Monitoramento ambiental da costa do Rio Grande do Norte com base em sensoriamento remoto e geodésia de precisão

This paper presents models of parameters of Sea Surface Layer (SSL), such as chlorophyll-a, sea surface temperature (SST), Primary Productivity (PP) and Total Suspended Matter (TSM) for the region adjacent to the continental shelf of Rio Grande do Norte (RN), Brazil. Concentrations of these parameters measured in situ were compared in time quasi-synchronous with images AQUA-MODIS between the years 2003 to 2011. Determination coefficients between samples in situ and bands reflectance sensor AQUA-MODIS were representative. From that, concentrations of SSL parameters were acquired for the continental shelf of the RN (eastern and northern) analyzing the geographic distribution of variation of these parameters between the years 2009-2012. Geographical and seasonal variations mainly influenced by global climate phenomena such as El Niño and La Niña, were found through the analysis of AQUA-MODIS images by Principal Components Analysis (PCA). Images show qualitatively the variance and availability of TSM in the regions, as well as their relationship with coastal erosion hotspots, monitored along the coast of the RN. In one of the areas identified as being of limited availability of TSM, we developed a methodology for assessment and evaluation of Digital Elevation Models (DEM) of beach surfaces (emerged and submerged sections) from the integration of topographic and bathymetric data measured in situ and accurately georeferenced compatible to studies of geomorphology and coastal dynamics of short duration. The methodology consisted of surveys with GNSS positioning operated in cinematic relative mode involved in topographic and bathymetric executed in relation to the stations of the geodetic network of the study area, which provided geodetic link to the Brazilian Geodetic System (GBS), univocal , fixed, and relatively stable over time. In this study Ponta Negra Beach, Natal / RN, was identified as a region with low variance and availability of MPS in the region off, as characterized by intense human occupation and intense coastal erosion in recent decades, which presents potential of the proposed methodology for accuracy and productivity, and the progress achieved in relation to the classical methods of surveying beach profiles

Variação espacial e sazonal de elementos maiores e traços no estuários do Rio Curimataú (RN), através de dados geoquímicos e de sensoriamento remoto

The Curimataú estuary is located in the oriental coast of Rio Grande do Norte State in Brazil. Its importance resides in the fact that this region possesses one of the last portions of preserved mangrove in the Rio Grande do Norte State. Nevertheless, it has been severely affected by many anthropogenic activities, as sugarcane monoculture and shrimp farming. Former works demonstrated that an accumulation of heavy metals is occurring in oysters in this estuary, and perhaps it could be explained by the input of metals in this ecosystem deriving from the shrimp farming. To better understanding the origin of these metals, bottom sediment samples, cores and suspended particulate matter were collected for a characterization of metal concentrations (Al, Ba, Cd, Cu, Cr, Fe, Mn, Ni, Pb, Zn) and to determine the potentially bioavailable metals. Additionally, the enrichment ratio for each element analyzed was calculated. The mineralogical composition of sediment samples and cores were obtained by X-ray diffraction. Moreover, data of orbital remote sensing were used in order to detect and quantify suspended matter by applying a logarithmic algorithm. Geochemical data of bottom sediments and cores revealed that, excepting Ba and Pb, the elements analyzed presented concentrations characteristic of an unpolluted ecosystem (Al: 0,25 - 8,76 %; Ba: 3,03 - 870 µg.g-1; Cd: < 0,25 µg.g-1; Cr: 1,72 - 82,4 µg.g-1; Cu: 0,12 -25,3 µg.g-1; Pb: 0,38 - 23,7 µg.g-1; Fe: 0,10 - 5,82 %; Mn: 15,1 - 815 µg.g-1; Ni: 0,14 - 36,1 µg.g-1; Zn: 1,37 - 113 µg.g-1). During the dry season a distribution pattern was observed, with higher metal concentrations in the margins, decreasing toward the central portion of the channel. These metal concentrations were well correlated with mineralogical compositions, with clay minerals prevailing at the margins, and quartz and feldspar in the center. However, this pattern was not observed during the wet season, probably because of the high water flux that disturbed bottom sediments. But, as observed for the dry season, a good correlation between metal concentrations and mineralogical composition was also observed for the wet season, with high metal concentrations where there were high quantities of clay minerals. Low enrichment ratios were obtained for the majority of elements analyzed, excepting for Mn, Ba and Pb. Manganese presented the higher ratios downstream for both seasons, and it can be an evidence of anthropogenic impact by shrimp farming. As barium and lead concentrations in sediment samples presented analytical problems during the total sample digestion, one cannot be sure that the ratios obtained correspond to the reality. The highest metal concentrations in particulate matter were obtained in the portion dominated by fluvial transport for all metals analyzed, excepting for copper. Barium and zinc were the only elements that presented elevated concentrations that are not common of unpolluted ecosystems (Ba: 5730 - 8355 µg.g-1; Zn: 3899 - 4348 µg.g-1). However, these high concentrations could not be related to the shrimp farming and waste waters from the town of Canguaretama, once they were obtained from the fluvial particulate matter, that is upstream from the activities above mentioned. The application of the logarithmic algorithm to the processed LANDSAT image was well succeeded, although the acquired image does not correspond exactly to the field campaigns. The IKONOS image provided very detailed views of the suspended sediment concentration at the estuary, as the mixture of distinct water flows at the confluence of Cunhaú and Curimataú rivers, with more turbid waters from Cunhaú river, that is directly affected by effluents from shrimp farming and urban waste waters deriving from the town of Canguaretama

Classificador neural híbrido para imagens obtidas por sensoriamento remoto

Remote sensing is one technology of extreme importance, allowing capture of data from the Earth's surface that are used with various purposes, including, environmental monitoring, tracking usage of natural resources, geological prospecting and monitoring of disasters. One of the main applications of remote sensing is the generation of thematic maps and subsequent survey of areas from images generated by orbital or sub-orbital sensors. Pattern classification methods are used in the implementation of computational routines to automate this activity. Artificial neural networks present themselves as viable alternatives to traditional statistical classifiers, mainly for applications whose data show high dimensionality as those from hyperspectral sensors. This work main goal is to develop a classiffier based on neural networks radial basis function and Growing Neural Gas, which presents some advantages over using individual neural networks. The main idea is to use Growing Neural Gas's incremental characteristics to determine the radial basis function network's quantity and choice of centers in order to obtain a highly effective classiffier. To demonstrate the performance of the classiffier three studies case are presented along with the results.

Monitoramento geoambiental do estuário do Rio Paraíba do Norte - PB por meio da cartografia temática digital e de produtos de sensoriamento remoto

The North Paraíba River Estuary, located in the eastern portion of the Paraíba State, Northeast Brazil, on coordinates 34º50 00 -34º57 30 S and 6º55 00 -7º7 30 W, constitutes a fluvio-marine plain formed by the North Paraíba River and its tributaries Sanhauá, Paroeira, Mandacaru, Tiriri, Tambiá, Ribeira and Guia. This estuary comprises an area of about 260 km2. Increasing human demands on the estuary area and inadequate environment managing have generated conflicts. The present work main purpose is to evaluate the geodynamic evolution of the North Paraíba River Estuary in the period from 1969 to 2001, using digital image processing techniques, thematic digital cartography and multitemporal data integration, combined to geological-geophysical field surveys. The SUDENE cartographic database, converted to digital format were, used to obtain occupation and topographic maps from 1969 and to generate a Digital Elevation Model (DEM). Digital Landsat 7 ETM+ and Spot HRVIR-PAN satellite images interpretation allowed the environmental characterization of the estuary. The most important digital processing results were achieved color composites RGB 5-4-3, 5-3-1, 5-2-NDWI and band ratio 7/4-5/3-4/2, 5/7-3/1-5/4). In addition the fusion image technique RGBI was used by the inclusion of the Spot HRVRI and Landsat 7 ETM+ panchromatic band on I layer with RGB triplets 5-4-3, 5-3-1 and 5/7-3/1-5/4. The DEM and digital images integration allowed the identification of seven geomorphological units: coastal tableland, flowing tray, tide plain, fluvial terrace, submerged dune, beach plain and beach). Both Side Scan Sonar and Echosound were used to analyse underwater surface and bedforms of the estuarine channel, sand predominance (fine to very fine) and 2D dune features 5 m wide and 0.5 m height. This investigation characterized the estuary as an environment dominated by regimen of average flow. The channel depth varies between 1 m and 11 m, being this last quota reached in the area of Porto de Cabedelo. The chanel estuary is relatively shallow, with erosion evidences mainly on its superior portion, attested by sand banks exposed during the low tide. Multitemporal digital maps from 1969 and 2001 integration were obtained through geoprocessing techniques, resulting the geodynamic evolution of the estuary based on landuse, DEM geomorphology and bathymetric maps

Aplicação de sensoriamento remoto e sistema de informação geográfica na determinação da vulnerabilidade natural e ambeintal do Município de Guamaré(RN): simulação de risco às atividades da indústria petrolífera

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Aplicação do Sensoriamento Remoto e do Sistema de Informações Geográficas na Detecção de Manchas de Óleo na Região do Pólo de Exploração de Guamaré, R.N.

Objective to establish a methodology for the oil spill monitoring on the sea surface, located at the Submerged Exploration Area of the Polo Region of Guamaré, in the State of Rio Grande do Norte, using orbital images of Synthetic Aperture Radar (SAR integrated with meteoceanographycs products. This methodology was applied in the following stages: (1) the creation of a base map of the Exploration Area; (2) the processing of NOAA/AVHRR and ERS-2 images for generation of meteoceanographycs products; (3) the processing of RADARSAT-1 images for monitoring of oil spills; (4) the integration of RADARSAT-1 images with NOAA/AVHRR and ERS-2 image products; and (5) the structuring of a data base. The Integration of RADARSAT-1 image of the Potiguar Basin of day 21.05.99 with the base map of the Exploration Area of the Polo Region of Guamaré for the identification of the probable sources of the oil spots, was used successfully in the detention of the probable spot of oil detected next to the exit to the submarine emissary in the Exploration Area of the Polo Region of Guamaré. To support the integration of RADARSAT-1 images with NOAA/AVHRR and ERS-2 image products, a methodology was developed for the classification of oil spills identified by RADARSAT-1 images. For this, the following algorithms of classification not supervised were tested: K-means, Fuzzy k-means and Isodata. These algorithms are part of the PCI Geomatics software, which was used for the filtering of RADARSAT-1 images. For validation of the results, the oil spills submitted to the unsupervised classification were compared to the results of the Semivariogram Textural Classifier (STC). The mentioned classifier was developed especially for oil spill classification purposes and requires PCI software for the whole processing of RADARSAT-1 images. After all, the results of the classifications were analyzed through Visual Analysis; Calculation of Proportionality of Largeness and Analysis Statistics. Amongst the three algorithms of classifications tested, it was noted that there were no significant alterations in relation to the spills classified with the STC, in all of the analyses taken into consideration. Therefore, considering all the procedures, it has been shown that the described methodology can be successfully applied using the unsupervised classifiers tested, resulting in a decrease of time in the identification and classification processing of oil spills, if compared with the utilization of the STC classifier

Estudo multitemporal da dinâmica espacial do estuário Potengi/RN, utilizando como base os dados de Sensoriamento Remoto.

This work was developed in the Potengi river estuary, northern coastal city of Natal, located in the State of Rio Grande do Norte. The objective was to study the dynamics of Multitemporal Space in that estuary, however, analyze how this environment has behaved during the years 1988, 1994 and 2006. The definition of that, there was the fact that during that period, which occurred in that area and more intensive space exploration to practice economic activities as well as a greater and more rapid expansion of urban area. This study was supported by the Remote Sensing, who have been shown today, as an efficient analysis of the environmental studies, through geoprocessing techniques. From the performed analysis it was found that occurred during the period of study (1988 to 2006), a huge change in the design of the estuary of Potengi river. The figures showed the area of vegetation was decreased 65.22%, the deforested area increased by 70.44% and the shrimp activity grow 452.07% and the urban area was increased in 52.65% along that period described. Considering the numbers shown there that the process of occupying space in that area requires attention, because it is an environment that represents a huge contribution to the ecological balance.

Análise da transformação do uso da terra, vegetação e impactos ambientais por meio de sensoriamento remoto e geoprocessamento

The mapping of the land use, vegetation and environmental impacts using remote sensing and geoprocessing allows detection, spatial representation and quantifying all alterations due to the human action in the nature, contributing to the monitoring and planning of those activities that cause damages to the environment. The aim of this research is analyze the transformation ocurred with the land use and vegetation in order to detect environmental impacts during the period from 1962 to 1995, considering a test area in the district of Assistência and surroundings, in the Rio Claro (SP) region. In order to archieve such aim the authors used boolean operations available in the Geographical Information System (GIS) - Idrisi. The maps were obtained through the ordinary (conventional) interpretation of aerial photos, later digitized in the software CAD Overlay and georeferenced in AutoCAD Map. It's observed that operations such as crossing digitized maps of one specific area in two differents dates, using GIS, produce overall results that might point out expansion or retraction's trends of the mapped classes, as well as quantify the intensity of the phenomena.

Mapeamento do uso da terra, vegetação e impactos ambientais por meio de sensoriamento remoto e geoprocessamento

The mapping of the land use, vegetation and environmental impacts using remote sensing ana geoprocessmg allow detection, spatial representation and quantification of the alterations caused by the human action on the nature, contributing to the monitoring and planning of those activities that may cause damages to the environment. This study apply methodologies based on digital processing of orbital images for the mapping of the land use, vegetation and anthropic activities that cause impacts in the environment. It was considered a test area in the district of Assistência and surroundings, in Rio Claro (SP) region. The methodology proposed was checked through the crossing of maps in the software GIS - Idrisi. These maps either obtained with conventional interpretation of aerial photos of 1995, digitized in the software CAD Overlay and geo-referenced in the AutoCAD Map, or with the application of digital classification systems on SPOT-XS and PAN orbital images of 1995, followed by field observations. The crossing of conventional and digital maps of a same area with the CIS allows to verify the overall results obtained through the computational handling of orbital images. With the use of digital processing techniques, specially multiespectral classification, it is possible to detect automatically and visually the impacts related to the mineral extraction, as well as to survey the land use, vegetation and environmental impacts.

Autonomous mobile robots designing for the medical trash collector task

This paper describes the UNESP robotic team in the medical trash collector task, proposed on the 5 rd IEEE Latin American Robots Competition in the LEGO category. We present our understanding of the task and discuss the proposed solution, focusing on the mechanical and computational issues of the robots. The mechanics is based on rigid body capability of transforming rotational into curvilinear movement. With respect to the computational control, the system is modeled as a reactive system with sequential transition of behaviors. A state-machine is proposed to allow this transition, and the synchronization of robotic states is guaranteed by the communication system. The proposed approach has shown itself capable of dealing with the high difficulty degree of this cooperative task. ©2006 IEEE.

Conception of wheeled mobile robots with reconfigurable control using integrate prototyping

With the fast innovation of the hardware and software technologies using rapid prototyping devices, with application in the robotics and automation, more and more it becomes necessary the development of applications based on methodologies that facilitate future modifications, updates and enhancements in the original projected system. This paper presents a conception of mobile robots using rapid prototyping, distributing the several control actions in growing levels of complexity and using resources of reconfigurable computing proposal oriented to embed systems implementation. Software and the hardware are structuralized in independents blocks, with connection through common bus. The study and applications of new structures control that permits good performance in relation to the parameter variations. This kind of controller can be tested on different platform representing the wheeled mobile robots using reprogrammable logic components (FPGA). © 2006 IEEE.

A framework for learning in humanoid simulated robots

One of the most important characteristics of intelligent activity is the ability to change behaviour according to many forms of feedback. Through learning an agent can interact with its environment to improve its performance over time. However, most of the techniques known that involves learning are time expensive, i.e., once the agent is supposed to learn over time by experimentation, the task has to be executed many times. Hence, high fidelity simulators can save a lot of time. In this context, this paper describes the framework designed to allow a team of real RoboNova-I humanoids robots to be simulated under USARSim environment. Details about the complete process of modeling and programming the robot are given, as well as the learning methodology proposed to improve robot's performance. Due to the use of a high fidelity model, the learning algorithms can be widely explored in simulation before adapted to real robots. © 2008 Springer-Verlag Berlin Heidelberg.

Virtual simulator for mobile robots navigation systems

This paper presents the virtual environment implementation for project simulation and conception of supervision and control systems for mobile robots, that are capable to operate and adapting in different environments and conditions. This virtual system has as purpose to facilitate the development of embedded architecture systems, emphasizing the implementation of tools that allow the simulation of the kinematic conditions, dynamic and control, with real time monitoring of all important system points. For this, an open control architecture is proposal, integrating the two main techniques of robotic control implementation in the hardware level: systems microprocessors and reconfigurable hardware devices. The implemented simulator system is composed of a trajectory generating module, a kinematic and dynamic simulator module and of a analysis module of results and errors. All the kinematic and dynamic results shown during the simulation can be evaluated and visualized in graphs and tables formats, in the results analysis module, allowing an improvement in the system, minimizing the errors with the necessary adjustments optimization. For controller implementation in the embedded system, it uses the rapid prototyping, that is the technology that allows, in set with the virtual simulation environment, the development of a controller project for mobile robots. The validation and tests had been accomplish with nonholonomics mobile robots models with diferencial transmission. © 2008 IEEE.

Environment mapping for mobile robots navigation using hierarchical neural network and omnivision

Autonomous robots must be able to learn and maintain models of their environments. In this context, the present work considers techniques for the classification and extraction of features from images in joined with artificial neural networks in order to use them in the system of mapping and localization of the mobile robot of Laboratory of Automation and Evolutive Computer (LACE). To do this, the robot uses a sensorial system composed for ultrasound sensors and a catadioptric vision system formed by a camera and a conical mirror. The mapping system is composed by three modules. Two of them will be presented in this paper: the classifier and the characterizer module. The first module uses a hierarchical neural network to do the classification; the second uses techiniques of extraction of attributes of images and recognition of invariant patterns extracted from the places images set. The neural network of the classifier module is structured in two layers, reason and intuition, and is trained to classify each place explored for the robot amongst four predefine classes. The final result of the exploration is the construction of a topological map of the explored environment. Results gotten through the simulation of the both modules of the mapping system will be presented in this paper. © 2008 IEEE.