818 resultados para Mapping geo-ambient


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The city of Natal-RN is constructed on dune areas with wavy relives softly waved and green areas that help to keep a pleasant climate, amongst these is distinguished field Pirangi-Potengi the dune with the areas of San Vale and Lagoinha. These environments are being substituted gradual for property and other workmanships of engineering on behalf of the urban expansion. This study the elaboration of a geoambiental mapping of Field had as objective generality Pirangi-Potengi the Dune with emphasis the San Vale and Lagoinha in Natal-RN. The done mapping had as objective specific to elaborate a vegetation map, a map of registers in cadastre of ambient problems to dunes, a map of flooding susceptibility, a map of vulnerability to the underground water contamination and a map of use and occupation of the ground. Of the carried through analysis, the area in study reveals sufficiently degraded, remaining only few green areas and dunares, as well as, the vulnerable presence of areas of vulnerability in floods and areas the contamination of the water-bearing one. The gotten results allow to affirm that this type of mapping, is of great importance for analysis and evaluation of the environment of the city

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Many weeds occur in patches but farmers frequently spray whole fields to control the weeds in these patches. Given a geo-referenced weed map, technology exists to confine spraying to these patches. Adoption of patch spraying by arable farmers has, however, been negligible partly due to the difficulty of constructing weed maps. Building on previous DEFRA and HGCA projects, this proposal aims to develop and evaluate a machine vision system to automate the weed mapping process. The project thereby addresses the principal technical stumbling block to widespread adoption of site specific weed management (SSWM). The accuracy of weed identification by machine vision based on a single field survey may be inadequate to create herbicide application maps. We therefore propose to test the hypothesis that sufficiently accurate weed maps can be constructed by integrating information from geo-referenced images captured automatically at different times of the year during normal field activities. Accuracy of identification will also be increased by utilising a priori knowledge of weeds present in fields. To prove this concept, images will be captured from arable fields on two farms and processed offline to identify and map the weeds, focussing especially on black-grass, wild oats, barren brome, couch grass and cleavers. As advocated by Lutman et al. (2002), the approach uncouples the weed mapping and treatment processes and builds on the observation that patches of these weeds are quite stable in arable fields. There are three main aspects to the project. 1) Machine vision hardware. Hardware component parts of the system are one or more cameras connected to a single board computer (Concurrent Solutions LLC) and interfaced with an accurate Global Positioning System (GPS) supplied by Patchwork Technology. The camera(s) will take separate measurements for each of the three primary colours of visible light (red, green and blue) in each pixel. The basic proof of concept can be achieved in principle using a single camera system, but in practice systems with more than one camera may need to be installed so that larger fractions of each field can be photographed. Hardware will be reviewed regularly during the project in response to feedback from other work packages and updated as required. 2) Image capture and weed identification software. The machine vision system will be attached to toolbars of farm machinery so that images can be collected during different field operations. Images will be captured at different ground speeds, in different directions and at different crop growth stages as well as in different crop backgrounds. Having captured geo-referenced images in the field, image analysis software will be developed to identify weed species by Murray State and Reading Universities with advice from The Arable Group. A wide range of pattern recognition and in particular Bayesian Networks will be used to advance the state of the art in machine vision-based weed identification and mapping. Weed identification algorithms used by others are inadequate for this project as we intend to collect and correlate images collected at different growth stages. Plants grown for this purpose by Herbiseed will be used in the first instance. In addition, our image capture and analysis system will include plant characteristics such as leaf shape, size, vein structure, colour and textural pattern, some of which are not detectable by other machine vision systems or are omitted by their algorithms. Using such a list of features observable using our machine vision system, we will determine those that can be used to distinguish weed species of interest. 3) Weed mapping. Geo-referenced maps of weeds in arable fields (Reading University and Syngenta) will be produced with advice from The Arable Group and Patchwork Technology. Natural infestations will be mapped in the fields but we will also introduce specimen plants in pots to facilitate more rigorous system evaluation and testing. Manual weed maps of the same fields will be generated by Reading University, Syngenta and Peter Lutman so that the accuracy of automated mapping can be assessed. The principal hypothesis and concept to be tested is that by combining maps from several surveys, a weed map with acceptable accuracy for endusers can be produced. If the concept is proved and can be commercialised, systems could be retrofitted at low cost onto existing farm machinery. The outputs of the weed mapping software would then link with the precision farming options already built into many commercial sprayers, allowing their use for targeted, site-specific herbicide applications. Immediate economic benefits would, therefore, arise directly from reducing herbicide costs. SSWM will also reduce the overall pesticide load on the crop and so may reduce pesticide residues in food and drinking water, and reduce adverse impacts of pesticides on non-target species and beneficials. Farmers may even choose to leave unsprayed some non-injurious, environmentally-beneficial, low density weed infestations. These benefits fit very well with the anticipated legislation emerging in the new EU Thematic Strategy for Pesticides which will encourage more targeted use of pesticides and greater uptake of Integrated Crop (Pest) Management approaches, and also with the requirements of the Water Framework Directive to reduce levels of pesticides in water bodies. The greater precision of weed management offered by SSWM is therefore a key element in preparing arable farming systems for the future, where policy makers and consumers want to minimise pesticide use and the carbon footprint of farming while maintaining food production and security. The mapping technology could also be used on organic farms to identify areas of fields needing mechanical weed control thereby reducing both carbon footprints and also damage to crops by, for example, spring tines. Objective i. To develop a prototype machine vision system for automated image capture during agricultural field operations; ii. To prove the concept that images captured by the machine vision system over a series of field operations can be processed to identify and geo-reference specific weeds in the field; iii. To generate weed maps from the geo-referenced, weed plants/patches identified in objective (ii).

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This study approaches the question of the administrative procedure of the environmental licensing of ranks of fuel resale, taking as basis a study case of the reality of the City of Natal/RN (Brazil). For in such a way, it was done a retrospect on the evolution of the system of road transport in Brazil, having started to briefly analyze the urbanization process that if after accented in the capitals of the Brazilian States the decade of 1950, relating these subjects with the growth of the sector of fuel resale. After that, it was transferred boarding of the defense of the national environment to the light of ambient principles constitutional. In the sequence, a boarding on the ambient guardianship in the Federal Constitution of 1988 was made, treating basically specifies and on the national urban politics and the national politics of the environment, with its instruments. In the sequence, it was transferred the analysis of the abilities and attributions of the National Advice of the Environment (CONAMA) and its Resolutions, for then only enter in the most important part of this work: an analysis of the environmental licensing of ranks of fuel resale, in the reality of the City of Natal/RN. Before this specific boarding, it was proceeded specifically a survey and communication from the applicable norms to such establishments (Resolutions of the CONAMA and norms of the ABNT), for after that carrying through an geo-ambient characterization of the City of Natal/RN. Finally, a reflection was made on the possibility of magnifying of the state activity, in terms of guarantees for the responsible members for the environmental policy and of administrative efficiency, through the idea of the ambient regulation. For the accomplishment of this study, it was proceeded research in diverse sources such as books, magazines, sites of the Internet, periodicals, thesis and dissertations, among others material, beyond visits the agencies that direct or indirectly act with the ambient defense and as fuel resale, such as Secretariat of Environment and Urbanism of the City of Natal (SEMURB), Institute of Economic Development and Environment of RN (IDEMA), Brazilian Institute of the Environment and the Natural resources You renewed, Executive Management of RN (IBAMA/RN), Public prosecutor's office of the Environment of Natal (Public prosecution service of the RN), National Agency of Oil (ANP) and Union of the Retailing of Derivatives of Oil of the RN, among others. To the end, satiated regulation is observed that although on the substance of the ambient licensing in ranks of fuel resale, also with federal, state and municipal norms, the municipal Public Power is very far from the fulfilment of its institutional functions, in the question environmental policy of these establishments, a time that few are the permitted ranks of resale in the city of Natal/RN

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This study investigates the degree to which gender, ethnicity, relationship to perpetrator, and geomapped socio-economic factors significantly predict the incidence of childhood sexual abuse, physical abuse and non- abuse. These variables are then linked to geographic identifiers using geographic information system (GIS) technology to develop a geo-mapping framework for child sexual and physical abuse prevention.

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Technology is present in almost every simple aspect of the people’s daily life. As an instance, let us refer to the smartphone. This device is usually equipped with a GPS modulewhich may be used as an orientation system, if it carries the right functionalities. The problem is that these applications may be complex to operate and may not be within the bounds of everybody. Therefore, the main goal here is to develop an orientation system that may help people with cognitive disabilities in their day-to-day journeys, when the caregivers are absent. On the other hand, to keep paid helpers aware of the current location of the disable people, it will be also considered a localization system. Knowing their current locations, caregiversmay engage in others activities without neglecting their prime work, and, at the same time, turning people with cognitive disabilities more independent.

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This study presents a first attempt to extend the “Multi-scale integrated analysis of societal and ecosystem metabolism (MuSIASEM)” approach to a spatial dimension using GIS techniques in the Metropolitan area of Barcelona. We use a combination of census and commercial databases along with a detailed land cover map to create a layer of Common Geographic Units that we populate with the local values of human time spent in different activities according to MuSIASEM hierarchical typology. In this way, we mapped the hours of available human time, in regards to the working hours spent in different locations, putting in evidence the gradients in spatial density between the residential location of workers (generating the work supply) and the places where the working hours are actually taking place. We found a strong three-modal pattern of clumps of areas with different combinations of values of time spent on household activities and on paid work. We also measured and mapped spatial segregation between these two activities and put forward the conjecture that this segregation increases with higher energy throughput, as the size of the functional units must be able to cope with the flow of exosomatic energy. Finally, we discuss the effectiveness of the approach by comparing our geographic representation of exosomatic throughput to the one issued from conventional methods.

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Recently, kernel-based Machine Learning methods have gained great popularity in many data analysis and data mining fields: pattern recognition, biocomputing, speech and vision, engineering, remote sensing etc. The paper describes the use of kernel methods to approach the processing of large datasets from environmental monitoring networks. Several typical problems of the environmental sciences and their solutions provided by kernel-based methods are considered: classification of categorical data (soil type classification), mapping of environmental and pollution continuous information (pollution of soil by radionuclides), mapping with auxiliary information (climatic data from Aral Sea region). The promising developments, such as automatic emergency hot spot detection and monitoring network optimization are discussed as well.

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This paper proposes the use of an autonomous assistant mobile robot in order to monitor the environmental conditions of a large indoor area and develop an ambient intelligence application. The mobile robot uses single high performance embedded sensors in order to collect and geo-reference environmental information such as ambient temperature, air velocity and orientation and gas concentration. The data collected with the assistant mobile robot is analyzed in order to detect unusual measurements or discrepancies and develop focused corrective ambient actions. This paper shows an example of the measurements performed in a research facility which have enabled the detection and location of an uncomfortable temperature profile inside an office of the research facility. The ambient intelligent application has been developed by performing some localized ambient measurements that have been analyzed in order to propose some ambient actuations to correct the uncomfortable temperature profile.

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This paper proposes the use of an autonomous assistant mobile robot in order to monitor the environmental conditions of a large indoor area and develop an ambient intelligence application. The mobile robot uses single high performance embedded sensors in order to collect and geo-reference environmental information such as ambient temperature, air velocity and orientation and gas concentration. The data collected with the assistant mobile robot is analyzed in order to detect unusual measurements or discrepancies and develop focused corrective ambient actions. This paper shows an example of the measurements performed in a research facility which have enabled the detection and location of an uncomfortable temperature profile inside an office of the research facility. The ambient intelligent application has been developed by performing some localized ambient measurements that have been analyzed in order to propose some ambient actuations to correct the uncomfortable temperature profile.

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The project investigated whether it would be possible to remove the main technical hindrance to precision application of herbicides to arable crops in the UK, namely creating geo-referenced weed maps for each field. The ultimate goal is an information system so that agronomists and farmers can plan precision weed control and create spraying maps. The project focussed on black-grass in wheat, but research was also carried out on barley and beans and on wild-oats, barren brome, rye-grass, cleavers and thistles which form stable patches in arable fields. Farmers may also make special efforts to control them. Using cameras mounted on farm machinery, the project explored the feasibility of automating the process of mapping black-grass in fields. Geo-referenced images were captured from June to December 2009, using sprayers, a tractor, combine harvesters and on foot. Cameras were mounted on the sprayer boom, on windows or on top of tractor and combine cabs and images were captured with a range of vibration levels and at speeds up to 20 km h-1. For acceptability to farmers, it was important that every image containing black-grass was classified as containing black-grass; false negatives are highly undesirable. The software algorithms recorded no false negatives in sample images analysed to date, although some black-grass heads were unclassified and there were also false positives. The density of black-grass heads per unit area estimated by machine vision increased as a linear function of the actual density with a mean detection rate of 47% of black-grass heads in sample images at T3 within a density range of 13 to 1230 heads m-2. A final part of the project was to create geo-referenced weed maps using software written in previous HGCA-funded projects and two examples show that geo-location by machine vision compares well with manually-mapped weed patches. The consortium therefore demonstrated for the first time the feasibility of using a GPS-linked computer-controlled camera system mounted on farm machinery (tractor, sprayer or combine) to geo-reference black-grass in winter wheat between black-grass head emergence and seed shedding.

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Unveiling the mechanisms of energy relaxation in biomolecules is key to our understanding of protein stability, allostery, intramolecular signaling, and long-lasting quantum coherence phenomena at ambient temperatures. Yet, the relationship between the pathways of energy transfer and the functional role of the residues involved remains largely unknown. Here, we develop a simulation method of mapping out residues that are highly efficient in relaxing an initially localized excess vibrational energy and perform site-directed mutagenesis functional assays to assess the relevance of these residues to protein function. We use the ligand binding domains of thyroid hormone receptor (TR) subtypes as a test case and find that conserved arginines, which are critical to TR transactivation function, are the most effective heat diffusers across the protein structure. These results suggest a hitherto unsuspected connection between a residue`s ability to mediate intramolecular vibrational energy redistribution and its functional relevance.

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Pós-graduação em Ciências Cartográficas - FCT

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Geochemical mapping is a valuable tool for the control of territory that can be used not only in the identification of mineral resources and geological, agricultural and forestry studies but also in the monitoring of natural resources by giving solutions to environmental and economic problems. Stream sediments are widely used in the sampling campaigns carried out by the world's governments and research groups for their characteristics of broad representativeness of rocks and soils, for ease of sampling and for the possibility to conduct very detailed sampling In this context, the environmental role of stream sediments provides a good basis for the implementation of environmental management measures, in fact the composition of river sediments is an important factor in understanding the complex dynamics that develop within catchment basins therefore they represent a critical environmental compartment: they can persistently incorporate pollutants after a process of contamination and release into the biosphere if the environmental conditions change. It is essential to determine whether the concentrations of certain elements, in particular heavy metals, can be the result of natural erosion of rocks containing high concentrations of specific elements or are generated as residues of human activities related to a certain study area. This PhD thesis aims to extract from an extensive database on stream sediments of the Romagna rivers the widest spectrum of informations. The study involved low and high order stream in the mountain and hilly area, but also the sediments of the floodplain area, where intensive agriculture is active. The geochemical signals recorded by the stream sediments will be interpreted in order to reconstruct the natural variability related to bedrock and soil contribution, the effects of the river dynamics, the anomalous sites, and with the calculation of background values be able to evaluate their level of degradation and predict the environmental risk.