Evidence map›Paper›PMID 42299490›Full record

ArticleGlobal change biology2026

Satellite Remote Sensing of Alpine Vegetation Dynamics: Challenges and Perspectives.

Arthur Bayle

Abstract read
In one paragraph

Article in Global change biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Arthur BayleUniv. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, LECA, Grenoble, France.ORCID 0000-0002-3442-0789

Funding

Agence Nationale de la Recherche ANR-20-CE32-0002Agence Nationale de la Recherche IA-10-LABX-0056Agence Nationale de la Recherche Labex OSUG@2020Zone Atelier Alpes project HERITAGE
6 · The paper itself

Abstract

Satellite greening has become a key tool for monitoring alpine vegetation change, but a positive vegetation-index trend is not an ecological observation in itself. This perspective shows that interpreting alpine greening requires addressing two sequential challenges: methodological complexity, which can bias trends during image processing, and phenomenological complexity, because different ecological processes can produce similar spectral signals. Progress now depends less on producing more greening maps than on linking robust satellite trends to ground-based ecological processes.

Indexed as

EcosystemEnvironmental MonitoringRemote Sensing TechnologySatellite Imageryalpine ecosystemsattributionbiasgreeningLandsatmountainsreproducible workflows

Identifiers

PMID42299490
PMCPMC13270260

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.