Joaquim Carlos Barbosa Queiroz

O emprego da geoestatística na determinação do tamanho "ótimo" de amostras aleatórias com vistas à obtenção de estimativas dos volumes dos fustes de espécies florestais em Paragominas, estado do Pará

O objetivo do trabalho foi determinar o tamanho adequado de amostra para estimar o volume de fustes de especies florestais de uma populacao de arvores a serem cortadas no sistema de manejo florestal da empresa Cikel Brasil Verde Madeiras - Para. Utilizaram-se as metodologias da amostragem sistematica e do estimador geoestatistico da krigagem ordinaria com simulacao sequencial, respectivamente para a escolha das amostras e estimacao dos volumes dos fustes das arvores. Os resultados mostraram que os metodos podem ser utilizados no calculo dos volumes de fustes de arvores. Entretanto, o metodo da krigagem apresenta um efeito de suavizacao, tendo como consequencia uma subestimacao dos volumes calculados. Neste caso, um fator de correcao foi aplicado para minimizar o efeito da suavizacao. A simulacao sequencial indicativa apresentou resultados mais precisos em relacao a krigagem, uma vez que tal metodo apresentou algumas vantagens, tal como a nao exigencia de amostras com distribuicoes normais e ausencia de efeito de suavizacao, caracteristico dos metodos de interpolacao.

Evaluation of sustainability in Eastern Amazon under proambiente program.

This study evaluates the sustainability of the innovative practices of smallholders who have extended their traditional farming and backyard gardening to other production parcels, such as agroforest systems in Eastern Amazon, Northeast Pará, under the PROAMBIENTE Program at Capim River Pole. According to these smallholders, these practices have assured food supplies and yields with the inclusion into the consumer market through produce diversity obtained by agroforest arrangement and increased purchase of material goods to the system. The smallholders’ perceptions also permit the evaluation of the sustainability of their experiences through the “Amoeba” method, which consolidates economic, social, cultural, and environmental indicators.

Evaluation via multivariate techniques of scale factor variability in the rietveld method applied to quantitative phase analysis with X ray powder diffraction

The present work uses multivariate statistical analysis as a form of establishing the main sources of error in the Quantitative Phase Analysis (QPA) using the Rietveld method. The quantitative determination of crystalline phases using x ray powder diffraction is a complex measurement process whose results are influenced by several factors. Ternary mixtures of Al2O3, MgO and NiO were prepared under controlled conditions and the diffractions were obtained using the Bragg-Brentano geometric arrangement. It was possible to establish four sources of critical variations: the experimental absorption and the scale factor of NiO, which is the phase with the greatest linear absorption coefficient of the ternary mixture; the instrumental characteristics represented by mechanical errors of the goniometer and sample displacement; the other two phases (Al2O3 and MgO); and the temperature and relative humidity of the air in the laboratory. The error sources excessively impair the QPA with the Rietveld method. Therefore it becomes necessary to control them during the measurement procedure.

Use of spatial regression models in the analysis of burnings and deforestation occurrences in forest region, Amazon, Brazil

Through the PRODESDIGITAL Project, the National Institute for Space Research (INPE) has been mapping vegetal coverage in the Brazilian Legal Amazon using Landsat satellite images. INPE not only identifies deforested areas but also releases a daily map of burning areas. These fires often get out of control and end up accidentally invading areas of forest exploited by the lumber industry, agricultural plantations, and pastures. However, the deforestation and burning maps alone are insufficient for monitoring and control on a regional scale. The current study performs a dynamic analysis of the characteristics of burning occurrences in the state of Pará, considering not only a possible spatial influence, but also the temporal dependence during the period 1999–2004. In the distribution analysis of burnings and deforestation in Pará throughout this time, it can be observed that burnings mainly take place near the main highways in the state. Therefore, the currently deforested areas correspond to the mesoregions with good infrastructure access. These regions should be targets for farming technological investments. It can be shown that burning occurrences do not happen in a random way. Furthermore, the spatial diffusion process is faster for burnings than for deforestation. The spatio-temporal study showed that there was a change in the pattern records of burnings mainly in 2004, where the greatest quantity of records were located in the northeastern mesoregion of Pará and great concentrations were also observed in southeastern and southwestern mesoregions.

Mapping the Risk of Burning in the Brazilian Amazon with the Use of Logistic Regression and Fuzzy Inference

Through the PRODESDIGITAL Project, the National Institute for Space Research (INPE) has been mapping vegetal coverage in the Brazilian Legal Amazon using Landsat satellite images. INPE not only identifies deforested areas but also releases a daily map of burning areas. Burning is frequently used as the cheapest way to deforest, to clear areas for farming and to increase the soil’s fertility in a short period of time. In many instances, these fires get out of control and end up accidentally invading areas of forest exploited by the lumber industry, agricultural plantations and pastures. However, the deforestation and burning area maps alone are insufficient for monitoring and control on a regional scale. It is necessary to know in an analytical way how actions (deforestation and burnings) that characterize human occupation are occurring in a region. In this research, two methods are used that allow the inclusion of co-variation in the estimation of variables of interest: logistic regression, which is a statistical method that considers a categorical or discrete response variable and discrete and/or continuous co-variation; and fuzzy logic, which makes use of artificial intelligence methods to incorporate into computational models information based on the knowledge or experience of a specialist. In both methods, the response variable may be related to the probability of occurrence of the environmental variable under study.

Conjunctive use of in situ gas sampling and chromatography with geospa-tial analysis to estimate greenhouse gas emissions of a large Amazonian hydroelectric reservoir

Hydroelectric power reservoirs are considered potential contributors to the greenhouse effect in the atmosphere through the emittance of methane and carbon dioxide. We combined in situ sampling and gas chromatography with geostatistical and remote sensing approaches to estimate greenhouse gas (GHG) emissions of a large hydropower reservoir. We used remote sensing data to estimate the water surface and geospatial interpolation to calculate total emissions as a function of reservoir surface area. The CH4 and CO2 gas concentrations were linearly correlated to sampling time, confirming the adequacy of the in situ sampling method to measure GHG diffusive fluxes from reservoir water surfaces. The combination of high purity (99.99%) ISO-norm gas standards with a gas chromatograph, enabled us to achieve low measurement detection limits of 0.16 and 0.60 μmol mol-1, respectively, for CH4 (using a flame ionization or FID detector) and CO2 (using a thermal conductivity or TCD detector). Our results show that CO2 emissions are significantly (an order of 5.102-103) higher than those of CH4 in both the spatial and temporal domain for this reservoir. The total diffusive GHG emissions over a year (June 2011 to May 2012) of the Tucuruí hydropower reservoir being in operation, in units of tons of carbon, added up to 6.82 × 103 for CH4 and 1.19 × 106 for CO2. We show that in situ GHG sampling using small floating gas chambers and high precision gas chromatography can be combined with geospatial interpolation techniques and remote sensing data to obtain estimates of diffusive GHG emissions from large water bodies with fluctuating water surfaces such as hydropower reservoirs. We recommend that more measurements and observations on these emissions are pursued in order to support and better quantify the ongoing discussions on estimates and mitigation of GHG emissions from reservoirs in the Amazon region and elsewhere in the world.

A Relação da Incidência de Casos de Dengue com a Precipitação na Área Urbana de Belém-PA, 2007 a 2011, Através de Modelos Multivariados de Séries Temporais

It was conducted a mapping study of the areas of incidence and predictions for dengue cases in the urban area of Belém, where the Dengue Incidence Rate (DIR) related to rainfall precipitation was used to forecast dengue occurrences using a multivariate model based on the Box and Jenkins time series methodology. The study period was 5 years (2007-2011). The results of the DIR data analysis and precipitation showed that the increase in DIR is accompanied by an increase in precipitation, demonstrating a direct relationship between these variables in the period under consideration, in the neighborhoods of the urban area of Belém, with greater emphasis in the neighborhoods of Marco, Guamá and Pedreira. The predictive model built for the DIR showed a good fit with satisfactory results and, in this case, can be used to predict dengue.

Three-Dimensional Geostatistical Estimation of Soil Units: A Case Study From Capitão Pocinho, Pará, Brazil (Case Study)

Lithology volumetric estimation was performed from samples of drills using three-dimensional geostatistical techniques. Monte Carlo simulations were performed to test the accuracy and influencing factors. Next, procedures were applied to a case study related to the environment. The simulation results show that estimates obtained via block Kriging can be relatively accurate. The case study in this research was challenging, given the quantitative limitations of information collected in the area. However, block Kriging proved to be consistent and feasible, and observed the model’s assumptions. It also offers the advantage that, after obtaining data from the drills, all necessary computational tools are available for free. A computer code was developed in the R program for mapping 3D and calculation of volumes of lithology. These results open precedents for future research using other geostatistical techniques, such as Indicator Simulation, Spatio-temporal Analysis, or even co-Kriging, correlating the lithologies with variables related to environmental contamination by pollutants. In the study area, the lithological profiles of piezometer wells revealed that the vadose zone was composed predominantly of sandy-clay material. The soil classified as sandy clay may have been associated with free aquifers. This sandy-clay material totaled around 2.67% of the study area, with a volume of approximately 596 240 m. The classified material, such as silty clayed sand and sand, which seemed to predominate in the saturated zone, represented about 14.31% and 13.1%, respectively. In this case, the volume estimated for each lithology was around 3 189 280 m and 2 916 384 m, respectively. The highest prevalence was sandy clay with 61.8% of the region’s volume, which is about 13 795 264 m. Finally, the silty sand represented about 8.2% of the total, with an estimated volume of 1 836 672 m.

Volumetric estimation of wood debris timber in a tropical forest using Ordinary Kriging, Paragominas, Pará State

The objective of this paper was to test the application of geo-statistical models to estimate the volume of wood timber residues in a forest area managed in Paragominas, state of Para. The Warren and Olsen’s and Ordinary Kriging methods were used to estimate the volume of forest residues in sampled and not sampled points. The results confirm that the applied methods were appropriate, given that the estimates for the volume of wood timber residues, in the area of study, showed a small difference of 5.2%, when compared to the actual value obtained.

ESTIMAÇÃO VOLUMÉTRICA DE RESÍDUOS LENHOSOS DE MADEIRA EM UMA FLORESTA TROPICAL ATRAVÉS DA KRIGAGEM ORDINÁRIA, PARAGOMINAS, ESTADO DO PARÁ

O objetivo deste trabalho foi testar a aplicacao de modelos da geoestatistica para estimar o volume de residuos lenhosos de madeira em uma area de floresta manejada no municipio de Paragominas, estado do Para. Os metodos de Warren e Olsen e da Krigagem Ordinaria foram utilizados para estimar o volume dos residuos florestais em pontos amostrados e nao amostrados. Os resultados confirmam que a aplicacao dos metodos foi adequada, uma vez que a estimativa para o volume dos residuos, da area em estudo, apresentou uma pequena diferenca 5,2%, em relacao ao valor real obtido.