Características ambientais e a ocorrência de leishmaniose visceral em Teresina, Piauí: uma aplicação utilizando sensoriamento remoto

Nas Américas, a leishmaniose visceral (LV) experimenta um processo de urbanização e o cão doméstico é considerado o principal reservatório da doença neste cenário, embora seu papel no ciclo de transmissão não esteja totalmente explicado. Este estudo teve como objetivo investigar, por meio da análise de dados espaciais e imagens de sensoriamento remoto, a relação de fatores ambientais com a ocorrência de infecção canina por Leishmania chagasi e sua correlação espacial com a doença humana na cidade de Teresina (Piauí - Brasil), onde foi relatada a primeira epidemia urbana de LV no Brasil. Os resultados são apresentados na forma de dois manuscritos, nos quais são utilizados dados georreferenciados obtidos por meio de um inquérito sorológico canino realizado durante o ano de 2011, em diferentes bairros com transmissão moderada ou intensa. No primeiro, a regressão logística multinível foi utilizada para correlacionar a prevalência da infecção canina com variáveis ambientais de quadrículas de 900m2 (30mx30m) onde os domicílios estavam localizados, ajustando para as características individuais dos cães (sexo, idade e raça) e da residência. Participaram desta análise 717 cães distribuídos em 494 domicílios e 396 quadrículas. Um percentual >16,5% da área da quadrícula coberta por pavimentação clara (ruas de terra ou asfalto antigo) foi a única variável ambiental associada com a infecção canina por L. chagasi (Odds ratio [OR] = 2,00, intervalo de 95% de confiança [IC95%]: 1,22 - 3,26). Estas áreas provavelmente correspondem àquelas mais pobres e com pior infraestrutura urbana, sugerindo a ocorrência de um padrão de transmissão intra-urbano similar aos padrões rurais e peri-urbanos da LV. No segundo manuscrito, a partir da análise hierárquica do vizinho mais próximo foi verificada a presença de sete clusters de maior concentração de cães soropositivos em relação aos soro negativos em áreas menos urbanizadas e com vegetação pouco densa. Participaram desta análise 322 cães distribuídos em cinco bairros. A relação espacial entre os caninos soropositivos e os casos humanos foi investigada através do método da distância média entre os pontos e analisada por meio do teste t. Foi encontrada uma maior proximidade de casos humanos em relação a cães soropositivos quando comparada à distância em relação aos soro negativos, sugerindo a existência de uma relação espacial entre a LV humana e a soropositividade canina. Os resultados contribuem para uma maior compreensão sobre a dinâmica da doença em meio urbano além de fornecer informações úteis para a prevenção e controle da LV em seres humanos.

Satellite passive microwave observations of the upper Colorado River snowpack

Seasonal snow cover in the mountains of the Upper Colorado River Basin is a major source of water for a large portion of the southwestern United States. The extent and amount of this snowpack not only reflects changes in weather patterns and climate but also influences the general circulation through modification of the energy exchange between land and atmosphere. ... Satellite observations and remote sensing techniques can enhance the standard snowpack observations to provide the temporal and spatial measurements required for understanding the role of snow in the surface energy balance and improving the management of water resources.

Is there a preferred classifier for operational thematic mapping?

The importance of properly exploiting a classifier's inherent geometric characteristics when developing a classification methodology is emphasized as a prerequisite to achieving near optimal performance when carrying out thematic mapping. When used properly, it is argued that the long-standing maximum likelihood approach and the more recent support vector machine can perform comparably. Both contain the flexibility to segment the spectral domain in such a manner as to match inherent class separations in the data, as do most reasonable classifiers. The choice of which classifier to use in practice is determined largely by preference and related considerations, such as ease of training, multiclass capabilities, and classification cost. © 1980-2012 IEEE.

区域水土流失研究综述

以区域水土流失为主题 ,分析并阐述了该领域的研究现状 ,指出了当前存在的主要问题 ,并对研究的今后发展方向进行了展望。

A new wind vector algorithm for C-band SAR

Ocean wind speed and wind direction are estimated simultaneously using the normalized radar cross sections or' corresponding to two neighboring (25-km) blocks, within a given synthetic aperture radar (SAR) image, having slightly different incidence angles. This method is motivated by the methodology used for scatterometer data. The wind direction ambiguity is removed by using the direction closest to that given by a buoy or some other source of information. We demonstrate this method with 11 EN-VISAT Advanced SAR sensor images of the Gulf of Mexico and coastal waters of the North Atlantic. Estimated wind vectors are compared with wind measurements from buoys and scatterometer data. We show that this method can surpass other methods in some cases, even those with insufficient visible wind-induced streaks in the SAR images, to extract wind vectors.

A new empirical model for retrieving sea surface salinity in L band

Sea surface salinity is a key physical parameter in ocean science. It is important in the ocean remote sensing to retrieve sea surface salinity by the microwave probe technology. Based on the in situ measurement data and remote sensing data of the Yellow Sea, we have built a new empirical model in this paper, which can be used to retrieve sea surface salinity of the Yellow Sea by means of the brightness temperature of the sea water at L-band. In this model, the influence of the roughness of the sea surface is considered, and the retrieved result is in good agreement with the in situ measurement data, where the mean absolute error of the retrieved sea surface salinity is about 0.288 psu. This result shows that our model has greater retrieval precision compared with similar models.

Wind-vector estimation for RADARSAT-1 SAR images: Validation of wind-direction estimates based upon geometry diversity

In this letter, a new wind-vector algorithm is presented that uses radar backscatter sigma(0) measurements at two adjacent subscenes of RADARSAT-1 synthetic aperture radar (SAR) images, with each subscene having slightly different geometry. Resultant wind vectors are validated using in situ buoy measurements and compared with wind vectors determined from a hybrid wind-retrieval model using wind directions determined by spectral analysis of wind-induced image streaks and observed by colocated QuikSCAT measurements. The hybrid wind-retrieval model consists of CMOD-IFR2 [applicable to C-band vertical-vertical (W) polarization] and a C-band copolarization ratio according to Kirchhoff scattering. The new algorithm displays improved skill in wind-vector estimation for RADARSAT-1 SAR data when compared to conventional wind-retrieval methodology. In addition, unlike conventional methods, the present method is applicable to RADARSAT-1 images both with and without visible streaks. However, this method requires ancillary data such as buoy measurements to resolve the ambiguity in retrieved wind direction.

地理信息系统支持下的滑坡灾害空间分析预测-以云南小江流域为例

As a typical geological and environmental hazard, landslide has been causing more and more property and life losses. However, to predict its accurate occurring time is very difficult or even impossible due to landslide's complex nature. It has been realized that it is not a good solution to spend a lot of money to treat with and prevent landslide. The research trend is to study landslide's spatial distribution and predict its potential hazard zone under certain region and certain conditions. GIS(Geographical Information System) is a power tools for data management, spatial analysis based on reasonable spatial models and visualization. It is new and potential study field to do landslide hazard analysis and prediction based on GIS. This paper systematically studies the theory and methods for GIS based landslide hazard analysis. On the basis of project "Mountainous hazard study-landslide and debris flows" supported by Chinese Academy of Sciences and the former study foundation, this paper carries out model research, application, verification and model result analysis. The occurrence of landslide has its triggering factors. Landslide has its special landform and topographical feature which can be identify from field work and remote sensing image (aerial photo). Historical record of landslide is the key to predict the future behaviors of landslide. These are bases for landslide spatial data base construction. Based on the plenty of literatures reviews, the concept framework of model integration and unit combinations is formed. Two types of model, CF multiple regression model and landslide stability and hydrological distribution coupled model are bought forward. CF multiple regression model comes form statistics and possibility theory based on data. Data itself contains the uncertainty and random nature of landslide hazard, so it can be seen as a good method to study and understand landslide's complex feature and mechanics. CF multiple regression model integrates CF (landslide Certainty Factor) and multiple regression prediction model. CF can easily treat with the problems of data quantifying and combination of heteroecious data types. The combination of CF can assist to determine key landslide triggering factors which are then inputted into multiple regression model. CF regression model can provide better prediction results than traditional model. The process of landslide can be described and modeled by suitable physical and mechanical model. Landslide stability and hydrological distribution coupled model is such a physical deterministic model that can be easily used for landslide hazard analysis and prediction. It couples the general limit equilibrium method and hydrological distribution model based on DEM, and can be used as a effective approach to predict the occurrence of landslide under different precipitation conditions as well as landslide mechanics research. It can not only explain pre-existed landslides, but also predict the potential hazard region with environmental conditions changes. Finally, this paper carries out landslide hazard analysis and prediction in Yunnan Xiaojiang watershed, including landslide hazard sensitivity analysis and regression prediction model based on selected key factors, determining the relationship between landslide occurrence possibility and triggering factors. The result of landslide hazard analysis and prediction by coupled model is discussed in details. On the basis of model verification and validation, the modeling results are showing high accuracy and good applying potential in landslide research.

Ecohydrodynamics of cold-water coral reefs: A case study of the Mingulay Reef complex (western Scotland)

Ecohydrodynamics investigates the hydrodynamic constraints on ecosystems across different temporal and spatial scales. Ecohydrodynamics play a pivotal role in the structure and functioning of marine ecosystems, however the lack of integrated complex flow models for deep-water ecosystems beyond the coastal zone prevents further synthesis in these settings. We present a hydrodynamic model for one of Earth's most biologically diverse deep-water ecosystems, cold-water coral reefs. The Mingulay Reef Complex (western Scotland) is an inshore seascape of cold-water coral reefs formed by the scleractinian coral Lophelia pertusa. We applied single-image edge detection and composite front maps using satellite remote sensing, to detect oceanographic fronts and peaks of chlorophyll a values that likely affect food supply to corals and other suspension-feeding fauna. We also present a high resolution 3D ocean model to incorporate salient aspects of the regional and local oceanography. Model validation using in situ current speed, direction and sea elevation data confirmed the model's realistic representation of spatial and temporal aspects of circulation at the reef complex including a tidally driven current regime, eddies, and downwelling phenomena. This novel combination of 3D hydrodynamic modelling and remote sensing in deep-water ecosystems improves our understanding of the temporal and spatial scales of ecological processes occurring in marine systems. The modelled information has been integrated into a 3D GIS, providing a user interface for visualization and interrogation of results that allows wider ecological application of the model and that can provide valuable input for marine biodiversity and conservation applications.

Geotechnical failure risk reviewed

Slope instabilities – commonly triggered by rainfall – pose a geotechnical risk causing disruption to transport routes and incur significant financial resources. This article details laboratory, ground and remote sensing investigations carried out by Queen’s University Belfast and Transport Northern Ireland (TNI) to characterise and monitor slope instability on two higher risk infrastructure slopes in Northern Ireland. The research is used to update a noninvasive risk assessment model of slopes across the country’s road network to direct resources for future investigation.

Pollen Sources

This chapter reviews what is known about abundance and distribution of the 12 most important aeroallergenic pollens in Europe: Ambrosia, Alnus, Artemisia, Betula, Chenopodiaceae, Corylus, Cupressaceae/Taxaceae, Olea, Platanus, Poaceae, Quercus and Urtica/Parietaria. Abundance is based on 10 years of pollen records from 521 stations of the European Aeroallergen Network that were interpolated into 12 distribution maps covering most of Europe. The chapter compares the distribution maps with other types of distribution maps that are available for selected tree species and discuss two methods for making harmonized pollen source inventories: “bottom-up” and “top-down”. Both methods have advantages and disadvantages, and both need to be explored and further developed. Remote sensing has shown to be a valuable method to improve the inventories, especially the use of satellites. The full potential as well as limitations of remote sensing in relation to pollen sources remains to be explored. The review suggests that the most probable way of obtaining inventories of all 12 pollen species is to use top-down methods that use an ecosystem-based approach that for each particular species connects ecological preference, pollen counts and remote sensing.

FPGA-based architecture for hyperspectral unmixing

This paper proposes an FPGA-based architecture for onboard hyperspectral unmixing. This method based on the Vertex Component Analysis (VCA) has several advantages, namely it is unsupervised, fully automatic, and it works without dimensionality reduction (DR) pre-processing step. The architecture has been designed for a low cost Xilinx Zynq board with a Zynq-7020 SoC FPGA based on the Artix-7 FPGA programmable logic and tested using real hyperspectral datasets. Experimental results indicate that the proposed implementation can achieve real-time processing, while maintaining the methods accuracy, which indicate the potential of the proposed platform to implement high-performance, low cost embedded systems.

A indústria de defesa na cooperação Brasil-Portugal

The global dynamics of alliances are strongly determined by the level of cooperation among states. This cooperation can be embodied in various aspects, but the level of defense and security cooperation becomes usually more doctrinal and lasting. By the nature of sovereignty that instills in the bilateral relationship, cooperation at defense and security level can leverages other forms of cooperation. The circumstances and relational balance between Brazil and Portugal seem to evolve towards distancing opportunities, despite they are culturally and institutionally untainted. The economic dynamics, the strategic projection in global sustainability terms, the scale and ambition of Brazilian regional leadership, contrasts with the actual context of Portugal, distancing himself both on the stage where they operate. On the other hand, the historical and cultural roots, the language, the affinity of the peoples of CPLP and some opportunities for economic niches, trend to attract both countries. The condition of Portugal in NATO and Europe, coupled with the ability to export technical and human resources to value-added for Brazil, seems also to become approaching factors. On the balance of these dynamics, there is a set of exogenous factors (economic, external global relations matrix, regional stability, among others), which are not always controlled by any of both countries. These factors call for strong capacity for foresight analysis and decision making, with the inherent risk. There is cooperation vectors that are not apparently penalized by geographic distance, or by the difference of realities. Among these vectors we shall highlight synergies in technological niches, highly tradable goods and, mostly, using the domain of dual technologies. The thirteen niches herein identified are: Monitoring, Navigation, Command and Control, Electronics, Optoelectronics, Communication and remote sensing, Information Technologies, Flight Simulation, Specialized Training, Fiber Optic Sensors, Materials Engineering, Nanotechnology and Communications. Cumulating with identified opportunities in traditional relational framework, both countries are growing (in geography and economic terms) into the Atlantic, making it a central element in the bilateral approach. By being at the same time a growing stage of disputes and which stability tends to be threatened, it will be done an analysis of these synergistic vectors, superimposed on the impact on Atlantic securitization process.

Urban image classification with semisupervised multiscale cluster kernels

This paper presents a semisupervised support vector machine (SVM) that integrates the information of both labeled and unlabeled pixels efficiently. Method's performance is illustrated in the relevant problem of very high resolution image classification of urban areas. The SVM is trained with the linear combination of two kernels: a base kernel working only with labeled examples is deformed by a likelihood kernel encoding similarities between labeled and unlabeled examples. Results obtained on very high resolution (VHR) multispectral and hyperspectral images show the relevance of the method in the context of urban image classification. Also, its simplicity and the few parameters involved make the method versatile and workable by unexperienced users.