Evidence map›Paper›PMID 39281018›Full record

ArticleData in brief2024

Snow cover phenology dataset over global mountain regions from 2000 to 2023.

Claudia Notarnicola

Abstract read
In one paragraph

Article in Data in brief, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Claudia NotarnicolaEurac Research, Institute for Earth Observation, Viale Druso 1, 39100 Bolzano, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Monitoring temporal and spatial changes in the mountain seasonal snowpack is a key step to better quantify the impact of recent climate warming on this very sensitive environment. In this context, to support the research on large scale, there is an urgent need of consistent and accurate data sets over global mountain regions. This paper presents a dataset derived from Moderate Resolution Imaging Spectroradiometer (MODIS) imagery collection 6.1 onboard of Terra satellite containing information on snow cover area and snow cover phenology (duration, start and end of the season) at 500 m ground resolution and covering the global mountain regions as delineated by the Global Mountain Biodiversity Assessment (GMBA) shapefile. The dataset contains yearly averaged snow cover area (SCA), snow cover duration (SCD), first snow day (FSD) and last snow day (LSD). The snow cover area SCA is based on snow cover fraction daily maps averaged on a yearly basis. To derive the snow phenology variables, SCD, FSD, LSD, a second-order autoregressive approach was adopted to interpolate the data thus reducing the impact of cloud coverage. The dataset was processed for the entire MODIS time series starting from October 2000 up to September 2023 and it is provided on yearly basis considering the hydrological year timeframe: from 1

Indexed as

Climate changeMODISMountain ecosystemRemote sensingSnow phenologyWater resources

Identifiers

PMID39281018
PMCPMC11399691

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.