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Research on Leaf Area Index Inversion Based on LESS 3D Radiative Transfer Model and Machine Learning...

Research on Leaf Area Index Inversion Based on LESS 3D Radiative Transfer Model and Machine Learning...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_7aa95db653544e19aa841367e00b3a08

Research on Leaf Area Index Inversion Based on LESS 3D Radiative Transfer Model and Machine Learning Algorithms

About this item

Full title

Research on Leaf Area Index Inversion Based on LESS 3D Radiative Transfer Model and Machine Learning Algorithms

Publisher

Basel: MDPI AG

Journal title

Remote sensing (Basel, Switzerland), 2024-10, Vol.16 (19), p.3627

Language

English

Formats

Publication information

Publisher

Basel: MDPI AG

More information

Scope and Contents

Contents

The Leaf Area Index (LAI) is a critical parameter that sheds light on the composition and function of forest ecosystems. Its efficient and rapid measurement is essential for simulating and estimating ecological activities such as vegetation productivity, water cycle, and carbon balance. In this study, we propose to combine high-resolution GF-6 2 m...

Alternative Titles

Full title

Research on Leaf Area Index Inversion Based on LESS 3D Radiative Transfer Model and Machine Learning Algorithms

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_7aa95db653544e19aa841367e00b3a08

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_7aa95db653544e19aa841367e00b3a08

Other Identifiers

ISSN

2072-4292

E-ISSN

2072-4292

DOI

10.3390/rs16193627

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