Evidence map›Paper›PMID 31752073›Full record

ArticleSensors (Basel, Switzerland)2019

Determining a Threshold to Delimit the Amazonian Forests from the Tree Canopy Cover 2000 GFC Data.

Kaio Allan Cruz Gasparini, Celso Henrique Leite Silva Junior, Yosio Edemir Shimabukuro, Egidio Arai, Luiz Eduardo Oliveira Cruz E Aragão, Carlos Alberto Silva, Peter L Marshall

Open access · goldAbstract readLetter
In one paragraph

Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.2field-weighted citation impact, top 20% 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

3 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
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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

7 authors at 3 institutions in 3 countries.

Kaio Allan Cruz GaspariniDivisão de Sensoriamento Remoto, Instituto Nacional de Pesquisas Espaciais, São José dos Campos - SP, Brazil.ORCID 0000-0001-8380-8272
Celso Henrique Leite Silva JuniorDivisão de Sensoriamento Remoto, Instituto Nacional de Pesquisas Espaciais, São José dos Campos - SP, Brazil.ORCID 0000-0002-1052-5551
Yosio Edemir ShimabukuroDivisão de Sensoriamento Remoto, Instituto Nacional de Pesquisas Espaciais, São José dos Campos - SP, Brazil.
Egidio AraiDivisão de Sensoriamento Remoto, Instituto Nacional de Pesquisas Espaciais, São José dos Campos - SP, Brazil.
Luiz Eduardo Oliveira Cruz E AragãoDivisão de Sensoriamento Remoto, Instituto Nacional de Pesquisas Espaciais, São José dos Campos - SP, Brazil.ORCID 0000-0002-4134-6708
Carlos Alberto SilvaDepartment of Geographical Sciences, University of Maryland, College Park, Maryland, MD 20740, USA.ORCID 0000-0002-7844-3560
Peter L MarshallDepartment of Forest Resources Management, The University of British Columbia, 2424 Main Mall, Vancouver, BC V6T 1Z4, Canada.ORCID 0000-0002-5479-557X
Instituto Nacional de Pesquisas Espaciais · BRUniversity of Maryland, College Park · USUniversity of British Columbia · CA

Funding

Conselho Nacional de Desenvolvimento Científico e Tecnológico 305054/2016-3. 95/5000Coordenação de Aperfeiçoamento de Pessoal de Nível Superior 001Fundação de Amparo à Pesquisa do Estado de São Paulo 2016/19806-3
6 · The paper itself

Abstract

Open global forest cover data can be a critical component for Reducing Emissions from Deforestation and Forest Degradation (REDD+) policies. In this work, we determine the best threshold, compatible with the official Brazilian dataset, for establishing a forest mask cover within the Amazon basin for the year 2000 using the Tree Canopy Cover 2000 GFC product. We compared forest cover maps produced using several thresholds (10%, 30%, 50%, 80%, 85%, 90%, and 95%) with a forest cover map for the same year from the Brazilian Amazon Deforestation Monitoring Project (PRODES) data, produced by the National Institute for Space Research (INPE). We also compared the forest cover classifications indicated by each of these maps to 2550 independently assessed Landsat pixels for the year 2000, providing an accuracy assessment for each of these map products. We found that thresholds of 80% and 85% best matched with the PRODES data. Consequently, we recommend using an 80% threshold for the Tree Canopy Cover 2000 data for assessing forest cover in the Amazon basin.

Indexed as

ForestsBrazilConfidence IntervalsConservation of Natural ResourcesEcosystemEnvironmental MonitoringGeographyRegression AnalysisTreesforest degradationforest mappingGoogle Earth EngineREDD+remote sensing

Identifiers

PMID31752073
PMCPMC6891484
OpenAlexW2985661740

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.