994 resultados para GIS Techniques


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Pós-graduação em Geociências e Meio Ambiente - IGCE

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Pós-graduação em Geociências e Meio Ambiente - IGCE

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Pós-graduação em Agronomia (Produção Vegetal) - FCAV

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Currently, the dam of Salto Grande is very degraded. Water quality is seriously amended, and lack of riparian vegetation, as well as the advance of feed crops and land occupation in areas that should be permanently preserved, only complicate this situation. The permanent preservation area is essential for the water sources protection, soil erosion control and consequent watercourse sedimentation. Through aerial photography, using GIS techniques, it was able to identify the outwards bounds of the dam, to demarcate the permanent preservation areas and generate maps for land use. With this data, in addition to studies and ideas of reforestation in different environments, the development of a plan for restoration of degraded areas surrounding the dam is easier to be done. This study confirmed that about 72% of land use in permanent preservation areas is not in accordance with specific laws, making necessary its recovering.

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In most brazilian cities, urban growth has occurred without adequate planning. Consequently, portions of the city were being occupied, often areas unfit for use and occupation of land, causing risks to local residents and decline of urban environmental quality. One of the most frequent problems is the riverbank occupation, causing the deforestation of the riparian vegetation. Given the above, this paper aimed to map the urban sprawl of Rio Claro/SP, as well as riparian vegetation in the vicinity of Corumbataí in the area including the urban area. For this purpose, GIS techniques were used in order to prepare the thematic map of urban expansion, as well as a map of the riparian vegetation through interpretation of aerial photographs in the environment of ARCGIS. From the maps, an analysis of “Plano Diretor” was made in order to verify if the current occupation of urban land meets the stipulations of this legal instrument

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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This study aimed to map the classes of use and occupation and their conflicts in Areas of Permanent Preservation (APPs) in the basin of Ribeirão São Pedro - Botucatu (SP) with the use of remote sensing techniques - image obtained by satellite 2011 - and the use of GIS. For this, we used the GIS techniques, and the integration of information held in the Geographic Information System (GIS) - IDRISI, coupled with the use of digital maps, published by the Brazilian Institute of Geography and Statistics - IBGE, scale 1: 50,000 and satellite images LANDSAT - 5 (2011) sensor TM (Thematic Mapper) with spatial resolution of 30 x 30 meters, provided by the National Institute for Space Research (INPE) .The Geographic Information System (GIS) was used IDRISI Selva and software, CartaLinx. This work had as legal support environmental legislation, specifically, the Federal Law 12.651 / 12. Thus, the study of the watershed becomes an important tool to understand its dynamics in relation to the use and occupation of their area and to characterize their environmental problems and taking as legal counsel to the preservation and conservation of the land to support environmental legislation.

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The misuse of land by man and is causing serious problems to the environment, resulting in ecological imbalance and depletion of natural resources, especially when it comes to areas of permanent preservation, that ecosystems are essential for balance and water conservation importance . Conflicts of land use is a major cause of silting of rivers and water bodies, causing significant losses in soil and decaying natural water resources both in quantity and in quality. Within this scenario, the planning becomes essential for the control of environmental impacts to the environment factor. This study aimed to evaluate land use conflicts in permanent preservation areas of the stream Água Fria watershed, Bofete (SP) using Geographic Information System and satellite image of LANDSAT - 5 of 2010, scale 1:50000. The results show that 51.16% of the permanent preservation areas of the watershed are conflicting, especially for pasture (88.94%) and reforestation with eucalyptus (11.06%). The GIS IDRISI Selva and Cartalinx along with GIS techniques demonstrated speed and efficiency in identifying, measuring and editing maps of land use, preservation and ongoing conflicts in areas of permanent preservation.

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The evolution of elongated body shapes in vertebrates has intrigued biologists for decades and is particularly recurrent among squamates. Several aspects might explain how the environment influences the evolution of body elongation, but climate needs to be incorporated in this scenario to evaluate how it contributes to morphological evolution. Climatic parameters include temperature and precipitation, two variables that likely influence environmental characteristics, including soil texture and substrate coverage, which may define the selective pressures acting during the evolution of morphology. Due to development of geographic information system (GIS) techniques, these variables can now be included in evolutionary biology studies and were used in the present study to test for associations between variation in body shape and climate in the tropical lizard family Gymnophthalmidae. We first investigated how the morphological traits that define body shape are correlated in these lizards and then tested for associations between a descriptor of body elongation and climate. Our analyses revealed that the evolution of body elongation in Gymnophthalmidae involved concomitant changes in different morphological traits: trunk elongation was coupled with limb shortening and a reduction in body diameter, and the gradual variation along this axis was illustrated by less-elongated morphologies exhibiting shorter trunks and longer limbs. The variation identified in Gymnophthalmidae body shape was associated with climate, with the species from more arid environments usually being more elongated. Aridity is associated with high temperatures and low precipitation, which affect additional environmental features, including the habitat structure. This feature may influence the evolution of body shape because contrasting environments likely impose distinct demands for organismal performance in several activities, such as locomotion and thermoregulation. The present study establishes a connection between morphology and a broader natural component, climate, and introduces new questions about the spatial distribution of morphological variation among squamates.

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The presented study carried out an analysis on rural landscape changes. In particular the study focuses on the understanding of driving forces acting on the rural built environment using a statistical spatial model implemented through GIS techniques. It is well known that the study of landscape changes is essential for a conscious decision making in land planning. From a bibliography review results a general lack of studies dealing with the modeling of rural built environment and hence a theoretical modelling approach for such purpose is needed. The advancement in technology and modernity in building construction and agriculture have gradually changed the rural built environment. In addition, the phenomenon of urbanization of a determined the construction of new volumes that occurred beside abandoned or derelict rural buildings. Consequently there are two types of transformation dynamics affecting mainly the rural built environment that can be observed: the conversion of rural buildings and the increasing of building numbers. It is the specific aim of the presented study to propose a methodology for the development of a spatial model that allows the identification of driving forces that acted on the behaviours of the building allocation. In fact one of the most concerning dynamic nowadays is related to an irrational expansion of buildings sprawl across landscape. The proposed methodology is composed by some conceptual steps that cover different aspects related to the development of a spatial model: the selection of a response variable that better describe the phenomenon under study, the identification of possible driving forces, the sampling methodology concerning the collection of data, the most suitable algorithm to be adopted in relation to statistical theory and method used, the calibration process and evaluation of the model. A different combination of factors in various parts of the territory generated favourable or less favourable conditions for the building allocation and the existence of buildings represents the evidence of such optimum. Conversely the absence of buildings expresses a combination of agents which is not suitable for building allocation. Presence or absence of buildings can be adopted as indicators of such driving conditions, since they represent the expression of the action of driving forces in the land suitability sorting process. The existence of correlation between site selection and hypothetical driving forces, evaluated by means of modeling techniques, provides an evidence of which driving forces are involved in the allocation dynamic and an insight on their level of influence into the process. GIS software by means of spatial analysis tools allows to associate the concept of presence and absence with point futures generating a point process. Presence or absence of buildings at some site locations represent the expression of these driving factors interaction. In case of presences, points represent locations of real existing buildings, conversely absences represent locations were buildings are not existent and so they are generated by a stochastic mechanism. Possible driving forces are selected and the existence of a causal relationship with building allocations is assessed through a spatial model. The adoption of empirical statistical models provides a mechanism for the explanatory variable analysis and for the identification of key driving variables behind the site selection process for new building allocation. The model developed by following the methodology is applied to a case study to test the validity of the methodology. In particular the study area for the testing of the methodology is represented by the New District of Imola characterized by a prevailing agricultural production vocation and were transformation dynamic intensively occurred. The development of the model involved the identification of predictive variables (related to geomorphologic, socio-economic, structural and infrastructural systems of landscape) capable of representing the driving forces responsible for landscape changes.. The calibration of the model is carried out referring to spatial data regarding the periurban and rural area of the study area within the 1975-2005 time period by means of Generalised linear model. The resulting output from the model fit is continuous grid surface where cells assume values ranged from 0 to 1 of probability of building occurrences along the rural and periurban area of the study area. Hence the response variable assesses the changes in the rural built environment occurred in such time interval and is correlated to the selected explanatory variables by means of a generalized linear model using logistic regression. Comparing the probability map obtained from the model to the actual rural building distribution in 2005, the interpretation capability of the model can be evaluated. The proposed model can be also applied to the interpretation of trends which occurred in other study areas, and also referring to different time intervals, depending on the availability of data. The use of suitable data in terms of time, information, and spatial resolution and the costs related to data acquisition, pre-processing, and survey are among the most critical aspects of model implementation. Future in-depth studies can focus on using the proposed model to predict short/medium-range future scenarios for the rural built environment distribution in the study area. In order to predict future scenarios it is necessary to assume that the driving forces do not change and that their levels of influence within the model are not far from those assessed for the time interval used for the calibration.

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Vast portions of Arctic and sub-Arctic Siberia, Alaska and the Yukon Territory are covered by ice-rich silty to sandy deposits that are containing large ice wedges, resulting from syngenetic sedimentation and freezing. Accompanied by wedge-ice growth in polygonal landscapes, the sedimentation process was driven by cold continental climatic and environmental conditions in unglaciated regions during the late Pleistocene, inducing the accumulation of the unique Yedoma deposits up to >50 meters thick. Because of fast incorporation of organic material into syngenetic permafrost during its formation, Yedoma deposits include well-preserved organic matter. Ice-rich deposits like Yedoma are especially prone to degradation triggered by climate changes or human activity. When Yedoma deposits degrade, large amounts of sequestered organic carbon as well as other nutrients are released and become part of active biogeochemical cycling. This could be of global significance for future climate warming as increased permafrost thaw is likely to lead to a positive feedback through enhanced greenhouse gas fluxes. Therefore, a detailed assessment of the current Yedoma deposit coverage and its volume is of importance to estimate its potential response to future climate changes. We synthesized the map of the coverage and thickness estimation, which will provide critical data needed for further research. In particular, this preliminary Yedoma map is a great step forward to understand the spatial heterogeneity of Yedoma deposits and its regional coverage. There will be further applications in the context of reconstructing paleo-environmental dynamics and past ecosystems like the mammoth-steppe-tundra, or ground ice distribution including future thermokarst vulnerability. Moreover, the map will be a crucial improvement of the data basis needed to refine the present-day Yedoma permafrost organic carbon inventory, which is assumed to be between 83±12 (Strauss et al., 2013, doi:10.1002/2013GL058088) and 129±30 (Walter Anthony et al., 2014, doi:10.1038/nature13560) gigatonnes (Gt) of organic carbon in perennially-frozen archives. Hence, here we synthesize data on the circum-Arctic and sub-Arctic distribution and thickness of Yedoma for compiling a preliminary circum-polar Yedoma map. For compiling this map, we used (1) maps of the previous Yedoma coverage estimates, (2) included the digitized areas from Grosse et al. (2013) as well as extracted areas of potential Yedoma distribution from additional surface geological and Quaternary geological maps (1.: 1:500,000: Q-51-V,G; P-51-A,B; P-52-A,B; Q-52-V,G; P-52-V,G; Q-51-A,B; R-51-V,G; R-52-V,G; R-52-A,B; 2.: 1:1,000,000: P-50-51; P-52-53; P-58-59; Q-42-43; Q-44-45; Q-50-51; Q-52-53; Q-54-55; Q-56-57; Q-58-59; Q-60-1; R-(40)-42; R-43-(45); R-(45)-47; R-48-(50); R-51; R-53-(55); R-(55)-57; R-58-(60); S-44-46; S-47-49; S-50-52; S-53-55; 3.: 1:2,500,000: Quaternary map of the territory of Russian Federation, 4.: Alaska Permafrost Map). The digitalization was done using GIS techniques (ArcGIS) and vectorization of raster Images (Adobe Photoshop and Illustrator). Data on Yedoma thickness are obtained from boreholes and exposures reported in the scientific literature. The map and database are still preliminary and will have to undergo a technical and scientific vetting and review process. In their current form, we included a range of attributes for Yedoma area polygons based on lithological and stratigraphical information from the original source maps as well as a confidence level for our classification of an area as Yedoma (3 stages: confirmed, likely, or uncertain). In its current version, our database includes more than 365 boreholes and exposures and more than 2000 digitized Yedoma areas. We expect that the database will continue to grow. In this preliminary stage, we estimate the Northern Hemisphere Yedoma deposit area to cover approximately 625,000 km². We estimate that 53% of the total Yedoma area today is located in the tundra zone, 47% in the taiga zone. Separated from west to east, 29% of the Yedoma area is found in North America and 71 % in North Asia. The latter include 9% in West Siberia, 11% in Central Siberia, 44% in East Siberia and 7% in Far East Russia. Adding the recent maximum Yedoma region (including all Yedoma uplands, thermokarst lakes and basins, and river valleys) of 1.4 million km² (Strauss et al., 2013, doi:10.1002/2013GL058088) and postulating that Yedoma occupied up to 80% of the adjacent formerly exposed and now flooded Beringia shelves (1.9 million km², down to 125 m below modern sea level, between 105°E - 128°W and >68°N), we assume that the Last Glacial Maximum Yedoma region likely covered more than 3 million km² of Beringia. Acknowledgements: This project is part of the Action Group "The Yedoma Region: A Synthesis of Circum-Arctic Distribution and Thickness" (funded by the International Permafrost Association (IPA) to J. Strauss) and is embedded into the Permafrost Carbon Network (working group Yedoma Carbon Stocks). We acknowledge the support by the European Research Council (Starting Grant #338335), the German Federal Ministry of Education and Research (Grant 01DM12011 and "CarboPerm" (03G0836A)), the Initiative and Networking Fund of the Helmholtz Association (#ERC-0013) and the German Federal Environment Agency (UBA, project UFOPLAN FKZ 3712 41 106).

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En el presente trabajo se estudia la producción potencial de biomasa procedente de los cultivos de centeno y triticale en las seis comarcas agrarias de la Comunidad de Madrid (CM) y la posibilidad de su aplicación a la producción de bioelectricidad en cada una de ellas. En primer lugar se realiza un estudio bibliográfico de la situación actual de la bioelectricidad. Uno de los principales datos a tener en cuenta es que en el PER 2011- 2020 se estima que el total de potencia eléctrica instalada a partir de biomasa en España en el año 2020 sea de 1.350 MW, unas dos veces y media la existente a finales de 2010. Además, se comenta el estado de la incentivación del uso de biomasa de cultivos energéticos para producción de electricidad, la cual se regula actualmente según el Real Decreto-ley 9/2013, de 12 de Julio, por el que se adoptaron medidas urgentes para garantizar la estabilidad financiera del sistema eléctrico, y se consideran los criterios de sostenibilidad en el uso de biocombustibles sólidos. Se realiza una caracterización de las seis comarcas agrarias que forman la Comunidad Autónoma de Madrid: Área Metropolitana, Campiña, Guadarrama, Lozoya- Somosierra, Sur-Occidental y Vegas, la cual consta de dos partes: una descripción de la climatología y otra de la distribución de la superficie dedicada a barbecho y cultivos herbáceos. Se hace una recopilación bibliográfica de los modelos de simulación más representativos de crecimiento de los cultivos (CERES y Cereal YES), así como de ensayos realizados con los cultivos de centeno y triticale para la producción de biomasa y de estudios efectuados mediante herramientas GIS y técnicas de análisis multicriterio para la ubicación de centrales de bioelectricidad y el estudio de la logística de la biomasa. Se propone un modelo de simulación de la productividad de biomasa de centeno y de triticale para la CM, que resulta de la combinación de un modelo de producción de grano en base a datos climatológicos y a la relación biomasa/grano media de ambos cultivos obtenida en una experiencia previa. Los modelos obtenidos responden a las siguientes ecuaciones (siendo TN = temperatura media normalizada a 9,9 ºC y PN = precipitación acumulada normalizada a 496,7 mm): - Producción biomasa centeno (t m.s./ha) = 2,785 * [1,078 * ln(TN + 2*PN) + 2,3256] - Producción biomasa triticale (t m.s./ha) = 2,595 * [2,4495 * ln(TN + 2*PN) + 2,6103] Posteriormente, aplicando los modelos desarrollados, se cuantifica el potencial de producción de biomasa de centeno y triticale en las distintas comarcas agrarias de la CM en cada uno de los escenarios establecidos, que se consideran según el uso de la superficie de barbecho de secano disponible (25%, 50%, 75% y 100%). Las producciones potenciales de biomasa, que se podrían alcanzar en la CM utilizando el 100% de la superficie de barbecho de secano, en base a los cultivos de centeno y triticale, se estimaron en 169.710,72 - 149.811,59 - 140.217,54 - 101.583,01 - 26.961,88 y 1.886,40 t anuales para las comarcas de Campiña - Vegas, Sur - Occidental - Área Metropolitana - Lozoya-Somosierra y Guadarrama, respectivamente. Se realiza un análisis multicriterio basado en la programación de compromiso para definir las comarcas agrarias con mejores características para la ubicación de centrales de bioelectricidad en base a los criterios de potencial de biomasa, infraestructura eléctrica, red de carreteras, espacios protegidos y superficie de núcleos urbanos. Al efectuar el análisis multicriterio, se obtiene la siguiente ordenación jerárquica en base a los criterios establecidos: Campiña, Sur Occidental, Vegas, Área Metropolitana, Lozoya-Somosierra y Guadarrama. Mediante la utilización de técnicas GIS se estudia la localización más conveniente de una central de bioelectricidad de 2,2 MW en cada una de las comarcas agrarias y según el uso de la superficie de barbecho de secano disponible (25%, 50%, 75% y 100%), siempre que exista potencial suficiente. Para el caso de la biomasa de centeno y de triticale en base seca se considera un PCI de 3500 kcal/kg, por lo que se necesitarán como mínimo 17.298,28 toneladas para satisfacer las necesidades de cada una de las centrales de 2,2 MW. Se analiza el potencial máximo de bioelectricidad en cada una de las comarcas agrarias en base a los cultivos de centeno y triticale como productores de biomasa. Según se considere el 25% o el 100% del barbecho de secano para producción de biomasa, la potencia máxima de bioelectricidad que se podría instalar en cada una de las comarcas agrarias variaría entre 5,4 y 21,58 MW en la comarca Campiña, entre 4,76 y 19,05 MW en la comarca Vegas, entre 4,46 y 17,83 MW en la comarca Sur Occidental, entre 3,23 y 12,92 MW en la comarca Área Metropolitana, entre 0,86 y 3,43 MW en la comarca Lozoya Somosierra y entre 0,06 y 0,24 MW en la comarca Guadarrama. La potencia total que se podría instalar en la CM a partir de la biomasa de centeno y triticale podría variar entre 18,76 y 75,06 MW según que se utilice el 25% o el 100% de las tierras de barbecho de secano para su cultivo. ABSTRACT In this work is studied the potential biomass production from rye and triticale crops in the six Madrid Community (MC) agricultural regions and the possibility of its application to the bioelectricity production in each of them. First is performed a bibliographical study of the current situation of bioelectricity. One of the main elements to be considered is that in the PER 2011-2020 is estimated that the total installed electric power from biomass in Spain in 2020 was 1.350 MW, about two and a half times as at end 2010. Also is discussed the status of enhancing the use of biomass energy crops for electricity production, which is currently regulated according to the Real Decreto-ley 9/2013, of July 12, by which urgent measures were adopted to ensure financial stability of the electrical system, and there are considered the sustainability criteria in the use of solid biofuels. A characterization of the six Madrid Community agricultural regions is carried out: Area Metropolitana, Campiña, Guadarrama, Lozoya-Somosierra, Sur-Occidental and Vegas, which consists of two parts: a description of the climatology and another about the distribution of the area under fallow and arable crops. It makes a bibliographic compilation of the most representative crop growth simulation models (CERES and Cereal YES), as well as trials carried out with rye and triticale crops for biomass production and studies conducted by GIS tools and techniques multicriteria analysis for the location of bioelectricity centrals and the study of the logistics of biomass. Is proposed a biomass productivity simulation model for rye and triticale for MC that results from the combination of grain production model based on climatological data and the average relative biomass/grain of both crops obtained in a prior experience. The models obtained correspond to the following equations (where TN = normalized average temperature and PN = normalized accumulated precipitation): - Production rye biomass (t d.m./ha) = 2.785 * [1.078 * ln (TN + 2*PN) + 2.3256] - Production triticale biomass (t d.m./ha) = 2,595 * [2.4495 * ln (TN + 2*PN) + 2.6103] Subsequently, applying the developed models, the biomass potential of the MC agricultural regions is quantified in each of the scenarios established, which are considered as the use of dry fallow area available (25%, 50%, 75 % and 100%). The potential biomass production that can be achieved within the MC using 100% of the rainfed fallow area based on rye and triticale crops, were estimated at 169.710,72 - 149.811,59 - 140.217,54 - 101.583,01 - 26.961,88 and 1.886,40 t annual for the regions of Campiña, Vegas, Sur Occidental, Area Metropolitana, Lozoya- Somosierra and Guadarrama, respectively. A multicriteria analysis is performed, based on compromise programming to define the agricultural regions with better features for the location of bioelectricity centrals, on the basis of biomass potential, electrical infrastructure, road network, protected areas and urban area criteria. Upon multicriteria analysis, is obtained the following hierarchical order based on criteria: Campiña, Sur Occidental, Vegas, Area Metropolitana, Lozoya-Somosierra and Guadarrama. Likewise, through the use of GIS techniques, the most suitable location for a 2,2 MW bioelectricity plant is studied in each of the agricultural regions and according to the use of dry fallow area available (25%, 50% , 75% and 100%), if there is sufficient potential. In the case of biomass rye and triticale dry basis is considered a PCI of 3500 kcal/kg, so it will take at least 17,298.28 t to satisfy the needs of each plant. Is analyzed the maximum bioelectricity potential on each of the agricultural regions on the basis of the rye and triticale crops as biomass producers. As deemed 25% or 100% dry fallow for biomass, the maximum bioelectricity potential varies between 5,4 and 21,58 MW in the Campiña region, between 4,76 and 19,05 MW in the Vegas region, between 4,46 and 17,83 MW in the Sur Occidental region, between 3,23 and 12,92 MW in the Area Metropolitana region, between 0,86 and 3,43 MW in the Lozoya-Somosierra region and between 0,06 and 0,24 MW in the Guadarrama region. The total power that could be installed in the CM from rye and triticale biomass could vary between 18.76 and 75.06 MW if is used the 25% or 100% of fallow land for rainfed crop.