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Anibal Gusso   Dr.  Institute, Department or Faculty Head 
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Anibal Gusso published an article in March 2015.
Top co-authors See all
Maurício Roberto Veronez

50 shared publications

Advanced Visualization & Geoinformatics Laboratory, Unisinos University, São Leopoldo, Brazil

J. R. Ducati

27 shared publications

Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil

Fabiane Bordin

19 shared publications

Advanced Visualization & Geoinformatics Laboratory, Unisinos University, São Leopoldo, Brazil

Damien Arvor

3 shared publications

UMR ESPACE-DEV 228; IRD; Montpellier France

Cristina Borges Cafruni

2 shared publications

Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil

4
Publications
19
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0
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8
Citations
Publication Record
Distribution of Articles published per year 

Total number of journals
published in
 
4
 
Publications
Article 4 Reads 6 Citations Multi-Temporal Patterns of Urban Heat Island as Response to Economic Growth Management Anibal Gusso, Cristina Cafruni, Fabiane Bordin, Mauricio Rob... Published: 16 March 2015
Sustainability, doi: 10.3390/su7033129
DOI See at publisher website ABS Show/hide abstract
For a reliable assessment of sustainability in big cities, it is imperative to evaluate urban ecosystem conditions and the environment of the cities undergoing economic growth. Urban green spaces are valuable sources of evapotranspiration, which is generated by trees and vegetation; these spaces mitigate urban heat islands in cities. Land surface temperature (LST) is closely related to the distribution of land-use and land-cover characteristics and can be used as an indicator of urban environment conditions and development. This study evaluates the patterns of LST distribution through time by employing the thermal spatial distribution signature procedure using thermal infrared data obtained from Landsat-5 Thematic Mapper. A set of 18 images, between 1985 and 2010, was used to study the urban environment during summer in 47 neighborhoods of Porto Alegre, Brazil. On a 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 and the maximum average difference of 2.83 K between neighborhoods. Results show that the Thermal Spatial Distribution Signature (TSDS) analysis can help multi-temporal studies for the evaluation of UHI through time.
CONFERENCE-ARTICLE 9 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
Proceedings of 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.
Article 6 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: 10 April 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 R 2 = 0.97 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.
Article 0 Reads 0 Citations Integrating Aqua and Terra/MODIS satellite Data for the Evaluation of Heat Stress Impacts on Summer Crops Leonardo Campos Inocêncio, Aníbal Gusso, Jorge Ricardo Ducat... Published: 01 January 2014
Revista Brasileira de Geografia Física, doi: 10.5935/1984-2295.20140004
DOI See at publisher website
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