Spatio-temporal modeling of agricultural yield data with an application to pricing crop insurance contracts

This article presents a statistical model of agricultural yield data based on a set of hierarchical Bayesian models that allows joint modeling of temporal and spatial autocorrelation. This method captures a comprehensive range of the various uncertainties involved in predicting crop insurance premium rates as opposed to the more traditional ad hoc, two-stage methods that are typically based on independent estimation and prediction. A panel data set of county-average yield data was analyzed for 290 counties in the State of Parana (Brazil) for the period of 1990 through 2002. Posterior predictive criteria are used to evaluate different model specifications. This article provides substantial improvements in the statistical and actuarial methods often applied to the calculation of insurance premium rates. These improvements are especially relevant to situations where data are limited.

Spatial Modeling of a Soil Fertility Index using Visible-Near-Infrared Spectra and Terrain Attributes

Our objective was to develop a methodology to predict soil fertility using visible near-infrared (vis-NIR) diffuse reflectance spectra and terrain attributes derived from a digital elevation model (DEM). Specifically, our aims were to: (i) assemble a minimum data set to develop a soil fertility index for sugarcane (Sarcharum officinarum L.) (SFI-SC) for biofuel production in tropical soils; (ii) construct a model to predict the SFI-SC using soil vis-NIR spectra and terrain attributes; and (iii) produce a soil fertility map for our study area and assess it by comparing it with a green vegetation index (GVI). The study area was 185 ha located in sao Paulo State, Brazil. In total, 184 soil samples were collected and analyzed for a range of soil chemical and physical properties. Their vis-NIR spectra were collected from 400 to 2500 nm. The Shuttle Radar Topographic Mission 3-arcsec (90-m resolution) DEM of the area was used to derive 17 terrain attributes. A minimum data set of soil properties was selected to develop the SFI-SC. The SFI-SC consisted of three classes: Class 1, the highly fertile soils; Class 2, the fertile soils; and Class 3, the least fertile soils. It was derived heuristically with conditionals and using expert knowledge. The index was modeled with the spectra and terrain data using cross-validated decision trees. The cross-validation of the model correctly predicted Class 1 in 75% of cases, Class 2 in 61%, and Class 3 in 65%. A fertility map was derived for the study area and compared with a map of the GVI. Our approach offers a methodology that incorporates expert knowledge to derive the SFI-SC and uses a versatile spectro-spatial methodology that may be implemented for rapid and accurate determination of soil fertility and better exploration of areas suitable for production.

Spatial heterogeneity of leaf wetness duration in apple trees and its influence on performance of a warning system for sooty blotch and flyspeck

To determine the effect of sensor placement on the performance of a disease-warning system for sooty blotch and flyspeck (SBFS), we measured leaf wetness duration (LWD) at 12 canopy positions in apple trees, then simulated operation of the disease-warning system using LWD measurements from different parts of the canopy. LWD sensors were placed in four trees within one Iowa orchard during two growing seasons, and in one tree in each of four orchards during a single growing season. The LWD measurements revealed substantial heterogeneity among sensor locations. In all data sets, the upper, eastern portion of the canopy had the longest mean daily LWD, and was the first site to form dew and the last to dry. The lower, western portion of the canopy averaged about 3 It less LWD per day than the top of the canopy, and was the last zone where dew formed and the first to dry off. On about 25% of nights when dew occurred in the top of the canopy, no dew formed in the lower, western canopy. Intracanopy variability of LWD was more pronounced when dew was the sole source of wetness than on days when rainfall occurred. Daily LWD in the upper, eastern portion of the canopy was slightly less than reference measurements made at a 0.7-m height over turfgrass located near the orchard. When LWD measurements from several canopy positions were input to the SBFS warning system, timing of occurrence of a fungicide-spray threshold varied by as much as 30 days among canopy positions. Under Iowa conditions, placement of an LWD sensor at an unobstructed site over turfgrass was a fairly accurate surrogate for the wettest part of the canopy. Therefore, such an extra-canopy LWD sensor might be substituted for a within-canopy sensor to enhance operational reliability of the SBFS warning system.

Assessing the ex ante economic impacts of transportation infrastructure policies in Brazil

This paper uses a fully operational inter-regional computable general equilibrium (CGE) model implemented for the Brazilian economy, based on previous work by Haddad and Hewings, in order to assess the likely economic effects of road transportation policy changes in Brazil. Among the features embedded in this framework, modelling of external scale economies and transportation costs provides an innovative way of dealing explicitly with theoretical issues related to integrated regional systems. The model is calibrated for 109 regions. The explicit modelling of transportation costs built into the inter-regional CGE model, based on origin-destination flows, which takes into account the spatial structure of the Brazilian economy, creates the capability of integrating the inter-regional CGE model with a geo-coded transportation network model enhancing the potential of the framework in understanding the role of infrastructure on regional development. The transportation model used is the so-called Highway Development and Management, developed by the World Bank, implemented using the software TransCAD. Further extensions of the current model specification for integrating other features of transport planning in a continental industrialising country like Brazil are discussed, with the goal of building a bridge between conventional transport planning practices and the innovative use of CGE models. In order to illustrate the analytical power of the integrated system, the authors present a set of simulations, which evaluate the ex ante economic impacts of physical/qualitative changes in the Brazilian road network (for example, a highway improvement), in accordance with recent policy developments in Brazil. Rather than providing a critical evaluation of this debate, they intend to emphasise the likely structural impacts of such policies. They expect that the results will reinforce the need to better specifying spatial interactions in inter-regional CGE models.

Non-Spatial Government Policies and Regional Income Inequality in Brazil

Silveira Neto R. Da M. and Azzoni C. R. Non-spatial government policies and regional income inequality in Brazil, Regional Studies. This paper uses both macro- and micro-data to analyse the role of social programmes in the recent reduction in Brazilian regional income inequality. Convergence indicators are presented for different sources of regional income in the period 1995-2006. A decomposition of the Gini indicator allows the identification of the role of each of these income sources with respect to the reduction of regional inequality during the period. The results point out that both labour productivity and government non-spatial policies - mainly minimum wage changes and income transference programmes - do have a role in explaining regional inequality reduction during the period. [image omitted] Silveira Neto R. Da M. et Azzoni C. R. Les politiques gouvernementales non-spatiales et l`ecart des revenus regionaux au Bresil, Regional Studies. Cet article emploie des donnees a la fois macroeconomiques et microeconomiques afin d`analyser le role des programmes d`actions sociales quant a la baisse recente de l`ecart des revenus regionaux au Bresil. On presente des indicateurs de convergence pour diverses sources des revenus regionaux pour la periode allant de 1995 a 2006. Une decomposition du coefficient de Gini permet d`identifier le role de chacune de ces sources des revenus par rapport a la baisse de l`ecart des revenus pendant cette periode. Les resultats indiquent que la productivite du travail et les politiques gouvernementales non-spatiales - notamment la modification du salaire minimum et les programmes visant le transfert des revenus - ont un role a jouer pour expliquer la baisse de l`ecart des revenus regionaux pendant la periode en question. Convergence Productivite du travail Transfert des revenus Salaire minimum Effets spatiaux des politiques non-spatiales Silveira Neto R. Da M. und Azzoni C. R. Nicht raumliche Regierungspolitiken und das regionale Einkommensungleichgewicht in Brasilien, Regional Studies. In diesem Beitrag analysieren wir mit Hilfe von Makro- und Mikrodaten die Rolle von sozialen Programmen bei der unlangst erzielten Verringerung des regionalen Einkommensungleichgewichts in Brasilien. Wir stellen Konvergenz-Indikatoren fur verschiedene regionale Einkommensquellen im Zeitraum von 1995 bis 2006 vor. Eine Dekomposition des Gini-Indikators ermoglicht die Identifizierung der jeweiligen Rolle dieser Einkommensquellen fur die Verringerung des regionalen Ungleichgewichts im betreffenden Zeitraum. Die Ergebnisse weisen darauf hin, dass sowohl die Produktivitat der Arbeitskrafte als auch die nicht raumlichen Regierungspolitiken - in erster Linie Veranderungen beim Mindestlohn und Programme fur Einkommenstransfers - als Grunde fur die Verringerung des regionalen Ungleichgewichts in dieser Periode durchaus eine Rolle spielen. Konvergenz Arbeitsproduktivitat Einkommenstransfer Mindestlohn Raumliche Auswirkungen nicht raumlicher Politiken Silveira Neto R. Da M. y Azzoni C. R. Politicas gubernamentales no espaciales y desigualdades de ingresos regionales en Brasil, Regional Studies. En este articulo utilizamos datos macro y micro para analizar el papel de los programas sociales en la reciente reduccion en las desigualdades de ingresos regionales de Brasil. Presentamos los indicadores de convergencia para diferentes fuentes de ingresos regionales en el periodo de 1995 a 2006. Una descomposicion del indice Gini permite identificar el papel de cada una de estas fuentes de ingresos con respecto a la reduccion de las desiguadades regionales durante este periodo. Los resultados destacan que tanto la productividad laboral como las politicas no espaciales del gobierno - principalmente los cambios de salario minimo y los programas de transferencias de ingresos - desempenan una funcion a la hora de explicar la reduccion de las desigualdades regionales durante este periodo. Convergencia Productividad laboral Transferencias de ingresos Salario minimo Efectos espaciales de politicas no espaciales.

Elevated left and reduced right orbitomedial prefrontal fractional anisotropy in adults with bipolar disorder revealed by tract-based spatial statistics

Context Diffusion tensor imaging (DTI) studies in adults with bipolar disorder (BD) indicate altered white matter (WM) in the orbitomedial prefrontal cortex (OMPFC), potentially underlying abnormal prefrontal corticolimbic connectivity and mood dysregulatioin in BD. Objective: To use tract-based spatial statistics (TBSS) to examine VVM skeleton (ie, the most compact whole-brain WM) in subjects with BD vs healthy control subjects. Design: Cross-sectional, case-control, whole-brain DTI using TBSS. Setting: University research institute. Participants: Fifty-six individuals, 31 having a DSM-IV diagnosis of BD type 1 (mean age, 35.9 years [age range, 24-52 years]) and 25 controls (mean age, 29.5 years [age range, 19-52 years]). Main Outcome Measures: Fractional anisotropy (FA) longitudinal and radial diffusivities in subjects with BD vs controls (covarying for age) and their relationships with clinical and demographic variables. Results: Subjects with BD vs controls had significantly greater FA (t > 3.0, P <=.05 corrected) in the left uncinate fasciculus (reduced radial diffusivity distally and increased longitudinal diffusivity centrally), left optic radiation (increased longitudinal diffusivity), and right anterothalamic radiation (no significant diffusivity change). Subjects with BD vs controls had significantly reduced FA (t > 3.0, P <=.05 corrected) in the right uncinate fasciculus (greater radial diffusivity). Among subjects with BD, significant negative correlations (P <.01) were found between age and FA in bilateral uncinate fasciculi and in the right anterothalamic radiation, as well as between medication load and FA in the left optic radiation. Decreased FA (P <.01) was observed in the left optic radiation and in the right anterothalamic radiation among subjects with BD taking vs those not taking mood stabilizers, as well as in the left optic radiation among depressed vs remitted subjects with BD. Subjects having BD with vs without lifetime alcohol or other drug abuse had significantly decreased FA in the left uncinate fasciculus. Conclusions: To our knowledge, this is the first study to use TBSS to examine WM in subjects with BD. Subjects with BD vs controls showed greater WM FA in the left OMPFC that diminished with age and with alcohol or other drug abuse, as well as reduced WM FA in the right OMPFC. Mood stabilizers and depressed episode reduced WM FA in left-sided sensory visual processing regions among subjects with BD. Abnormal right vs left asymmetry in FA in OMPFC WM among subjects with BD, likely reflecting increased proportions of left-sided longitudinally aligned and right-sided obliquely aligned myelinated fibers, may represent a biologic mechanism for mood dysregulation in BD.

Study of the spatial distribution of the absorbed dose in blood volumes irradiated using a teletherapy unit

Blood irradiation can be performed using a dedicated blood irradiator or a teletherapy unit. A thermal device providing appropriate storage conditions during blood components irradiation with a teletherapy unit has been recently proposed. However, the most appropriated volume of the thermal device was not indicated. The goal of this study was to indicate the most appropriated blood volume for irradiation using a teletherapy unit in order to minimize both the dose heterogeneity in the volume and the blood irradiation time using these equipments. Theoretical and experimental methods were used to study the dose distribution in the blood volume irradiated using a linear accelerator and a cobalt-60 therapy machine. The calculation of absorbed doses in the middle plane of cylindrical acrylic volumes was accomplished by a treatment planning system. Experimentally, we also used cylindrical acrylic phantoms and thermoluminescent dosimeters to confirm the calculated doses. The data obtained were represented by isodose curves. We observed that an irradiation volume should have a height of 28 cm and a diameter of 28 cm and a height of 35 cm and a diameter of 35 cm, when the irradiation is to be performed by a linear accelerator and a cobalt-60 teletherapy unit, respectively. Calculated values of relative doses varied from 93% to 100% in the smaller volume, and from 66% to 100% in the largest one. A difference of 5.0%, approximately, was observed between calculated and experimental data. The size of these volumes permits the irradiation of blood bags in only one bath without compromising the homogeneity of the absorbed dose over the irradiated volume. Thus, these irradiation volumes can be recommend to minimize the irradiation time when a teletherapy unit is used to irradiate blood. (C) 2010 Elsevier Ltd. All rights reserved.

A Comparison of the Home Range Sizes of Mainland and Island Populations of Black-Faced Lion Tamarins (Leontopithecus caissara) Using Different Spatial Analysis

The critically endangered black-faced lion tamarin, Leontopithecus caissara, has a restricted geographical distribution consisting of small mainland and island populations, each with distinct habitats in coastal southeastern Brazil. Necessary conservation management actions require an assessment of whether differences in habitats are reflected in use of space by the species. We studied two tamarin groups on the mainland at Sao Paulo state between August 2005 and March 2007, and compared the results with data from Superagui Island. Three home range estimators were used: minimum convex polygon (MCP), Kernel, and the new technique presented dissolved monthly polygons (DMP). These resulted, respectively, in home ranges of 345, 297, and 282 ha for the 12-month duration of the study. Spatial overlap of mainland groups was extensive, whereas temporal overlap was not, a pattern that indicates resource partitioning is an important strategy to avoid intraspecific competition. L. caissara large home ranges seem to be dynamic, with constant incorporation of new areas and abandonment of others through time. The main difference between mainland and island groups is the amount and variety of sleeping sites. A better understanding of the home range sizes, day range lengths, and territorial behavior of this species will aid in developing better management strategies for its protection. Additionally, the presented DMP protocol is a useful improvement over the MCP method as it results in more realistic home range sizes for wildlife species. Am. J. Primatol. 73: 1114-1126, 2011. (C) 2011 Wiley Periodicals, Inc.

Are Reanalysis Data Useful for Calculating Climate Indices over South America?

Precipitation and temperature climate indices are calculated using the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis and validated against observational data from some stations over Brazil and other data sources. The spatial patterns of the climate indices trends are analyzed for the period 1961-1990 over South America. In addition, the correlation and linear regression coefficients for some specific stations were also obtained in order to compare with the reanalysis data. In general, the results suggest that NCEP/NCAR reanalysis can provide useful information about minimum temperature and consecutive dry days indices at individual grid cells in Brazil. However, some regional differences in the climate indices trends are observed when different data sets are compared. For instance, the NCEP/NCAR reanalysis shows a reversal signal for all rainfall annual indices and the cold night index over Argentina. Despite these differences, maps of the trends for most of the annual climate indices obtained from the NCEP/NCAR reanalysis and BRANT analysis are generally in good agreement with other available data sources and previous findings in the literature for large areas of southern South America. The pattern of trends for the precipitation annual indices over the 30 years analyzed indicates a change to wetter conditions over southern and southeastern parts of Brazil, Paraguay, Uruguay, central and northern Argentina, and parts of Chile and a decrease over southwestern South America. All over South America, the climate indices related to the minimum temperature (warm or cold nights) have clearly shown a warming tendency; however, no consistent changes in maximum temperature extremes (warm and cold days) have been observed. Therefore, one must be careful before suggesting an), trends for warm or cold days.

PCA Tomography: how to extract information from data cubes

Astronomy has evolved almost exclusively by the use of spectroscopic and imaging techniques, operated separately. With the development of modern technologies, it is possible to obtain data cubes in which one combines both techniques simultaneously, producing images with spectral resolution. To extract information from them can be quite complex, and hence the development of new methods of data analysis is desirable. We present a method of analysis of data cube (data from single field observations, containing two spatial and one spectral dimension) that uses Principal Component Analysis (PCA) to express the data in the form of reduced dimensionality, facilitating efficient information extraction from very large data sets. PCA transforms the system of correlated coordinates into a system of uncorrelated coordinates ordered by principal components of decreasing variance. The new coordinates are referred to as eigenvectors, and the projections of the data on to these coordinates produce images we will call tomograms. The association of the tomograms (images) to eigenvectors (spectra) is important for the interpretation of both. The eigenvectors are mutually orthogonal, and this information is fundamental for their handling and interpretation. When the data cube shows objects that present uncorrelated physical phenomena, the eigenvector`s orthogonality may be instrumental in separating and identifying them. By handling eigenvectors and tomograms, one can enhance features, extract noise, compress data, extract spectra, etc. We applied the method, for illustration purpose only, to the central region of the low ionization nuclear emission region (LINER) galaxy NGC 4736, and demonstrate that it has a type 1 active nucleus, not known before. Furthermore, we show that it is displaced from the centre of its stellar bulge.

Malaria on the Amazonian frontier: Transmission dynamics, risk factors, spatial distribution, and prospects for control

Little follow-up data on malaria transmission in communities originating from frontier settlements in Amazonia are available. Here we describe a cohort study in a frontier settlement in Acre, Brazil, where 509 subjects contributed 489.7 person-years of follow-up. The association between malaria morbidity during the follow-up and individual, household, and spatial covariates was explored with mixed-effects logistic regression models and spatial analysis. Incidence rates for Plasmodium vivax and Plasmodium falciparum malaria were 30.0/100 and 16.3/100 person-years at risk, respectively. Malaria morbidity was strongly associated with land clearing and farming, and decreased after five years of residence in the area, suggesting that clinical immunity develops among subjects exposed to low malaria endemicity. Significant spatial clustering of malaria was observed in the areas of most recent occupation, indicating that the continuous influx of nonimmune settlers to forest-fringe areas perpetuates the cycle of environmental change and colonization that favors malaria transmission in rural Amazonia.

MODIS aerosol optical depth Retrievals with high spatial resolution over an urban area using the critical reflectance

[1] The retrieval of aerosol optical depth (Ta) over land by satellite remote sensing is still a challenge when a high spatial resolution is required. This study presents a tool that uses satellite measurements to dynamically identify the aerosol optical model that best represents the optical properties of the aerosol present in the atmosphere. We use aerosol critical reflectance to identify the single scattering albedo of the aerosol layer. Two case studies show that the Sao Paulo region can have different aerosol properties and demonstrates how the dynamic methodology works to identify those differences to obtain a better T a retrieval. The methodology assigned the high single scattering albedo aerosol model (pi o( lambda = 0.55) = 0.90) to the case where the aerosol source was dominated by biomass burning and the lower pi(o) model (pi(o) (lambda = 0.55) = 0.85) to the case where the local urban aerosol had the dominant influence on the region, as expected. The dynamic methodology was applied using cloud-free data from 2002 to 2005 in order to retrieve Ta with Moderate Resolution Imaging Spectroradiometer ( MODIS). These results were compared with collocated data measured by AERONET in Sao Paulo. The comparison shows better results when the dynamic methodology using two aerosol optical models is applied (slope 1.06 +/- 0.08 offset 0.01 +/- 0.02 r(2) 0.6) than when a single and fixed aerosol model is used (slope 1.48 +/- 0.11 and offset - 0.03 +/- 0.03 r(2) 0.6). In conclusion the dynamical methodology is shown to work well with two aerosol models. Further studies are necessary to evaluate the methodology in other regions and under different conditions.

DIAGNOSTIC TECHNIQUES OF LOCAL INFLUENCE IN SPATIAL ANALYSIS OF SOYBEAN YIELD

Modeling of spatial dependence structure, concerning geoestatistics approach, is an indispensable tool for fixing parameters that define this structure, applied on interpolation of values in places that are not sampled, by kriging techniques. However, the estimation of parameters can be greatly affected by the presence of atypical observations on sampled data. Thus, this trial aimed at using diagnostics techniques of local influence in spatial linear Gaussians models, applied at geoestatistics in order to evaluate sensitivity of maximum likelihood estimators and restrict maximum likelihood to small perturbations in these data. So, studies with simulated and experimental data were performed. Those results, obtained from the study of real data, allowed us to conclude that the presence of atypical values among the sampled data can have a strong influence on thematic maps, changing, therefore, the spatial dependence. The application of diagnostics techniques of local influence should be part of any geoestatistic analysis, ensuring that the information from thematic maps has better quality and can be used with greater security by farmers.

Dynamic Changes in the Mental Rotation Network Revealed by Pattern Recognition Analysis of fMRI Data

We investigated the temporal dynamics and changes in connectivity in the mental rotation network through the application of spatio-temporal support vector machines (SVMs). The spatio-temporal SVM [Mourao-Miranda, J., Friston, K. J., et al. (2007). Dynamic discrimination analysis: A spatial-temporal SVM. Neuroimage, 36, 88-99] is a pattern recognition approach that is suitable for investigating dynamic changes in the brain network during a complex mental task. It does not require a model describing each component of the task and the precise shape of the BOLD impulse response. By defining a time window including a cognitive event, one can use spatio-temporal fMRI observations from two cognitive states to train the SVM. During the training, the SVM finds the discriminating pattern between the two states and produces a discriminating weight vector encompassing both voxels and time (i.e., spatio-temporal maps). We showed that by applying spatio-temporal SVM to an event-related mental rotation experiment, it is possible to discriminate between different degrees of angular disparity (0 degrees vs. 20 degrees, 0 degrees vs. 60 degrees, and 0 degrees vs. 100 degrees), and the discrimination accuracy is correlated with the difference in angular disparity between the conditions. For the comparison with highest accuracy (08 vs. 1008), we evaluated how the most discriminating areas (visual regions, parietal regions, supplementary, and premotor areas) change their behavior over time. The frontal premotor regions became highly discriminating earlier than the superior parietal cortex. There seems to be a parcellation of the parietal regions with an earlier discrimination of the inferior parietal lobe in the mental rotation in relation to the superior parietal. The SVM also identified a network of regions that had a decrease in BOLD responses during the 100 degrees condition in relation to the 0 degrees condition (posterior cingulate, frontal, and superior temporal gyrus). This network was also highly discriminating between the two conditions. In addition, we investigated changes in functional connectivity between the most discriminating areas identified by the spatio-temporal SVM. We observed an increase in functional connectivity between almost all areas activated during the 100 degrees condition (bilateral inferior and superior parietal lobe, bilateral premotor area, and SMA) but not between the areas that showed a decrease in BOLD response during the 100 degrees condition.