ArticleScientific data2023
A detailed land use/land cover map for the European Alps macro region.
Article in Scientific data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Orchard netting impacts on biodiversity leading to cascading effects at the ecosystem level.Biological reviews of the Cambridge Philosophical Society · 2026Pooled it
- Human food sources shape routine movements across elevational gradients in an alpine bird.Movement ecology · 2026Article
- Unravelling decades of habitat dynamics in protected areas: A hierarchical approach applied to the Gran Paradiso National Park (NW Italy).Environmental monitoring and assessment · 2025Article
- An Uncomfortable Neighborhood: Presence Evolution of Two Competing Carnivores in North-Eastern Italy.Ecology and evolution · 2025Article
- Dynamic land-cover maps in the Guangdong-Hong Kong-Macao Greater Bay Area at 30 m spatial resolution, 2000-2022.Scientific data · 2025Article
- Comprehensive dataset from high resolution UAV land cover mapping of diverse natural environments in Serbia.Scientific data · 2025Article
- Spatiotemporal patterns and drivers of orchard meadow loss in South Tyrol, Italy.Scientific reports · 2024Article
- An annual land cover dataset for the Baltic Sea Region with crop types and peat bogs at 30 m from 2000 to 2022.Scientific data · 2024Article
- Multispectral Light Detection and Ranging Technology and Applications: A Review.Sensors (Basel, Switzerland) · 2024Review
- A detailed land use/land cover map for the European Alps macro region.Scientific data · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Spatially and thematically detailed land use maps are of special importance to study and manage populated mountain regions. Due to the complex terrain, high elevational gradients as well as differences in land demand, these regions are characterized by a high density of different land uses that form heterogeneous landscapes. Here, we present a new highly detailed land use/landcover map for the areas included in the European Strategy for the Alpine Region. The map has a spatial resolution of up to 5 m and a temporal extent from 2015 to 2020. It was created by aggregating 15 high-resolution layers resulting in 65 land use/cover classes. The overall map accuracy was assessed at 88.8%. The large number of land use classes and the high spatial resolution allow an easy customization of the map for research and management purposes, making it useable by a broad audience for various applications. Our map shows that by combining theme specific "high-resolution" land use products to build a comprehensive land use/land cover map, a high thematic and spatial detail can be achieved.
Identifiers
What OpenQuestion holds
Registered trials
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.