S. R. M. Evangelista

Aligning ontologies, evaluating concept similarities and visualizing results

Ontologies have been created for many different subjects and by independent groups around the world. The nonexistence of a commonly accepted and used general purpose upper-ontology makes it difficult to integrate these ontologies through merge and alignment operations. The majority of the algorithms proposed so far rely on syntactic analysis, disregarding the structural properties of the source ontologies. In our previous work, we proposed an alignment method that considers the structural properties of an upper-ontology constructed using a thesaurus and Formal Concept Analysis technique (FCA). We also analyzed the FCAs lattice structure and proposed a measure of similarity based on Tverskys model, which allowed us to identify closely related concepts in different source ontologies. In this paper, we apply the alignment method to ontologies developed for a completely different domain, and enhance the solution by providing a navigational aid for the lattice. It is well known that one of the main drawbacks of the application of FCA is that the resulting lattice soon becomes cluttered when the number of objects and attributes increases. The proposed solution is based on hyperbolic visualization and on structural elements of the lattice.

Estimativa da Et o pelo modelo Penman-Monteith FAO com dados mínimos integrada a um Sistema de Informação Geográfica 1

O objetivo do presente trabalho foi avaliar a metodologia de estimativa da EtoPM utilizando dados minimos integrados a um Sistema de Informacao Geografica, na bacia do Jaguaribe, Ceara. Foi utilizado o sistema integrado de modelagem regional PRECIS (Providing Regional Climates for Impacts Studies), versao 1.2, utilizando as condicoes de contorno do Modelo Climatico Global, HadAM3P, acoplado ao Modelo Climatico Regional (HadRM3P), atraves da tecnica dinâmica de reducao de escala (downscaling). Dados mensais de temperaturas maxima e minima e precipitacao foram gerados para o periodo de 1961-1990, os quais foram analisados quanto a sua variabilidade espacial (latitude/longitude), utilizando-se geoestatistica (krigagem). Para validacao, foi aplicada regressao linear entre EtoPM estimada com dados minimos e estimada com dados medidos atraves de uma estacao meteorologica de referencia. A media da EtoPM anual estimada com dados minimos situou-se em 1.719 mm. A metodologia funcionou satisfatoriamente na regiao estudada, considerando-se os resultados da regressao (coeficiente angular de 0,95, coeficiente de determinacao de 0,902, residuos menores que 0,45 mm dia-1 e Raiz do Quadrado Medio do Erro (RQME) igual a 0,067 mm dia-1).

Mudanças climáticas e impactos na necessidade hídrica das culturas perenes na Bacia do Jaguaribe, no Estado do Ceará

The aim of this study was to estimate climate change impacts on irrigation water demand for permanent crops. The PRECIS (Providing Regional Climates for Impact Studies) system was applied, and downscaling techniques were used at the river basin level, with the boundary conditions of the regional climate model (HadRM3P). A climate data set was generated for 1961 to 1990 (baseline) and for future climate projections. The regional geographical coordinates were considered for interpolation in a georeferenced coordinated system. The reference evapotranspiration was estimated through data of monthly average temperature. Projected climate change increased projected irrigation water demand, because evapotranspiration was estimated to increase by 3.1 to 2.2% and rainfall was estimated to decrease by 30.9 to 37.3%. The 2040 water need was estimated to increase by 32.9% to 43.9%, according to the analyzed scenario.

Visualization of ontologies through hypertrees

In this paper, we present the use of hypertree as a supporting tool for visualization of ontologies in agricultural domain. This kind of visualization technique was used in the Information Agency Project, in execution by the Brazilian Agricultural Research Corporation -- Embrapa. The projects aim is to provide an information dissemination system structured in accordance to the productive chains of given products. That structure was chosen because it reflects the natural way technicians use to interact whenever they are transferring knowledge back and forth with farmers.

Numerical models to forecast the sugarcane production in regional scale based on time series of NDVI/AVHRR images

The use of time series of meteorological satellite images, such as the AVHRR/NOAA, and agrometeorological data can be very useful in developing monitoring and forecasting methods for sugarcane crops because they are based on detection changes of space-time behavior. The knowledge about different sugarcane producing areas and climate in a given region is information required to develop models that can be applied simultaneously to several producing municipalities of sugarcane in order to assess the relation between NDVI and WRSI, the estimated productivity and the detection of similarity between the municipalities through distance functions. Thus, the main goal of this paper is to propose numerical models applied to monitor the sugarcane production based on time series of NDVI/AVHRR images and agrometeorological data. The regression method analyzes the relation between a single dependent variable (sugarcane production) and several independent variables (planted area, NDVI, WRSI), that is, use the independent variables whose values are known to predict the values of the selected dependent variable. The models proposed to estimate the sugarcane production using the variables planted area, NDVI and WRSI presented correlation coefficients (R2) around 0.9 and are able to estimate the sugarcane production for the state of São Paulo in Brazil.

Mudanças climáticas e cenários futuros para a produção de capim‑marandu no Estado de São Paulo

The objective of this work was to analyze future scenarios for palisade grass yield subjected to climate change for the state of Sao Paulo, Brazil. An empirical crop model was used to estimate yields, according to growing degree-days adjusted by one drought attenuation factor. Climate data from 1963 to 2009 of 23 meteorological stations were used for current climate conditions. Downscaled outputs of two general circulation models were used to project future climate for the 2013-2040 and 2043-2070 periods, considering two contrasting scenarios of temperature and atmospheric CO2 concentration increase (high and low). Annual dry matter yield should be from 14 to 42% higher than the current one, depending on the evaluated scenario. Yield variation between seasons (seasonality) and years is expected to increase. The increase of dry matter accumulation will be higher in the rainy season than in the dry season, and this result is more evident for soils with low-water storage capacity. The results varied significantly between regions ( 60%). Despite their higher climate potential, warmer regions will probably have a lower increase in future forage production.

Impactos das mudanças climáticas na demanda de irrigação da bananeira na Bacia do Jaguaribe

Climate change has a potential to impact hydrologic cycle processes, such as rainfall, which affect run-off, temperature and air humidity that have relationship to evaporation over water bodies and plant evapotranspiration. The purpose of this study was to assess impacts of climate change on irrigation water demand of banana, at the river basin level (Jaguaribe river, between Castanhao and Itaicaba Dams). A climate data set was generated by a climate model for 1961-90 (baseline) and the future. The output climate data has been generated, considering a georreferenced coordenated system of the study area in a 0.44 x 0.44o resolution, generating spatial distribution output for each variable. The reference evapotranspiration has been estimated using monthly average temperature and projected an increase in mean water requirements for 2040 in relation to initial conditions from 1.989 mm to 2.536 mm and 2.491 mm (27.50 and 25.24%) for A2 and B2 scenarios, developed by Intergovernamental Panel on Climate Change, respectively.