Evidence map›Paper›PMID 36964148›Full record

ArticleScientific reports2023

A near real-time web-system for predicting fire spread across the Cerrado biome.

Ubirajara Oliveira, Britaldo Soares-Filho, Hermann Rodrigues, Danilo Figueira, Leticia Gomes, William Leles, Christian Berlinck, Fabiano Morelli, Mercedes Bustamante, Jean Ometto and 1 more

Open access · goldFull text read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
3.2field-weighted citation impact, top 8% of its field
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

2 citing papers in PubMed, 20 citations in OpenAlex.

  1. Article
  2. 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

11 authors at 4 institutions in 1 country.

Ubirajara OliveiraCenter for Remote Sensing, Federal University of Minas Gerais, Belo Horizonte, Brazil. ubiologia@yahoo.com.br.
Britaldo Soares-FilhoCenter for Remote Sensing, Federal University of Minas Gerais, Belo Horizonte, Brazil.
Hermann RodriguesCenter for Remote Sensing, Federal University of Minas Gerais, Belo Horizonte, Brazil.
Danilo FigueiraCenter for Remote Sensing, Federal University of Minas Gerais, Belo Horizonte, Brazil.
Leticia GomesFederal University of Brasília, Brasília, Brazil.
William LelesCenter for Remote Sensing, Federal University of Minas Gerais, Belo Horizonte, Brazil.
Christian BerlinckChico Mendes Institute for the Conservation of Biodiversity, Brasília, Brazil.
Fabiano MorelliThe National Institute for Space Research, São Paulo, Brazil.
Mercedes BustamanteFederal University of Brasília, Brasília, Brazil.
Jean OmettoThe National Institute for Space Research, São Paulo, Brazil.
Heloísa MirandaFederal University of Brasília, Brasília, Brazil.
Universidade Federal de Minas Gerais · BRUniversidade de Brasília · BRNational Institute for Space Research · BRInstituto Chico Mendes de Conservação da Biodiversidade · BR

Funding

Brazilian National Council for Scientific and Technological Development CNPq/AWS 032/2019Brazilian National Council for Scientific and Technological Development - PREVFOGO 441995/2018-7Development of Systems to Prevent Forest Fires and Monitor Vegetation Cover in the Brazilian Cerrado" (World Bank Project no. P143185)-Forest Investment Program (FIP) P143185Financiadora de Estudos e Projetos - Finep 01.22.0254.00Fundação de Amparo à Pesquisa do Estado de São Paulo 2017/22269-2Fundo Nacional de Desenvolvimento Científico e Tecnológico - FNDCT 01.22.0254.00INCT-Mudanças Climáticas 465501/2014-1
6 · The paper itself

Abstract

Wildfires are aggravating due to climate change. Public policies need territorial intelligence to prevent and promptly fight fires, especially in vast regions like Brazil. To this end, we have developed a fire-spread prediction system for the Brazilian Cerrado, the biome most affected by wildfires in South America. The system automatically uploads hot pixels and satellite data to calculate maps of fuels loads, vegetation moisture, and probability of burning for simulating fire spread thrice a day for the entire Cerrado at 25 ha and for nine conservation units at 0.04 ha spatial resolution. In both versions, the model attains 65-89% of spatial match. Model results together with ancillary data, e.g., historical burned areas and annual CO

Identifiers

PMID36964148
PMCPMC10039015
OpenAlexW4360824141

What OpenQuestion holds

Textfull text, public
LicenceCC BY
measurements read4
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.