Fernando Kawakubo

Dr. Fernando Kawakubo

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Research Focus & Metrics

Academic Career Length

25Years (2002-Present)

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

Representative Publications

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RMRobson dos Santos Souza Marinho
Robson dos Santos Souza Marinho
RDRodrigo Lopes Sanz Duro
Rodrigo Lopes Sanz Duro
MMMânlio Tasso de Oliveira Mota
Mânlio Tasso de Oliveira Mota
JHJames Hunter
James Hunter
RDRicardo Sobhie Diaz
Ricardo Sobhie Diaz
SKShirley Vasconcelos Komninakis
Shirley Vasconcelos Komninakis
Environmental changes are among the main factors that contribute to the emergence or re-emergence of viruses of public health importance. Here, we show the impact of environmental modifications on cases of infections by the dengue, chikungunya and Zika viruses in humans in the state of Tocantins, Brazil, between the years 2010 and 2019. We conducted a descriptive and principal component analysis (PCA) to explore the main trends in environmental modifications and in the cases of human infections caused by these arboviruses in Tocantins. Our analysis demonstrated that the occurrence of El Niño, deforestation in the Cerrado and maximum temperatures had correlations with the cases of infections by the Zika virus between 2014 and 2016. El Niño, followed by La Niña, a gradual increase in precipitation and the maximum temperature observed between 2015 and 2017 were shown to have contributed to the infections by the chikungunya virus. La Niña and precipitation were associated with infections by the dengue virus between 2010 and 2012 and El Niño contributed to the 2019 outbreak observed within the state. By PCA, deforestation, temperatures and El Niño were the most important variables related to cases of dengue in humans. We conclude from this analysis that environmental changes (deforestation and climate change) presented a strong influence on the human infections caused by the dengue, chikungunya and Zika viruses in Tocantins from 2010 to 2019.

10 January 2018 in Natural Hazards and Earth System Sciences
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Guilherme MataveliGuilherme Mataveli
Guilherme Mataveli
MSMaria Elisa Siqueira Silva
Maria Elisa Siqueira Silva
GPGabriel Pereira
Gabriel Pereira
FCFrancielle da Silva Cardozo
Francielle da Silva Cardozo
FKFernando Kawakubo
Fernando Kawakubo
VSViviane Valéria da Silva
Viviane Valéria da Silva
In the Brazilian savannas (Cerrado biome) fires are natural and a tool for shifting land use; therefore, temporal and spatial patterns result from the interaction of climate, vegetation condition and human activities. Moreover, orbital sensors are the most effective approach to establish patterns in the biome. We aimed to characterize fire, precipitation and vegetation condition regimes and to establish spatial patterns of fire occurrence and their correlation with precipitation and vegetation condition in the Cerrado. The Cerrado was first and second biome for the occurrence of burned areas (BA) and hotspots, respectively. Occurrences are higher during the dry season and in the savanna land use. Hotspots and BA tend to decrease, and concentrate in the north, but more intense hotspots are not necessarily located where concentration is higher. Spatial analysis showed that averaged and summed values can hide patterns, such as for precipitation, which has the lowest average in August, but minimum precipitation in August was found in 7 % of the Cerrado. Usually, there is a 2–3-month lag between minimum precipitation and maximum hotspots and BA, while minimum VCI and maximum hotspots and BA occur in the same month. Hotspots and BA are better correlated with VCI than precipitation, qualifying VCI as an indicator of the susceptibility of vegetation to ignition.

29 April 2011 in International Journal of Remote Sensing
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FKFernando Kawakubo
Fernando Kawakubo
RMRubia Morato
Rubia Morato
RNR. S. Nader
R. S. Nader
ALA. Luchiari
A. Luchiari
Multitemporal Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) imagery was used to assess coastline morphological changes in southeastern Brazil. A spectral linear mixing approach (SLMA) was used to estimate fraction imagery representing amounts of vegetation, clean water (a proxy for shade) and soil. Fraction abundances were related to erosive and depositional features. Shoreline, sandy banks (including emerged and submerged banks) and sand spits were highlighted mainly by clean water and soil fraction imagery. To evaluate changes in the coastline geomorphic features, the fraction imagery generated for each data set was classified in a contextual approach using a segmentation technique and ISOSEG, an unsupervised classification. Evaluation of the classifications was performed visually and by an error matrix relating ground-truth data to classification results. Comparison of the classification results revealed an intense transformation in the coastline, and that erosive and depositional features are extremely dynamic and subject to change in short periods of time.

28 June 2016 in International Journal of Remote Sensing
Verified
Journal Article
Closed access
FKFernando Kawakubo
Fernando Kawakubo
RMReinaldo Paul Pérez Machado
Reinaldo Paul Pérez Machado
The task of mapping coffee crops using multispectral data sets is not yet a trivial routine. This is because coffee fields are extremely heterogeneous in terms of spectral reflectance. This study therefore aims to contribute to the mapping of coffee crops using multispectral imagery with 23.5 m spatial resolution taken by the Linear Imaging Self Scanner (LISS III) instrument on board the Indian Remote Sensing (IRS) satellite system. The section of land covered by this study is a traditional coffee-producing province located in the south of the State of Minas Gerais, southeastern Brazil. Whereas the pixel mixture effect was managed using spectral mixture analysis (SMA), the classification was carried out using data mining (DM) techniques. The decision tree (DT) outcomes were evaluated using a simple and qualitative method based on the elements of photointerpretation. In total, eight land-use and land-cover (LULC) types were mapped, including three classes of coffee-growing land expressing different phenological conditions and management. These were named ‘Production Coffee’, ‘Mixed Coffee’, and ‘Old/Pruned Coffee’. The results showed that the methodology was effective for mapping LULC types, as the workflow adopted simplified image interpretation and offered improvements in the classification performance. Despite the coffee-cultivation classes having a large spectral variability, which increases the chances of classification errors, not many confusions were observed involving the three coffee classes mapped with other categories of use. This therefore shows that the method was efficient in isolating the coffee classes (with an accuracy greater than 70%) from other categories of use. Comparing the results obtained in this work with a conventional maximum-likelihood (ML) classification, the results revealed that when using the methodology described, the confusions between classes were less dispersed and an improvement of approximately 10% was observed in the mapping of the Production Coffee class.

19 April 2019 in Remote Sensing
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FKFernando Kawakubo
Fernando Kawakubo
RMRubia Morato
Rubia Morato
MMMarcos Martins
Marcos Martins
Guilherme MataveliGuilherme Mataveli
Guilherme Mataveli
PNPablo Nepomuceno
Pablo Nepomuceno
MMMarcos Roberto Martines
Marcos Roberto Martines
The growing intensity of impervious surface area (ISA) is one of the most striking effects of urban growth. The expansion of ISA gives rise to a set of changes on the physical environment, impacting the quality of life of the human population as well as the dynamics of fauna and flora. Hence, due to its importance, the present study aimed to examine the ISA distribution in the Metropolitan Region of São Paulo (MRSP), Brazil, using satellite imagery from the Landsat-8 Operational Land Imager (OLI) instrument. In contrast to other investigations that primarily focus on the accuracy of the estimate, the proposal of this study is—besides generating a robust estimate—to perform an integrated analysis of the impervious-surface distribution at pixel scale with the variability present in different territorial units, namely municipalities, sub-prefecture and districts. The importance of this study is that it strengthens the use of information related to impervious cover in the territorial planning, providing elements for a better understanding and connection with other spatial attributes. Reducing the dimensionality of the dataset (visible, near-infrared and short-wave infrared bands) by Karhune–Loeve analysis, the first three principal components (PCs) contained more than 99% of the information present in the original bands. Projecting PC1, PC2 and PC3 onto a series of two-dimensional (2D) scatterplots, four endmembers—Low Albedo (Dark), High Albedo (Substrate), Green Vegetation (GV) and Non-Photosynthetic Vegetation (NPV)—were visually selected to produce the unmixing estimates. The selected endmembers fitted the model well, as the propagated error was consistently low (root-mean-square error = 0.005) and the fraction estimates at pixel scale were found to be in accordance with the physical structures of the landscape. The impervious surface fraction (ISF) was calculated by adding the Dark and Substrate fraction imagery. Reconciling the ISF with reference samples revealed the estimates to be reliable (R2 = 0.97), regardless of an underestimation error (~8% on average) having been found, mostly over areas with higher imperviousness rates. Intra-pixel variability was combined with the territorial units of analysis through a modification of the Lorenz curve, which permitted a straightforward comparison of ISF values at different reference scales. Good adherence was observed when the original 30-m ISF was compared to a resampled 300-m ISF, but with some differences, suggesting a systematic behavior with the degradation of pixel resolution tending to underestimate lower fractions and overestimate higher ones; furthermore, discrepancies were bridged with the increase of scale analysis. The analysis of the IFS model also revealed that, in the context of the MRSP, gross domestic product (GDP) has little potential for explaining the distribution of impervious areas on the municipality scale. Finally, the ISF model was found to be more sensitive in describing impervious surface response than other well-known indices, such as Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-up Index (NDBI).

17 December 2005 in Agrária (São Paulo. Online)
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MGMaria Lúcia Cereda Gomide
Maria Lúcia Cereda Gomide
FKFernando Kawakubo
Fernando Kawakubo
El objetivo del estúdio fue realizar uno diagnóstico ambiental dela tierra indígena Sangradouro/Volta Grande-MT y realizar algunas proposiciones com el fin de proteger esta tierra indígena de los impactos que viene sufriendo por la ocupacion intensa de los cerrados de suyo entorno. Lãs actividades econômicas estan relacionadas principalmente con la monoclutura de la soja e del ganado. Asi fué proponido la criacion de uma zona amortizadora em los limites de la tierra indígena y corredor sustentable em la área del rio das Mortes, entre lãs tierras Xavante de Sangradouro e São Marcos. Estas proposiciones fueram hechas a partir de la análisis de lãs imagines del satélite Landsat y de los trabajos de campo. The purpose of this research was bring out the environmental issues related with a indigenous land: Sangradouro/Volta Grande MT, and introduce some proposition to protect this indigenous area from the impacts that they have been suffering with the intense occupation of “savanna ” in their surroundings. The economical activities that deforest the most part of the “savanna” of the center of Brazil, are related mainly with the monoculture of soy and cattle. So, was proposed the creation of a bufferzone from indigenous land and hall of support in the area of river called “ Rio das Mortes”, between the Xavante area of Sangradouro and São Marcos. This proposes was done based on the analysis of landsat satellite data and field work. Resumo indisponível.