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Fabiane Bordin     University Educator/Researcher 
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Fabiane Bordin published an article in January 2018.
Top co-authors
John Boland

102 shared publications

Centre for Industrial and Applied Mathematics, School of Information Technology and Mathematical Sciences, University of South Australia, Mawson Lakes Boulevard, Mawson Lakes, SA 5095, Australia

Maurício Roberto Veronez

43 shared publications

Multidisciplinary Advanced Visualization and GeoInformatics Laboratory, Unisinos University, São Leopoldo, 93022-750 Rio Grande do Sul, Brazil

Damien Arvor

30 shared publications

French National Center for Scientific Research (CNRS), Université Rennes 2, UMR LETG, Place du Recteur Henri Le Moal, 354043 Rennes Cedex, France

Jorge Ricardo Ducati

22 shared publications

Universidade Federal do Rio Grande do Sul, Brasil

7
Publications
25
Reads
0
Downloads
6
Citations
Publication Record
Distribution of Articles published per year 
(2012 - 2018)
Total number of journals
published in
 
7
 
Publications See all
Article 0 Reads 0 Citations Canopy temperatures distribution over soybean crop fields using satellite data in the Amazon biome frontier Anibal Gusso Published: 01 January 2018
European Journal of Remote Sensing, doi: 10.1080/22797254.2018.1511832
DOI See at publisher website ABS Show/hide abstract
During the studied time window, between 2003 and 2010, there was an important increase of land use conversion into new soybean areas (first-time-use) in Mato Grosso state (MT) in Brazil. Uncertainties of future scenario of Brazilian agriculture and increase in the frequency of extreme events, such as the occurrence of high temperatures, is highly likely to produce yield loss on summer crops. The MT is the largest producer of soybeans and accounted for 28.2% of the national production in 2013. The objective of this study was to investigated specific characterization of land surface temperature distribution over the soybean crop fields canopies (canopy-LST) due to massive land use conversion into new soybean areas and its impacts on yield. Satellite imagery data from Aqua and Terra/MODIS sensors (Moderate Resolution Imaging Spectroradiometer) were compared to official agricultural statistics covering eight densely cultivated regions in the studied period. Results show that within the period from flowering to grain filling canopy-LST exhibits a non-negligible relation to yield. It is expected an additional loss of 4.9% on soybean yield for each 1oC of canopy-LST above the obtained optimal level of canopy-LST with 28.4oC, associated to the higher yield averages. The difference between overall average of canopy-LST and air temperature was found 4.2 oC.
Article 4 Reads 0 Citations Income Driven Patterns of the Urban Environment Anibal Gusso, André Silva, John Boland, Leticia Lenz, Conrad... Published: 15 February 2017
Sustainability, doi: 10.3390/su9020275
DOI See at publisher website ABS Show/hide abstract
This study investigates the land surface temperature (LST) distribution from thermal infrared data for analyzing the characteristics of surface coverage using the Vegetation–Impervious–Soil (VIS) approach. A set of ten images, obtained from Landsat-5 Thematic Mapper, between 2001 and 2010, were used to study the urban environmental conditions of 47 neighborhoods of Porto Alegre city, Brazil. Porto Alegre has had the smallest population growth rate of all 27 state capitals in the last two decades in Brazil, with an increase of 11.55% in inhabitants from 1.263 million in 1991 to 1.409 million in 2010. We applied the environmental Kuznets curve (EKC) theory in order to test the influence of the economically-related scenario on the spatial nature of social-environmental arrangement of the city at neighborhood scale. Our results suggest that the economically-related scenario exerts a non-negligible influence on the physically driven characteristics of the urban environmental conditions as predicted by EKC theory. The linear inverse correlation R2 between household income (HI) and LST is 0.36 and has shown to be comparable to all other studied variables. Future research may investigate the relation between other economically-related indicators to specific land surface characteristics.
PREPRINT 3 Reads 0 Citations Economic Driven Patterns of the Urban Environment Anibal Gusso, Conrad Philipp, André Silva, John Boland, Leti... Published: 16 December 2016
EARTH SCIENCES, doi: 10.20944/preprints201612.0085.v1
DOI See at publisher website ABS Show/hide abstract
This study investigates the land surface temperature (LST) distribution from thermal infrared data for analyzing the characteristics of surface coverage using the Vegetation-Impervious-Soil (VIS) approach. A set of ten images, obtained from Landsat-5 Thematic Mapper, between 2001 and 2010, were used to study the urban environmental conditions of 47 neighborhoods of Porto Alegre city, Brazil. Porto Alegre has had the smallest population growth rate of all 27 state capitals in the last two decades in Brazil, with an increase of 11.55% in inhabitants from 1,263 million in 1991 to 1,409 million in 2010. We applied the environmental Kuznets curve (EKC) theory in order to test the influence of the economically-related scenario on the spatial nature of social-environmental arrangement of the city at neighborhood scale. Our results suggest that the economically-related scenario exerts a non-negligible influence on the physically driven characteristics of the urban environmental conditions as predicted by EKC theory. The linear inverse correlation R2 between household income (HI) and LST is 0.36 and has shown to be comparable to all other studied variables. Future research may investigate the relation between other economically-related indicators to specific land surface characteristics.
CONFERENCE-ARTICLE 4 Reads 0 Citations Multitemporal Analysis of Thermal Distribution Characteristics for Urban Heat Islands Management Anibal Gusso, Fabiane Bordin, Mauricio Veronez, Cristina Caf... Published: 05 November 2014
The 4th World Sustainability Forum, doi: 10.3390/wsf-4-f009
DOI See at publisher website ABS Show/hide abstract
The evaluation of the urban ecosystem conditions and environment while cities that are still growing economically, are highly necessary for reliable assessment of sustainability in big cities. The urban green spaces are valuable sources of evapotranspiration process generated by trees and vegetation which mitigates urban heat islands (UHI) in the cities. The Land Surface Temperature (LST) is closely related to the distribution of Land Use and Land Cover (LULC) characteristics and can be used as an indicator of the urban environment conditions and development. This research evaluates the patterns of LST distribution by means the Thermal Spatial Distribution Signature (TSDS) procedure using Thermal Infrared (TIR) data obtained from Landsat-5 Thematic Mapper (TM). A set of eighteen images, between 1985 and 2009, were used to study the urban environment during the summer season, in 47 neighborhoods in the city of Porto Alegre, Brazil. At neighborhood scale, results show a non-linear inverse correlation (R2=0.55) between vegetation index and LST. The overall average of the LST is 300.23 K (27.8˚C) with a standard deviation of 1.25 K. The max difference found between neighborhoods was 2.83 K.
Conference 4 Reads 0 Citations Monitoring the vulnerability of soybean to heat waves and their impacts in Mato Grosso state, Brazil Anibal Gusso, Jorge Ricardo Ducati, Mauricio Roberto Veronez... Published: 01 July 2014
2014 IEEE Geoscience and Remote Sensing Symposium, doi: 10.1109/igarss.2014.6946560
DOI See at publisher website
Article 5 Reads 2 Citations Assessing the MODIS Crop Detection Algorithm for Soybean Crop Area Mapping and Expansion in the Mato Grosso State, Brazi... Anibal Gusso, Damien Arvor, Jorge Ricardo Ducati, Mauricio R... Published: 01 January 2014
The Scientific World Journal, doi: 10.1155/2014/863141
DOI See at publisher website PubMed View at PubMed ABS Show/hide abstract
Estimations of crop area were made based on the temporal profiles of the Enhanced Vegetation Index (EVI) obtained from moderate resolution imaging spectroradiometer (MODIS) images. Evaluation of the ability of the MODIS crop detection algorithm (MCDA) to estimate soybean crop areas was performed for fields in the Mato Grosso state, Brazil. Using the MCDA approach, soybean crop area estimations can be provided for December (first forecast) using images from the sowing period and for February (second forecast) using images from the sowing period and the maximum crop development period. The area estimates were compared to official agricultural statistics from the Brazilian Institute of Geography and Statistics (IBGE) and from the National Company of Food Supply (CONAB) at different crop levels from 2000/2001 to 2010/2011. At the municipality level, the estimates were highly correlated, with and RMSD = 13,142 ha. The MCDA was validated using field campaign data from the 2006/2007 crop year. The overall map accuracy was 88.25%, and the Kappa Index of Agreement was 0.765. By using pre-defined parameters, MCDA is able to provide the evolution of annual soybean maps, forecast of soybean cropping areas, and the crop area expansion in the Mato Grosso state.
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