Reducing vertical bias and error in tidal marsh digital elevation models with machine learning and LiDAR derivatives-Reference-Cited by-同舟云学术

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Reducing vertical bias and error in tidal marsh digital elevation models with machine learning and LiDAR derivatives

Published:2023-09 Issue: Volume:291 Page:108442
ISSN:0272-7714
Container-title:Estuarine, Coastal and Shelf Science
language:en
Short-container-title:Estuarine, Coastal and Shelf Science

Author:

Warner Daniel L.^ORCID,Callahan John A.^ORCID,McKenna Thomas E.^ORCID,Medlock Catherine

Funder

Delaware Sea Grant

NOAA Office for Coastal Management

Publisher

Elsevier BV

Subject

Aquatic Science,Oceanography

Reference42 articles.

1. Temporal variation of accumulation rates on a natural salt marsh in the 20th century - the impact of sea level rise and increased inundation frequency;Andersen;Mar. Geol.,2011

2. Deepdive: Deep Learning for General Purpose. R Package Version;Balakrishnan,2021

3. The value of estuarine and coastal ecosystem services;Barbier;Ecol. Monogr.,2011

4. New measures for assessing model equilibrium and prediction mismatch in species distribution models;Barbosa;Divers. Distrib.,2013

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Characterizing low‐lying coastal upland forests to predict future landward marsh expansion;Ecosphere;2024-06

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