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Improving forest age estimation to understand subtropical forest regrowth dynamics using deep learning image segmentation of time‐series historical aerial photographs

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Bibliographic Details
Published in:Remote Sensing in Ecology and Conservation
Format: Online Article RSS Article
Published: 2025
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container_title Remote Sensing in Ecology and Conservation
description
discipline_display Natural Sciences
discipline_facet Natural Sciences
format Online Article
RSS Article
genre Journal Article
id rss_article:22161
institution FRELIP
journal_source_facet Remote Sensing in Ecology and Conservation
publishDate 2025
publishDateSort 2025
record_format rss_article
spellingShingle Improving forest age estimation to understand subtropical forest regrowth dynamics using deep learning image segmentation of time‐series historical aerial photographs
Zoology
Natural Sciences — Life Sciences
Natural Sciences
sub_discipline_display Natural Sciences — Life Sciences
sub_discipline_facet Natural Sciences — Life Sciences
subject_display Zoology
Natural Sciences — Life Sciences
Natural Sciences
Zoology
Natural Sciences — Life Sciences
Natural Sciences
subject_facet Zoology
Natural Sciences — Life Sciences
Natural Sciences
title Improving forest age estimation to understand subtropical forest regrowth dynamics using deep learning image segmentation of time‐series historical aerial photographs
title_auth Improving forest age estimation to understand subtropical forest regrowth dynamics using deep learning image segmentation of time‐series historical aerial photographs
title_full Improving forest age estimation to understand subtropical forest regrowth dynamics using deep learning image segmentation of time‐series historical aerial photographs
title_fullStr Improving forest age estimation to understand subtropical forest regrowth dynamics using deep learning image segmentation of time‐series historical aerial photographs
title_full_unstemmed Improving forest age estimation to understand subtropical forest regrowth dynamics using deep learning image segmentation of time‐series historical aerial photographs
title_short Improving forest age estimation to understand subtropical forest regrowth dynamics using deep learning image segmentation of time‐series historical aerial photographs
title_sort improving forest age estimation to understand subtropical forest regrowth dynamics using deep learning image segmentation of time‐series historical aerial photographs
topic Zoology
Natural Sciences — Life Sciences
Natural Sciences
url https://zslpublications.onlinelibrary.wiley.com/doi/10.1002/rse2.70042?af=R