangladesh from landsat-8 OLI;Alam;Can. J. Remote. Sens.,2021

2. Long term carbon storage potential and CO2 sink strength of a restored salt marsh in new jersey;Artigas;Agricult. Forest Meteorol.,2015

3. Assessment and prediction of carbon sequestration using Markov chain and InVEST model in Sariska tiger reserve, India;Babbar;J. Clean. Prod.,2021

4. Mapping of crop types and crop sequences with combined time series of sentinel-1, sentinel-2 and landsat 8 data for Germany;Blickensdörfer;Remote Sens. Environ.,2022

5. Image classification using random forests and ferns;Bosch,2007

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