Comparison between artificial neural networks and maximum likelihood classification in digital soil mapping

Soil surveys are the main source of spatial information on soils and have a range of different applications, mainly in agriculture. The continuity of this activity has however been severely compromised, mainly due to a lack of governmental funding. The purpose of this study was to evaluate the feasibility of two different classifiers (artificial neural networks and a maximum likelihood algorithm) in the prediction of soil classes in the northwest of the state of Rio de Janeiro. Terrain attributes such as elevation, slope, aspect, plan curvature and compound topographic index (CTI) and indices of clay minerals, iron oxide and Normalized Difference Vegetation Index (NDVI), derived from Landsat 7 ETM+ sensor imagery, were used as discriminating variables. The two classifiers were trained and validated for each soil class using 300 and 150 samples respectively, representing the characteristics of these classes in terms of the discriminating variables. According to the statistical tests, the accuracy of the classifier based on artificial neural networks (ANNs) was greater than of the classic Maximum Likelihood Classifier (MLC). Comparing the results with 126 points of reference showed that the resulting ANN map (73.81 %) was superior to the MLC map (57.94 %). The main errors when using the two classifiers were caused by: a) the geological heterogeneity of the area coupled with problems related to the geological map; b) the depth of lithic contact and/or rock exposure, and c) problems with the environmental correlation model used due to the polygenetic nature of the soils. This study confirms that the use of terrain attributes together with remote sensing data by an ANN approach can be a tool to facilitate soil mapping in Brazil, primarily due to the availability of low-cost remote sensing data and the ease by which terrain attributes can be obtained.

Land use/cover classification in the Brazilian Amazon using satellite images

Land use/cover classification is one of the most important applications in remote sensing. However, mapping accurate land use/cover spatial distribution is a challenge, particularly in moist tropical regions, due to the complex biophysical environment and limitations of remote sensing data per se. This paper reviews experiments related to land use/cover classification in the Brazilian Amazon for a decade. Through comprehensive analysis of the classification results, it is concluded that spatial information inherent in remote sensing data plays an essential role in improving land use/cover classification. Incorporation of suitable textural images into multispectral bands and use of segmentation‑based method are valuable ways to improve land use/cover classification, especially for high spatial resolution images. Data fusion of multi‑resolution images within optical sensor data is vital for visual interpretation, but may not improve classification performance. In contrast, integration of optical and radar data did improve classification performance when the proper data fusion method was used. Among the classification algorithms available, the maximum likelihood classifier is still an important method for providing reasonably good accuracy, but nonparametric algorithms, such as classification tree analysis, have the potential to provide better results. However, they often require more time to achieve parametric optimization. Proper use of hierarchical‑based methods is fundamental for developing accurate land use/cover classification, mainly from historical remotely sensed data.

Inhibitory effects in the detection of 1 cpd jo targets superimposed to angular frequency stimuli or sinewave gratings

Independence among channels processing different aspects of spatial information, including orthogonal stimuli, has been generally assumed in the literature. We tested independence between the processing of jo targets and the processing of either vertical sinusoidal gratings or angular frequency stimuli with suprathreshold summation. We found the detection of a jo target at 1 cpd to be affected in an inhibitory fashion by either background angular frequencies in the range of 3-96 cycles or sinewave gratings in the range of 0.8-3.0 cpd. These results demonstrate interactions both among orthogonal stimuli and among channels processing vertical sinewave gratings and jo target stimuli. Our discussion focuses on the hypothesis of frequency decomposition in polar coordinates

Effects of septal cholinergic lesion on rat exploratory behavior in an open-field

The medial septum participates in the modulation of exploratory behavior triggered by novelty. Also, selective lesions of the cholinergic component of the septohippocampal system alter the habituation of rats to an elevated plus-maze without modifying anxiety indices. We investigated the effects of the intraseptal injection of the cholinergic immunotoxin 192 IgG-saporin (SAP) on the behavior of rats in an open-field. Thirty-nine male Wistar rats (weight: 194-230 g) were divided into three groups, non-injected controls and rats injected with either saline (0.5 µl) or SAP (237.5 ng/0.5 µl). Twelve days after surgery, the animals were placed in a square open-field (120 cm) and allowed to freely explore for 5 min. After the test, the rats were killed by decapitation and the septum, hippocampus and frontal cortex were removed and assayed for acetylcholinesterase activity. SAP increased acetylcholinesterase activity in the septum, hippocampus and frontal cortex and decreased the total distance run (9.15 ± 1.51 m) in comparison to controls (13.49 ± 0.91 m). The time spent in the center and at the periphery was not altered by SAP but the distance run was reduced during the first and second minutes (2.43 ± 0.36 and 1.75 ± 0.34 m) compared to controls (4.18 ± 0.26 and 3.14 ± 0.25 m). SAP-treated rats showed decreased but persistent exploration throughout the session. These results suggest that septohippocampal cholinergic mechanisms contribute to at least two critical processes, one related to the motivation to explore new environments and the other to the acquisition and storage of spatial information (i.e., spatial memory).

Spatial variability of particle size fractions of an Oxisol cultivated with conilon coffee

Information on the spatial distribution of particle size fractions is essential for use planning and management of soils. The aim of this work to was to study the spatial variability of particle size fractions of a Typic Hapludox cultivated with conilon coffee. The soil samples were collected at depths of 0-0.20 and 0.20-0.40 m in the coffee canopy projection, totaling 109 georeferentiated points. At the depth of 0.2-0.4 m the clay fraction showed average value significantly higher, while the sand fraction showed was higher in the depth of 0-0.20 m. The silt showed no significant difference between the two depths. The particle size fractions showed medium and high spatial variability. The levels of total sand and clay have positive and negative correlation, respectively, with the altitude of the sampling points, indicating the influence of landscape configuration.

Spatial analysis of urban violence based on emergency room data

OBJECTIVE: To estimate the spatial intensity of urban violence events using wavelet-based methods and emergency room data. METHODS: Information on victims attended at the emergency room of a public hospital in the city of São Paulo, Southeastern Brazil, from January 1, 2002 to January 11, 2003 were obtained from hospital records. The spatial distribution of 3,540 events was recorded and a uniform random procedure was used to allocate records with incomplete addresses. Point processes and wavelet analysis technique were used to estimate the spatial intensity, defined as the expected number of events by unit area. RESULTS: Of all georeferenced points, 59% were accidents and 40% were assaults. There is a non-homogeneous spatial distribution of the events with high concentration in two districts and three large avenues in the southern area of the city of São Paulo. CONCLUSIONS: Hospital records combined with methodological tools to estimate intensity of events are useful to study urban violence. The wavelet analysis is useful in the computation of the expected number of events and their respective confidence bands for any sub-region and, consequently, in the specification of risk estimates that could be used in decision-making processes for public policies.

Spatial analysis of leprosy incidence and associated socioeconomic factors

OBJECTIVE: To identify clusters of the major occurrences of leprosy and their associated socioeconomic and demographic factors. METHODS: Cases of leprosy that occurred between 1998 and 2007 in São José do Rio Preto (southeastern Brazil) were geocodified and the incidence rates were calculated by census tract. A socioeconomic classification score was obtained using principal component analysis of socioeconomic variables. Thematic maps to visualize the spatial distribution of the incidence of leprosy with respect to socioeconomic levels and demographic density were constructed using geostatistics. RESULTS: While the incidence rate for the entire city was 10.4 cases per 100,000 inhabitants annually between 1998 and 2007, the incidence rates of individual census tracts were heterogeneous, with values that ranged from 0 to 26.9 cases per 100,000 inhabitants per year. Areas with a high leprosy incidence were associated with lower socioeconomic levels. There were identified clusters of leprosy cases, however there was no association between disease incidence and demographic density. There was a disparity between the places where the majority of ill people lived and the location of healthcare services. CONCLUSIONS: The spatial analysis techniques utilized identified the poorer neighborhoods of the city as the areas with the highest risk for the disease. These data show that health departments must prioritize politico-administrative policies to minimize the effects of social inequality and improve the standards of living, hygiene, and education of the population in order to reduce the incidence of leprosy.

Spatial study of homicide rates in the state of Bahia, Brazil, 1996-2010

OBJECTIVE To analyze the spatial distribution of homicide mortality in the state of Bahia, Northeastern Brazil. METHODS Ecological study of the 15 to 39-year old male population in the state of Bahia in the period 1996-2010. Data from the Mortality Information System, relating to homicide (X85-Y09) and population estimates from the Brazilian Institute of Geography and Statistics were used. The existence of spatial correlation, the presence of clusters and critical areas of the event studied were analyzed using Moran’s I Global and Local indices. RESULTS A non-random spatial pattern was observed in the distribution of rates, as was the presence of three clusters, the first in the north health district, the second in the eastern region, and the third cluster included townships in the south and the far south of Bahia. CONCLUSIONS The homicide mortality in the three different critical areas requires further studies that consider the socioeconomic, cultural and environmental characteristics in order to guide specific preventive and interventionist practices.

Temporal trends and spatial distribution of unsafe abortion in Brazil, 1996-2012

OBJECTIVE To analyze temporal trends and distribution patterns of unsafe abortion in Brazil. METHODS Ecological study based on records of hospital admissions of women due to abortion in Brazil between 1996 and 2012, obtained from the Hospital Information System of the Ministry of Health. We estimated the number of unsafe abortions stratified by place of residence, using indirect estimate techniques. The following indicators were calculated: ratio of unsafe abortions/100 live births and rate of unsafe abortion/1,000 women of childbearing age. We analyzed temporal trends through polynomial regression and spatial distribution using municipalities as the unit of analysis. RESULTS In the study period, a total of 4,007,327 hospital admissions due to abortions were recorded in Brazil. We estimated a total of 16,905,911 unsafe abortions in the country, with an annual mean of 994,465 abortions (mean unsafe abortion rate: 17.0 abortions/1,000 women of childbearing age; ratio of unsafe abortions: 33.2/100 live births). Unsafe abortion presented a declining trend at national level (R2: 94.0%, p < 0.001), with unequal patterns between regions. There was a significant reduction of unsafe abortion in the Northeast (R2: 93.0%, p < 0.001), Southeast (R2: 92.0%, p < 0.001) and Central-West regions (R2: 64.0%, p < 0.001), whereas the North (R2: 39.0%, p = 0.030) presented an increase, and the South (R2: 22.0%, p = 0.340) remained stable. Spatial analysis identified the presence of clusters of municipalities with high values for unsafe abortion, located mainly in states of the North, Northeast and Southeast Regions. CONCLUSIONS Unsafe abortion remains a public health problem in Brazil, with marked regional differences, mainly concentrated in the socioeconomically disadvantaged regions of the country. Qualification of attention to women’s health, especially to reproductive aspects and attention to pre- and post-abortion processes, are necessary and urgent strategies to be implemented in the country.

Temporal evolution and spatial distribution of maternal death

OBJECTIVE To analyze the temporal evolution of maternal mortality and its spatial distribution.METHODS Ecological study with a sample made up of 845 maternal deaths in women between 10 and 49 years, registered from 1999 to 2008 in the state of Rio Grande do Sul, Southern Brazil. Data were obtained from Information System on Mortality of Ministry of Health. The maternal mortality ratio and the specific maternal mortality ratio were calculated from records, and analyzed by the Poisson regression model. In the spatial distribution, three maps of the state were built with the rates in the geographical macro-regions, in 1999, 2003, and 2008.RESULTS There was an increase of 2.0% in the period of ten years (95%CI 1.00;1.04; p = 0.01), with no significant change in the magnitude of the maternal mortality ratio. The Serra macro-region presented the highest maternal mortality ratio (1.15, 95%CI 1.08;1.21; p < 0.001). Most deaths in Rio Grande do Sul were of white women over 40 years, with a lower level of education. The time of delivery/abortion and postpartum are times of increased maternal risk, with a greater negative impact of direct causes such as hypertension and bleeding.CONCLUSIONS The lack of improvement in maternal mortality ratio indicates that public policies had no impact on women’s reproductive and maternal health. It is needed to qualify the attention to women’s health, especially in the prenatal period, seeking to identify and prevent risk factors, as a strategy of reducing maternal death.

Spatial distribution and socioeconomic context of tuberculosis in Rio de Janeiro, Brazil

OBJECTIVE To analyze the spatial distribution of risk for tuberculosis and its socioeconomic determinants in the city of Rio de Janeiro, Brazil.METHODS An ecological study on the association between the mean incidence rate of tuberculosis from 2004 to 2006 and socioeconomic indicators of the Censo Demográfico (Demographic Census) of 2000. The unit of analysis was the home district registered in the Sistema de Informação de Agravos de Notificação (Notifiable Diseases Information System) of Rio de Janeiro, Southeastern Brazil. The rates were standardized by sex and age group, and smoothed by the empirical Bayes method. Spatial autocorrelation was evaluated by Moran’s I. Multiple linear regression models were studied and the appropriateness of incorporating the spatial component in modeling was evaluated.RESULTS We observed a higher risk of the disease in some neighborhoods of the port and north regions, as well as a high incidence in the slums of Rocinha and Vidigal, in the south region, and Cidade de Deus, in the west. The final model identified a positive association for the variables: percentage of permanent private households in which the head of the house earns three to five minimum wages; percentage of individual residents in the neighborhood; and percentage of people living in homes with more than two people per bedroom.CONCLUSIONS The spatial analysis identified areas of risk of tuberculosis incidence in the neighborhoods of the city of Rio de Janeiro and also found spatial dependence for the incidence of tuberculosis and some socioeconomic variables. However, the inclusion of the space component in the final model was not required during the modeling process.

Spatial patterns of leprosy in a hyperendemic state in Northern Brazil, 2001-2012

ABSTRACT OBJECTIVE To describe the spatial patterns of leprosy in the Brazilian state of Tocantins. METHODS This study was based on morbidity data obtained from the Sistema de Informações de Agravos de Notificação (SINAN – Brazilian Notifiable Diseases Information System), of the Ministry of Health. All new leprosy cases in individuals residing in the state of Tocantins, between 2001 and 2012, were included. In addition to the description of general disease indicators, a descriptive spatial analysis, empirical Bayesian analysis and spatial dependence analysis were performed by means of global and local Moran’s indexes. RESULTS A total of 14,542 new cases were recorded during the period under study. Based on the annual case detection rate, 77.0% of the municipalities were classified as hyperendemic (> 40 cases/100,000 inhabitants). Regarding the annual case detection rate in < 15 years-olds, 65.4% of the municipalities were hyperendemic (10.0 to 19.9 cases/100,000 inhabitants); 26.6% had a detection rate of grade 2 disability cases between 5.0 and 9.9 cases/100,000 inhabitants. There was a geographical overlap of clusters of municipalities with high detection rates in hyperendemic areas. Clusters with high disease risk (global Moran’s index: 0.51; p < 0.001), ongoing transmission (0.47; p < 0.001) and late diagnosis (0.44; p < 0.001) were identified mainly in the central-north and southwestern regions of Tocantins. CONCLUSIONS We identified high-risk clusters for transmission and late diagnosis of leprosy in the Brazilian state of Tocantins. Surveillance and control measures should be prioritized in these high-risk municipalities.

Spatial analysis of avoidable hospitalizations due to tuberculosis in Ribeirao Preto, SP, Brazil (2006-2012)

ABSTRACT OBJECTIVE To describe the spatial distribution of avoidable hospitalizations due to tuberculosis in the municipality of Ribeirao Preto, SP, Brazil, and to identify spatial and space-time clusters for the risk of occurrence of these events. METHODS This is a descriptive, ecological study that considered the hospitalizations records of the Hospital Information System of residents of Ribeirao Preto, SP, Southeastern Brazil, from 2006 to 2012. Only the cases with recorded addresses were considered for the spatial analyses, and they were also geocoded. We resorted to Kernel density estimation to identify the densest areas, local empirical Bayes rate as the method for smoothing the incidence rates of hospital admissions, and scan statistic for identifying clusters of risk. Softwares ArcGis 10.2, TerraView 4.2.2, and SaTScanTM were used in the analysis. RESULTS We identified 169 hospitalizations due to tuberculosis. Most were of men (n = 134; 79.2%), averagely aged 48 years (SD = 16.2). The predominant clinical form was the pulmonary one, which was confirmed through a microscopic examination of expectorated sputum (n = 66; 39.0%). We geocoded 159 cases (94.0%). We observed a non-random spatial distribution of avoidable hospitalizations due to tuberculosis concentrated in the northern and western regions of the municipality. Through the scan statistic, three spatial clusters for risk of hospitalizations due to tuberculosis were identified, one of them in the northern region of the municipality (relative risk [RR] = 3.4; 95%CI 2.7–4,4); the second in the central region, where there is a prison unit (RR = 28.6; 95%CI 22.4–36.6); and the last one in the southern region, and area of protection for hospitalizations (RR = 0.2; 95%CI 0.2–0.3). We did not identify any space-time clusters. CONCLUSIONS The investigation showed priority areas for the control and surveillance of tuberculosis, as well as the profile of the affected population, which shows important aspects to be considered in terms of management and organization of health care services targeting effectiveness in primary health care.

Spatial distribution of dengue in the city of Cruzeiro, São Paulo State, Brazil: use of geoprocessing tools

The aim of this article is to identify patterns in spatial distribution of cases of dengue fever that occurred in the municipality of Cruzeiro, State of São Paulo, in 2006. This is an ecological and exploratory study using the tools of spatial analysis in the preparation of thematic maps with data from Sinan-Net. An analysis was made by area, taking as unit the IBGE census, the analysis included four months in 2006 which show the occurrence of the disease in the city. The thematic maps were constructed by TerraView 3.3.1 software, the same software provided the values of the indicators of Global Moran (I M) every month and the Kernel estimation. In the year 2006, 691 cases of dengue were georeferenced (with a rate of 864.2 cases/100,000 inhabitants); the indicators of Moran and p-values obtained were I M = 0.080 (March) p = 0.11; I M = 0.285 (April) p = 0.01; I M = 0.201 (May) p = 0.01 and I M = 0.002 (June) p = 0.57. The first cases were identified in the Northeast and Central areas of Cruzeiro and the recent cases, in the North, Northeast and Central. It was possible to identify census tracts where the epidemic began and how it occurred temporally and spatially in the city.

Fasciola hepatica IN BOVINES IN BRAZIL: DATA AVAILABILITY AND SPATIAL DISTRIBUTION

Fasciolosis is a disease of importance for both veterinary and public health. For the first time, georeferenced prevalence data of Fasciola hepatica in bovines were collected and mapped for the Brazilian territory and data availability was discussed. Bovine fasciolosis in Brazil is monitored on a Federal, State and Municipal level, and to improve monitoring it is essential to combine the data collected on these three levels into one dataset. Data were collected for 1032 municipalities where livers were condemned by the Federal Inspection Service (MAPA/SIF) because of the presence of F. hepatica. The information was distributed over 11 states: Espírito Santo, Goiás, Minas Gerais, Mato Grosso do Sul, Mato Grosso, Pará, Paraná, Rio de Janeiro, Rio Grande do Sul, Santa Catarina and São Paulo. The highest prevalence of fasciolosis was observed in the southern states, with disease clusters along the coast of Paraná and Santa Catarina and in Rio Grande do Sul. Also, temporal variation of the prevalence was observed. The observed prevalence and the kriged prevalence maps presented in this paper can assist both animal and human health workers in estimating the risk of infection in their state or municipality.