The impact of spatial data redundancy on SOLAP query performance

Geographic Data Warehouses (GDW) are one of the main technologies used in decision-making processes and spatial analysis, and the literature proposes several conceptual and logical data models for GDW. However, little effort has been focused on studying how spatial data redundancy affects SOLAP (Spatial On-Line Analytical Processing) query performance over GDW. In this paper, we investigate this issue. Firstly, we compare redundant and non-redundant GDW schemas and conclude that redundancy is related to high performance losses. We also analyze the issue of indexing, aiming at improving SOLAP query performance on a redundant GDW. Comparisons of the SB-index approach, the star-join aided by R-tree and the star-join aided by GiST indicate that the SB-index significantly improves the elapsed time in query processing from 25% up to 99% with regard to SOLAP queries defined over the spatial predicates of intersection, enclosure and containment and applied to roll-up and drill-down operations. We also investigate the impact of the increase in data volume on the performance. The increase did not impair the performance of the SB-index, which highly improved the elapsed time in query processing. Performance tests also show that the SB-index is far more compact than the star-join, requiring only a small fraction of at most 0.20% of the volume. Moreover, we propose a specific enhancement of the SB-index to deal with spatial data redundancy. This enhancement improved performance from 80 to 91% for redundant GDW schemas.

A Framework for Exploring Multidimensional Data with 3D Projections

Visualization of high-dimensional data requires a mapping to a visual space. Whenever the goal is to preserve similarity relations a frequent strategy is to use 2D projections, which afford intuitive interactive exploration, e. g., by users locating and selecting groups and gradually drilling down to individual objects. In this paper, we propose a framework for projecting high-dimensional data to 3D visual spaces, based on a generalization of the Least-Square Projection (LSP). We compare projections to 2D and 3D visual spaces both quantitatively and through a user study considering certain exploration tasks. The quantitative analysis confirms that 3D projections outperform 2D projections in terms of precision. The user study indicates that certain tasks can be more reliably and confidently answered with 3D projections. Nonetheless, as 3D projections are displayed on 2D screens, interaction is more difficult. Therefore, we incorporate suitable interaction functionalities into a framework that supports 3D transformations, predefined optimal 2D views, coordinated 2D and 3D views, and hierarchical 3D cluster definition and exploration. For visually encoding data clusters in a 3D setup, we employ color coding of projected data points as well as four types of surface renderings. A second user study evaluates the suitability of these visual encodings. Several examples illustrate the framework`s applicability for both visual exploration of multidimensional abstract (non-spatial) data as well as the feature space of multi-variate spatial data.

A classification methodology for the risk of weed infestation using fuzzy logic

Despite modern weed control practices, weeds continue to be a threat to agricultural production. Considering the variability of weeds, a classification methodology for the risk of infestation in agricultural zones using fuzzy logic is proposed. The inputs for the classification are attributes extracted from estimated maps for weed seed production and weed coverage using kriging and map analysis and from the percentage of surface infested by grass weeds, in order to account for the presence of weed species with a high rate of development and proliferation. The output for the classification predicts the risk of infestation of regions of the field for the next crop. The risk classification methodology described in this paper integrates analysis techniques which may help to reduce costs and improve weed control practices. Results for the risk classification of the infestation in a maize crop field are presented. To illustrate the effectiveness of the proposed system, the risk of infestation over the entire field is checked against the yield loss map estimated by kriging and also with the average yield loss estimated from a hyperbolic model.

An integrated database on ticks and tick-borne zoonoses in the tropics and subtropics with special reference to developing and emerging countries

Tick-borne zoonoses (TBZ) are emerging diseases worldwide. A large amount of information (e.g. case reports, results of epidemiological surveillance, etc.) is dispersed through various reference sources (ISI and non-ISI journals, conference proceedings, technical reports, etc.). An integrated database-derived from the ICTTD-3 project (http://www.icttd.nl)-was developed in order to gather TBZ records in the (sub-)tropics, collected both by the authors and collaborators worldwide. A dedicated website (http://www.tickbornezoonoses.org) was created to promote collaboration and circulate information. Data collected are made freely available to researchers for analysis by spatial methods, integrating mapped ecological factors for predicting TBZ risk. The authors present the assembly process of the TBZ database: the compilation of an updated list of TBZ relevant for (sub-)tropics, the database design and its structure, the method of bibliographic search, the assessment of spatial precision of geo-referenced records. At the time of writing, 725 records extracted from 337 publications related to 59 countries in the (sub-)tropics, have been entered in the database. TBZ distribution maps were also produced. Imported cases have been also accounted for. The most important datasets with geo-referenced records were those on Spotted Fever Group rickettsiosis in Latin-America and Crimean-Congo Haemorrhagic Fever in Africa. The authors stress the need for international collaboration in data collection to update and improve the database. Supervision of data entered remains always necessary. Means to foster collaboration are discussed. The paper is also intended to describe the challenges encountered to assemble spatial data from various sources and to help develop similar data collections.

Agribusiness Opportunity Costs and Environmental Legal Protection: Investigating Trade-Off on Hotspot Preservation in the State of So Paulo, Brazil

Prior to deforestation, So Paulo State had 79,000 km(2) covered by Cerrado (Brazilian savanna) physiognomies, but today less than 8.5% of this biodiversity hotspot remains, mostly in private lands. The global demand for agricultural goods has imposed strong pressure on natural areas, and the economic decisions of agribusiness managers are crucial to the fate of Cerrado domain remaining areas (CDRA) in Brazil. Our aim was to investigate the effectiveness of Brazilian private protected areas policy, and to propose a feasible alternative to promote CDRA protection. This article assessed the main agribusiness opportunity costs for natural areas preservation: the land use profitability and the arable land price. The CDRA percentage and the opportunity costs were estimated for 349 municipal districts of So Paulo State through secondary spatial data and profitability values of 38 main agricultural products. We found that Brazilian private protected areas policy fails to preserve CDRA, although the values of non-compliance fines were higher than average opportunity costs. The scenario with very restrictive laws on private protected areas and historical high interest rates allowed us to conceive a feasible cross compliance proposal to improve environmental and agricultural policies.

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.

The BRAzilian Seismographic Integrated Systems (BRASIS): infrastructure and data management

In geophysics and seismology, raw data need to be processed to generate useful information that can be turned into knowledge by researchers. The number of sensors that are acquiring raw data is increasing rapidly. Without good data management systems, more time can be spent in querying and preparing datasets for analyses than in acquiring raw data. Also, a lot of good quality data acquired at great effort can be lost forever if they are not correctly stored. Local and international cooperation will probably be reduced, and a lot of data will never become scientific knowledge. For this reason, the Seismological Laboratory of the Institute of Astronomy, Geophysics and Atmospheric Sciences at the University of Sao Paulo (IAG-USP) has concentrated fully on its data management system. This report describes the efforts of the IAG-USP to set up a seismology data management system to facilitate local and international cooperation.

Regional Effects of Port Infrastructure: A Spatial CGE Application to Brazil

This article attempts to elucidate one of the mechanisms that link trade barriers, in the form of port costs, and subsequent growth and regional inequality. Prior attention has focused on inland or link costs, but port costs can be considered as a further barrier to enhancing trade liberalization and growth. In contrast to a highway link, congestion at a port may have severe impacts that are spread over space and time whereas highway link congestion may be resolved within several hours. Since a port is part of the transportation network, any congestion/disruption is likely to ripple throughout the hinterland. In this sense, it is important to model properly the role nodal components play in the context of spatial models and international trade. In this article, a spatial computable general equilibrium (CGE) model that is integrated to a transport network system is presented to simulate the impacts of increases in port efficiency in Brazil. The role of ports of entry and ports of exit are explicitly considered to grasp the holistic picture in an integrated interregional system. Measures of efficiency for different port locations are incorporated in the calibration of the model and used as the benchmark in our simulations. Three scenarios are evaluated: (1) an overall increase in port efficiency in Brazil to achieve international standards; (2) efficiency gains associated with decentralization in port management in Brazil; and (3) regionally differentiated increases in port efficiency to reach the boundary of the national efficiency frontier.

Spatial and temporal distribution of fish in Palmas bay, Ubatuba, Brazil

The aim of this study was to analyze the distribution and abundance of the fish fauna of Palmas bay on Anchieta Island in southeastern Brazil. Specimens were caught in the summer and winter of 1992, using an otter trawl at three locations in the bay. The specimens were caught in both the nighttime and daytime. Data on the water temperature and salinity were recorded for the characterization of the predominant water mass in the region, and sediment samples were taken for granulometric analysis. A total of 7 656 specimens (79 species), with a total weight of approximately 300 kg, were recorded. The most abundant species were Eucinostomus argenteus, Ctenosciaena gracilicirrhus, Haemulon steindachneri, Eucinostomus gula and Diapterus rhombeus, which together accounted for more than 73% of the sample. In general, the ecological indices showed no differences in the composition of species for the abiotic variables analyzed. The multivariate analysis showed that the variations in the distribution of the fish fauna were mainly associated with intra-annual differences in temperature and salinity, resulting from the presence of South Atlantic Central Water (SACW) in the area during the summer. The analysis also showed an association with the type of bottom and a lesser association with respect to the night/day periods.

Spatial clustering analysis of the foot-and-mouth disease outbreaks in Mato Grosso do Sul state, Brazil - 2005

In the southern region of Mato Grosso do Sul state, Brazil, a foot-and-mouth disease (FMD) epidemic started in September 2005. A total of 33 outbreaks were detected and 33,741 FMD-susceptible animals were slaughtered and destroyed. There were no reports of FMD cases in other species than bovines. Based on the data of this epidemic, it was carried out an analysis using the K-function and it was observed spatial clustering of outbreaks within a range of 25km. This observation may be related to the dynamics of foot-and-mouth disease spread and to the measures undertaken to control the disease dissemination. The control measures were effective once the disease did not spread to farms more than 47 km apart from the initial outbreaks.

A spatial approach for the epidemiology of antibiotic use and resistance in community-based studies: the emergence of urban clusters of Escherichia coli quinolone resistance in Sao Paulo, Brasil

Background: Population antimicrobial use may influence resistance emergence. Resistance is an ecological phenomenon due to potential transmissibility. We investigated spatial and temporal patterns of ciprofloxacin (CIP) population consumption related to E. coli resistance emergence and dissemination in a major Brazilian city. A total of 4,372 urinary tract infection E. coli cases, with 723 CIP resistant, were identified in 2002 from two outpatient centres. Cases were address geocoded in a digital map. Raw CIP consumption data was transformed into usage density in DDDs by CIP selling points influence zones determination. A stochastic model coupled with a Geographical Information System was applied for relating resistance and usage density and for detecting city areas of high/low resistance risk. Results: E. coli CIP resistant cluster emergence was detected and significantly related to usage density at a level of 5 to 9 CIP DDDs. There were clustered hot-spots and a significant global spatial variation in the residual resistance risk after allowing for usage density. Conclusions: There were clustered hot-spots and a significant global spatial variation in the residual resistance risk after allowing for usage density. The usage density of 5-9 CIP DDDs per 1,000 inhabitants within the same influence zone was the resistance triggering level. This level led to E. coli resistance clustering, proving that individual resistance emergence and dissemination was affected by antimicrobial population consumption.

Dispersive analysis of KL mu 3 and KLe3 scalar and vector form factors using KTeV data

Using the published KTeV samples of K(L) -> pi(+/-)e(-/+)nu and K(L) -> pi(+/-)mu(-/+)nu decays, we perform a reanalysis of the scalar and vector form factors based on the dispersive parametrization. We obtain phase-space integrals I(K)(e) = 0.15446 +/- 0.00025 and I(K)(mu) = 0.10219 +/- 0.00025. For the scalar form factor parametrization, the only free parameter is the normalized form factor value at the Callan-Treiman point (C); our best-fit results in InC = 0.1915 +/- 0.0122. We also study the sensitivity of C to different parametrizations of the vector form factor. The results for the phase-space integrals and C are then used to make tests of the standard model. Finally, we compare our results with lattice QCD calculations of F(K)/F(pi) and f(+)(0).

Gene Expression Noise in Spatial Patterning: hunchback Promoter Structure Affects Noise Amplitude and Distribution in Drosophila Segmentation

Positional information in developing embryos is specified by spatial gradients of transcriptional regulators. One of the classic systems for studying this is the activation of the hunchback (hb) gene in early fruit fly (Drosophila) segmentation by the maternally-derived gradient of the Bicoid (Bcd) protein. Gene regulation is subject to intrinsic noise which can produce variable expression. This variability must be constrained in the highly reproducible and coordinated events of development. We identify means by which noise is controlled during gene expression by characterizing the dependence of hb mRNA and protein output noise on hb promoter structure and transcriptional dynamics. We use a stochastic model of the hb promoter in which the number and strength of Bcd and Hb (self-regulatory) binding sites can be varied. Model parameters are fit to data from WT embryos, the self-regulation mutant hb(14F), and lacZ reporter constructs using different portions of the hb promoter. We have corroborated model noise predictions experimentally. The results indicate that WT (self-regulatory) Hb output noise is predominantly dependent on the transcription and translation dynamics of its own expression, rather than on Bcd fluctuations. The constructs and mutant, which lack self-regulation, indicate that the multiple Bcd binding sites in the hb promoter (and their strengths) also play a role in buffering noise. The model is robust to the variation in Bcd binding site number across a number of fly species. This study identifies particular ways in which promoter structure and regulatory dynamics reduce hb output noise. Insofar as many of these are common features of genes (e. g. multiple regulatory sites, cooperativity, self-feedback), the current results contribute to the general understanding of the reproducibility and determinacy of spatial patterning in early development.

Understanding the Influences of Spatial Patterns on N Availability Within the Brazilian Amazon Forest

Nitrogen variations at different spatial scales and integrated across functional groups were addressed for lowland tropical forests in the Brazilian Amazon as follows: (1) how does N availability vary across the region over different spatial scales (regional x landscape scale); ( 2) how are these variations in N availability integrated across plant functional groups ( legume 9 non-legume trees). Leaf N, P, and Ca concentrations as well the leaf N isotope ratios (delta(15)N) from a large set of legume and non-legume tree species were measured. Legumes had higher foliar N/Ca ratios than non-legumes, consistent with the high energetic costs in plant growth associated with higher foliar P/Ca ratios found in legumes than in non-legumes. At the regional level, foliar delta(15)N decreased with increasing rainfall. At the landscape level, N availability was higher in the forests on clayey soils on the plateau than in forests on sandier soils. The isotope as well as the non-isotope data relationships here documented, explain to a large extent the variation in delta(15)N signatures across gradients of rainfall and soil. Although at the regional level, the precipitation regime is a major determinant of differences in N availability, at the landscape level, under the same precipitation regime, soil type seems to be a major factor influencing the availability of N in the Brazilian Amazon forest.

Spatial portability of numerical models of leaf wetness duration based on empirical approaches

Leaf wetness duration (LWD) models based on empirical approaches offer practical advantages over physically based models in agricultural applications, but their spatial portability is questionable because they may be biased to the climatic conditions under which they were developed. In our study, spatial portability of three LWD models with empirical characteristics - a RH threshold model, a decision tree model with wind speed correction, and a fuzzy logic model - was evaluated using weather data collected in Brazil, Canada, Costa Rica, Italy and the USA. The fuzzy logic model was more accurate than the other models in estimating LWD measured by painted leaf wetness sensors. The fraction of correct estimates for the fuzzy logic model was greater (0.87) than for the other models (0.85-0.86) across 28 sites where painted sensors were installed, and the degree of agreement k statistic between the model and painted sensors was greater for the fuzzy logic model (0.71) than that for the other models (0.64-0.66). Values of the k statistic for the fuzzy logic model were also less variable across sites than those of the other models. When model estimates were compared with measurements from unpainted leaf wetness sensors, the fuzzy logic model had less mean absolute error (2.5 h day(-1)) than other models (2.6-2.7 h day(-1)) after the model was calibrated for the unpainted sensors. The results suggest that the fuzzy logic model has greater spatial portability than the other models evaluated and merits further validation in comparison with physical models under a wider range of climate conditions. (C) 2010 Elsevier B.V. All rights reserved.