Igor da Silva Narvaes

Dr. Igor da Silva Narvaes

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Research Focus & Metrics

Academic Career Length

11Years (2016-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 January 2019 in Pesquisa Agropecuária Brasileira
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ESEDSON SANO
EDSON SANO
RRRoberto Rosa
Roberto Rosa
CSCarlos Alberto de Mattos Scaramuzza
Carlos Alberto de Mattos Scaramuzza
MAMarcos Adami
Marcos Adami
Édson Luis BolfeÉdson Luis Bolfe
Édson Luis Bolfe
Gustavo BaymaGustavo Bayma
Gustavo Bayma
The objective of this work was to analyze land use dynamics in the Brazilian Cerrado region from 2002 to 2013. This analysis was based on the interpretation of Landsat satellite images carried out by the projects Projeto de Conservação e Utilização Sustentável da Diversidade Biológica Brasileira (Probio) and TerraClass Cerrado 2013, both coordinated by Ministério do Meio Ambiente. In 2002, 38.9% of the Cerrado was covered by some type of anthropic activity. In 2013, this percentage increased to 43.4%. One of the main highlights is the emergence of a new agricultural frontier in the northern region of the study area, known as Matopiba.

13 December 2016 in Forests
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ITIsabelle Tritsch
Isabelle Tritsch
PSPlinio Sist
Plinio Sist
INIgor da Silva Narvaes
Igor da Silva Narvaes
LFLucas José Mazzei de Freitas
Lucas José Mazzei de Freitas
LBLilian Blanc
Lilian Blanc
VGValery Gond
Valery Gond
In the Brazilian Amazon, multiple logging activities are undergoing, involving different actors and interests. They shape a disturbance gradient bound to the intensity and frequency of logging, and forest management techniques. However, until now, few studies have been carried out at the landscape scale taking into account these multiple types of logging and this disturbance gradient. Here we address this issue of how to account for the multiple logging activities shaping the current forest landscape. We developed an inexpensive and efficient remote sensing methodology based on Landsat imagery to detect and track logging activity based on the monitoring of canopy openings. Then, we implemented a set of remote sensing indicators to follow the different trajectories of forest disturbance through time. Using these indicators, we emphasized five major spatial and temporal disturbance patterns occurring in the municipality of Paragominas (State of Pará, Brazilian Amazon), from well-managed forests to highly over-logged forests. Our disturbance indicators provide observable evidence for the difference between legal and illegal patterns, with some illegal areas having suffered more than three explorations in fifteen years. They also clearly underlined the efficiency of Reduced Impact Logging (RIL) techniques applied under Forest Stewardship Council (FSC) guidelines to reduce the logging impacts in terms of canopy openings. For these reasons, we argue the need to promote legal certified logging to conserve forests, as without them, many actors mine the forest resources without any concerns for future stocks. Finally, our remote tracking methodology, which produces easy to interpret disturbance indicators, could be a real boon to forest managers, including for conservationists working in protected areas and stakeholders dealing with international trade rules such as RBUE (Wood regulation of European Union) or FLEGT (Forest Law for Enforcement, Governance and Trade).

14 June 2017 in Revista Brasileira de Cartografia
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CSCarlos Aberto de Mattos Scaramuzza
Carlos Aberto de Mattos Scaramuzza
ESEDSON SANO
EDSON SANO
MAMarcos Adami
Marcos Adami
Édson Luis BolfeÉdson Luis Bolfe
Édson Luis Bolfe
ACAlexandre Coutinho
Alexandre Coutinho
Gustavo BaymaGustavo Bayma
Gustavo Bayma
The Brazilian Cerrado is one of the world´s biodiversity hotspot and hosts some of the most intensive agricultural activities for food production in the world. The objective of this study was to produce a land-use and land-cover (LULC) map of the Cerrado based on Landsat-8 Operational Land Imager (OLI) images. A set of 121 scenes from 2013 was processed using the image segmentation technique. The segments were exported in the shapefi le format and interpreted visually in a geographical information system software using RGB/564 color composites. The following LULC classes were considered: annual croplands, perennial croplands, cultivated pasturelands, reforestation, mosaic of occupation, urban areas, mining areas, bare soil, forestlands, non-forestlands, water bodies, and non-identifi ed (clouds and burned areas). The overall accuracy was estimated by an independent scientist with large experience in Cerrado´s image interpretation. The results showed that 43.4% of the study area (88.5 million hectares) were already converted into agricultural, urban and mining areas, 54.6% (111 million hectares) were still natural areas, and 1.9% (3.9 million hectares) was classified as non-identified. Cultivated pasturelands were the most representative land-use type (29.5%), followed by annual croplands (8.5%) and perennial croplands (3.1%). The overall accuracy of the final map was 80.2%.

3 May 2023 in Forests
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INIgor da Silva Narvaes
Igor da Silva Narvaes
JSJoão Roberto dos Santos
João Roberto dos Santos
PBPolyanna Da Conceição Bispo
Polyanna Da Conceição Bispo
PGPaulo Maurício de Alencastro Graça
Paulo Maurício de Alencastro Graça
Ulisses GuimarãesUlisses Guimarães
Ulisses Guimarães
Fábio Furlan GamaFábio Furlan Gama
Fábio Furlan Gama
Polarimetric synthetic aperture radar (SAR) images are essential to understand forest structure and plan forest inventories with the purpose of natural resource management and environmental conservation efforts. We developed a method for estimating above-ground biomass (AGB) from power and phase-radar attributes in L-band images. The model was based on the variables “Pv” (from Freeman–Durden decomposition) and “σ°HH”, complemented by the attributes of Touzi decomposition “αS2”, “τm”, “ ΦS3”, and “ ΦS2”. The analyses demonstrated the contribution of volumetric, multiple, and direct scattering resulting from the interaction between the signal and the random structure of canopies and their forest biomass. The proposed model had good predictive capacity and a positive correlation (R2 = 0.67 and = 0.81, respectively), with Syx = 56.9 Mg ha−1 and a low average estimation error of 7.5% at R2 = 0.81 in the validation. An additional exploratory analysis of the parallel polarimetric responses did not reveal a defined pattern for the different phytophysiognomies—although all indicated a predominance of multiple and/or volumetric scattering. This fact can be related to the floristic and structural variation in the primary forest units, the degree of human intervention in legal logging, and the differences among succession stages.

1 January 2021 in Research, Society and Development
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WPWaltair Maria Martins Pereira
Waltair Maria Martins Pereira
RBRebeca Lima Braga
Rebeca Lima Braga
ESEmanuele Rocha da Silva
Emanuele Rocha da Silva
JSJosé Natanael Gama dos Santos
José Natanael Gama dos Santos
BNBelmiro Figueiredo Vinente Neto
Belmiro Figueiredo Vinente Neto
LGLourdes Garcez
Lourdes Garcez
Este estudo teve como objetivo identificar a dependência espacial das taxas de detecção de hanseníase na população geral e em menores de 15 anos com a proporção de migração, no estado do Pará. Foi realizada pesquisa com desenho de estudo ecológico em uma série histórica de casos de novos de hanseníase, entre os anos de 2006 a 2015, a partir de do banco de dados do Sistema de Informação de Agravos Notificáveis do Ministério da Saúde, referentes ao Estado. A evolução temporal da taxa de detecção geral, padronizada pela idade, apresentada geograficamente, identificou um corredor de muito hiperendemicidade, no sentido Sudoeste-Sudeste do Estado e dois aglomerados de municípios, também de muito hiperendemicidade, na fronteira com os estados do Tocantins e do Maranhão. A análise espacial demonstrou que as taxas médias na população em geral e em menores de 15 anos e a proporção de migração apresentaram autocorrelação espacial positiva, permitindo identificar clusters localizados nas áreas Sudeste, Sudoeste, Centro Norte e Nordeste do Estado. Nessas áreas estão concentrados os projetos de exploração mineral e de agropecuária e foram construídas duas Usinas Hidroelétricas nas décadas de 1960 e 2000, sendo favorecidas por rede viária e ferroviária consolidada que é usada para o escoamento dos produtos e para o intenso fluxo migratório das pessoas. Esta pesquisa evidencia que a hanseníase apresenta alta magnitude com característica de transmissão e que os 2/3 da área territorial que expressam hiperendemicidade, a destacando como sério problema de saúde pública no estado do Pará.

1 January 2016 in Pesquisa Agropecuária Brasileira
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LGLaura Camila de Godoy Goergen
Laura Camila de Godoy Goergen
RKRicardo de Vargas Kilca
Ricardo de Vargas Kilca
INIgor da Silva Narvaes
Igor da Silva Narvaes
MSMatheus Nunes Silva
Matheus Nunes Silva
ESEmanuel Silva
Emanuel Silva
MAMarcos Adami
Marcos Adami
Resumo: O objetivo deste trabalho foi avaliar a utilização de imagens do sensor TM/Landsat 5 na diferenciação de plantios comerciais de Eucalyptus dunnii e Eucalyptus urograndis com diferentes idades. Demarcaram-se parcelas para identificar as duas espécies, em dois períodos distintos (2009 e 2011), a idades de 3 e 5 anos, para E. dunnii, e 2,2 e 4,2 anos para E. urograndis. Avaliaram-se seis bandas do sensor TM/Landsat 5 (B1, B2, B3, B4, B5 e B7) e seis índices de vegetação: razão simples (SR); índice de vegetação por diferença normalizada (NDVI); índice de vegetação ajustado ao solo (Savi)-0,25; Savi-0,5; índice de vegetação por diferença normalizada com uso da banda verde (GNDVI); e índice de umidade na vegetação (MVI). O processamento digital das imagens consistiu de correção geométrica, radiométrica e atmosférica. Os plantios de E. dunnii e E. urograndis foram diferenciados por meio de cinco bandas do Landsat (B2, B3, B4, B5 e B7) e três índices de vegetação (Savi-0,5, Savi-0,25 e GNDVI), no ano de 2009, e por quatro bandas do Landsat (B2, B4, B5 e B7) e seis índices de vegetação (NDVI, SR, Savi-0,5, Savi-0,25, MVI e GNDVI) no ano de 2011. Os dados espectrais extraídos das imagens TM/Landsat 5 são eficazes, tanto para distinguir as espécies de eucalipto como também a mesma espécie em plantios equiâneos.