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Dataset . 2026
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2026
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2026
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
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5m Resolution Digital Terrain Model for Italy

Authors: Mario Panza; Marina Muto; Mauro Rossi; Massimiliano Alvioli; Giulio Iovine; Ivan Marchesini;

5m Resolution Digital Terrain Model for Italy

Abstract

This dataset provides a seamless high-resolution Digital Terrain Model of the Italian territory at 5 m spatial resolution (HR-DTM-5m). The model was generated by integrating heterogeneous airborne LiDAR-derived DTMs, available at 1–2 m resolution over large but spatially fragmented portions of Italy, with the national TINITALY 1.1 digital terrain model at 10 m resolution, which was used as the sole elevation source in areas not covered by LiDAR data. The dataset was produced through a structured and fully reproducible workflow including data harmonisation, regional mosaicking of homogeneous LiDAR datasets, resampling to a common grid, and systematic blending of adjacent and partially overlapping elevation sources. Prior to blending, systematic vertical offsets between LiDAR-derived DTMs and TINITALY were corrected to ensure a consistent vertical reference. Smooth transition zones were then applied to minimise elevation discontinuities and ensure spatial continuity across dataset boundaries. The HR-DTM-5m prioritises morphological realism and topographic continuity over the strict optimisation of point-wise elevation accuracy. This design choice reflects the intended use of the dataset for geomorphological and hydrological applications, including flood modelling, landslide susceptibility analysis, and the study of rapid surface processes at regional to national scale. The dataset provides complete national coverage on a single 5 m grid, preserving the high level of detail of LiDAR data where available, while relying on the resampled TINITALY model in areas without LiDAR coverage. It is conceived as an operational and extensible product, allowing the integration of new LiDAR acquisitions without recomputing the entire national model.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average