Evidence map›Paper›PMID 41030659›Full record

ArticleData in brief2025

Semi-automated multi-criteria filtering of building footprints for enhanced Wildland-Urban Interface mapping in mainland Portugal.

Bruno Barbosa, Sandra Oliveira, Jorge Rocha

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Data in brief, 2025. 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

3 authors.

Bruno BarbosaCentre of Geographical Studies, Institute of Geography and Spatial Planning, University of Lisbon, Lisbon 1600-276, Portugal.
Sandra OliveiraCentre of Geographical Studies, Institute of Geography and Spatial Planning, University of Lisbon, Lisbon 1600-276, Portugal.
Jorge RochaCentre of Geographical Studies, Institute of Geography and Spatial Planning, University of Lisbon, Lisbon 1600-276, Portugal.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The expansion of the Wildland-Urban Interface (WUI) demands precise mapping to effectively mitigate wildfire risk. However, the absence of national building footprint databases presents a significant challenge. This study, focused on mainland Portugal, proposes a semi-automated, multi-criteria filtering framework to refine global open-source building datasets-specifically Microsoft's Global Building Footprints. The method integrates regional adaptability and spatial metrics such as area thresholds and proximity analyses, using Portugal's official Geographic Buildings Location Database as a reference. The framework prioritizes residential structures by excluding anomalies-such as industrial facilities, photovoltaic arrays, and transmission lines-through dynamically adjusted thresholds at various administrative levels (e.g., municipal and NUTS-2). The filtering process reduced the number of building footprints from approximately 5.6 million to around 3.0 million. We mapped the WUI across Portugal using both the original dataset (WUI_MSB) and the filtered dataset (WUI_MSB_F) to compare outcomes. The WUI was classified into

Indexed as

Building footprintsGeographic information systemResource allocation efficiencySpatial bias correctionWildland-urban interface

Identifiers

PMID41030659
PMCPMC12477925

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.