885 resultados para Spatial R-DBMS, Miniere italiane, GIS, depositi sterili
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Acquisition made accessible thanks to a 2015-2017 grant from the Council on Libraries and Information Resources.
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Publisher varies: Industrie grafiche italiane, 1921-1922; Coop. tipografica Azzoguidi, 1923-1943.
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Projected air and ground temperatures are expected to be higher in Arctic and sub-Arcticlatitudes and with temperatures already close to the limit where permafrost can exist,resistance against degradation is low. With thawing permafrost, the landscape is modifiedwith depression in which thermokarst lakes emerge. In permafrost soils a considerableamount of soil organic carbon is stored, with the potential of altering climate even furtherif expansion and formation of new thermokarst lakes emerge, as decay releasesgreenhouse gases (C02 and CH4) to the atmosphere. Analyzing the spatial distribution andmorphometry over time of thermokarst lakes and other water bodies, is of importance inaccurately predict carbon budget and feedback mechanisms, as well as to assess futurelandscape layout and these features interaction. Different types of high-spatial resolutionaerial and satellite imageries from 1963, 1975, 2003, 2010 and 2015, were used in bothpre- and post-classification change detection analyses. Using object oriented segmentationin eCognition combined with manual adjustments, resulted in digitalized water bodies>28m2 from which direction of change and morphometric values were extracted. Thequantity of thermokarst lakes and other water bodies was in 1963 n=92, with succeedingyears as a trend decreased in numbers, until 2010-2015 when eleven water bodies wereadded in 2015 (n=74 to n=85). In 1963-2003, area of these water bodies decreased with50 651m2 (189 446-138 795m2) and continued to decrease in 2003-2015 ending at 129337m2. Limnicity decreased from 19.9% in 1963 to 14.6% in 2003 (-5.3%). In 2010 and2015 13.7-13.6%. The late increase in water bodies differs from an earlier hypothesis thatsporadic permafrost regions experience decrease in both area and quantity of thermokarstlakes and water bodies. During 1963-2015, land gain has been in dominance of the ratiobetween the two competing processes of expansion and drainage. In 1963-1975, 55/45%,followed by 90/10% in 1975-2003. After major drainage events, land loss increased to62/38% in 2010-2015. Drainage and infilling rates, calculated for 15 shorelines werevaried across both landscape and parts of shorelines, with in average 0.17/0.15/0.14m/yr.Except for 1963-1975 when rate of change in average was in opposite direction (-0.09m/yr.), likely due to evident expansion of a large thermokarst lake. Using a squaregrid, distribution of water bodies was determined, with an indistinct cluster located in NEand central parts. Especially for water bodies <250m2, which is the dominant area classthroughout 1963-2015 ranging from n=39-51. With a heterogeneous composition of bothsmall and large thermokarst lakes, and with both expansion and drainage altering thelandscape in Tavvavuoma, both positive and negative climate feedback mechanisms are inplay - given that sporadic permafrost still exist.
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Urban growth and change presents numerous challenges for planners and policy makers. Effective and appropriate strategies for managing growth and change must address issues of social, environmental and economic sustainability. Doing so in practical terms is a difficult task given the uncertainty associated with likely growth trends not to mention the uncertainty associated with how social and environmental structures will respond to such change. An optimization based approach is developed for evaluating growth and change based upon spatial restrictions and impact thresholds. The spatial optimization model is integrated with a cellular automata growth simulation process. Application results are presented and discussed with respect to possible growth scenarios in south east Queensland, Australia.
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Online geographic information systems provide the means to extract a subset of desired spatial information from a larger remote repository. Data retrieved representing real-world geographic phenomena are then manipulated to suit the specific needs of an end-user. Often this extraction requires the derivation of representations of objects specific to a particular resolution or scale from a single original stored version. Currently standard spatial data handling techniques cannot support the multi-resolution representation of such features in a database. In this paper a methodology to store and retrieve versions of spatial objects at, different resolutions with respect to scale using standard database primitives and SQL is presented. The technique involves heavy fragmentation of spatial features that allows dynamic simplification into scale-specific object representations customised to the display resolution of the end-user's device. Experimental results comparing the new approach to traditional R-Tree indexing and external object simplification reveal the former performs notably better for mobile and WWW applications where client-side resources are limited and retrieved data loads are kept relatively small.
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The paper presents a computational system based upon formal principles to run spatial models for environmental processes. The simulator is named SimuMap because it is typically used to simulate spatial processes over a mapped representation of terrain. A model is formally represented in SimuMap as a set of coupled sub-models. The paper considers the situation where spatial processes operate at different time levels, but are still integrated. An example of such a situation commonly occurs in watershed hydrology where overland flow and stream channel flow have very different flow rates but are highly related as they are subject to the same terrain runoff processes. SimuMap is able to run a network of sub-models that express different time-space derivatives for water flow processes. Sub-models may be coded generically with a map algebra programming language that uses a surface data model. To address the problem of differing time levels in simulation, the paper: (i) reviews general approaches for numerical solvers, (ii) considers the constraints that need to be enforced to use more adaptive time steps in discrete time specified simulations, and (iii) scaling transfer rates in equations that use different time bases for time-space derivatives. A multistep scheme is proposed for SimuMap. This is presented along with a description of its visual programming interface, its modelling formalisms and future plans. (C) 2003 Elsevier Ltd. All rights reserved.
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This study investigated the spatial distribution patterns of three shrimp species, Periclimenes holthuisi, P. brevicarpalis, and Thor amboinensis on the sea anemone Stichodactyla haddoni in the laboratory. Anemones were partitioned into five zones (mouth, inner tentacle, outer tentacle, upper column, and lower column), and shrimp distribution on these zones was determined. Regardless of species, significantly higher numbers of shrimps chose outer tentacles (>40%) over other zones during daytime. Such distribution might be attributed to their feeding practices as these crustaceans clipped and ate parts of the outer tentacles. Periclimenes holthuisi also showed varying temporal distribution patterns on their hosts. At night when anemones contracted their tentacles, shrimp moved in significant numbers from the outer tentacle region either to the column or off the anemones. Shrimps returned to the tentacles during daytime when anemones expanded their tentacles. Thus, spatial and temporal distribution of shrimps depend upon their feeding activities and degree of anemone expansion.
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This paper investigates how demographic (socioeconomic) and land-use (physical and environmental) data can be integrated within a decision support framework to formulate and evaluate land-use planning scenarios. A case-study approach is undertaken with land-use planning scenarios for a rapidly growing coastal area in Australia, the Shire of Hervey Bay. The town and surrounding area require careful planning of the future urban growth between competing land uses. Three potential urban growth scenarios are put forth to address this issue. Scenario A ('continued growth') is based on existing socioeconomic trends. Scenario B ('maximising rates base') is derived using optimisation modelling of land-valuation data. Scenario C ('sustainable development') is derived using a number of social, economic, and environmental factors and assigning weightings of importance to each factor using a multiple criteria analysis approach. The land-use planning scenarios are presented through the use of maps and tables within a geographical information system, which delineate future possible land-use allocations up until 2021. The planning scenarios are evaluated by using a goal-achievement matrix approach. The matrix is constructed with a number of criteria derived from key policy objectives outlined in the regional growth management framework and town planning schemes. The authors of this paper examine the final efficiency scores calculated for each of the three planning scenarios and discuss the advantages and disadvantages of the three land-use modelling approaches used to formulate the final scenarios.
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Remote sensing, as a direct adjunct to field, lithologic and structural mapping, and more recently, GIS have played an important role in the study of mineralized areas. A review on the application of remote sensing in mineral resource mapping is attempted here. It involves understanding the application of remote sensing in lithologic, structural and alteration mapping. Remote sensing becomes an important tool for locating mineral deposits, in its own right, when the primary and secondary processes of mineralization result in the formation of spectral anomalies. Reconnaissance lithologic mapping is usually the first step of mineral resource mapping. This is complimented with structural mapping, as mineral deposits usually occur along or adjacent to geologic structures, and alteration mapping, as mineral deposits are commonly associated with hydrothermal alteration of the surrounding rocks. In addition to these, understanding the use of hyperspectral remote sensing is crucial as hyperspectral data can help identify and thematically map regions of exploration interest by using the distinct absorption features of most minerals. Finally coming to the exploration stage, GIS forms the perfect tool in integrating and analyzing various georeferenced geoscience data in selecting the best sites of mineral deposits or rather good candidates for further exploration.
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In broader catchment scale investigations, there is a need to understand and ultimately exploit the spatial variation of agricultural crops for an improved economic return. In many instances, this spatial variation is temporally unstable and may be different for various crop attributes and crop species. In the Australian sugar industry, the opportunity arose to evaluate the performance of 231 farms in the Tully Mill area in far north Queensland using production information on cane yield (t/ha) and CCS ( a fresh weight measure of sucrose content in the cane) accumulated over a 12-year period. Such an arrangement of data can be expressed as a 3-way array where a farm x attribute x year matrix can be evaluated and interactions considered. Two multivariate techniques, the 3-way mixture method of clustering and the 3-mode principal component analysis, were employed to identify meaningful relationships between farms that performed similarly for both cane yield and CCS. In this context, farm has a spatial component and the aim of this analysis was to determine if systematic patterns in farm performance expressed by cane yield and CCS persisted over time. There was no spatial relationship between cane yield and CCS. However, the analysis revealed that the relationship between farms was remarkably stable from one year to the next for both attributes and there was some spatial aggregation of farm performance in parts of the mill area. This finding is important, since temporally consistent spatial variation may be exploited to improve regional production. Alternatively, the putative causes of the spatial variation may be explored to enhance the understanding of sugarcane production in the wet tropics of Australia.
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Fine-scale spatial genetic structure (SGS) in natural tree populations is largely a result of restricted pollen and seed dispersal. Understanding the link between limitations to dispersal in gene vectors and SGS is of key interest to biologists and the availability of highly variable molecular markers has facilitated fine-scale analysis of populations. However, estimation of SGS may depend strongly on the type of genetic marker and sampling strategy (of both loci and individuals). To explore sampling limits, we created a model population with simulated distributions of dominant and codominant alleles, resulting from natural regeneration with restricted gene flow. SGS estimates from subsamples (simulating collection and analysis with amplified fragment length polymorphism (AFLP) and microsatellite markers) were correlated with the 'real' estimate (from the full model population). For both marker types, sampling ranges were evident, with lower limits below which estimation was poorly correlated and upper limits above which sampling became inefficient. Lower limits (correlation of 0.9) were 100 individuals, 10 loci for microsatellites and 150 individuals, 100 loci for AFLPs. Upper limits were 200 individuals, five loci for microsatellites and 200 individuals, 100 loci for AFLPs. The limits indicated by simulation were compared with data sets from real species. Instances where sampling effort had been either insufficient or inefficient were identified. The model results should form practical boundaries for studies aiming to detect SGS. However, greater sample sizes will be required in cases where SGS is weaker than for our simulated population, for example, in species with effective pollen/seed dispersal mechanisms.
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This article explores the relationship between the nation, the city, narratives, and belonging in Serbia through an analysis of narratives of a set of 30 interviews with young Belgrade intellectuals aged 23-35. I argue that what appears to be emerging in post-Milosevic Serbia is a new articulation and a new scale of belonging. Most of my informants are mobilising their city identities, moving from a national to an urban perspective. They imaginatively defend their city identity through a discourse that, others' its newcomers, i.e. the rural residents. However, the article is critical of their articulated dichotomous rhetoric of 'Us, the City Cosmopolitans' vs. I Them, the Rural Nationalists' My overall aim is to offer an analysis of the Serbian case, where one sees that the city of Belgrade has become a microcosm and a symbolic expression for modernity, resistance, openness and democracy. However, instead of seeing urbanity as the only locus of modernity, one needs to understand that urbanity does not one-dimensionally lead to the urbanisation of the mind, implying that once you have cities, or live in a city, there is a specific urban, cosmopolitan experience.
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The El Nino-Southern Oscillation (ENSO) phenomenon significantly impacts rainfall and ensuing crop yields in many parts of the world. In Australia, El Nino events are often associated with severe drought conditions. However, El Nino events differ spatially and temporally in their manifestations and impacts, reducing the relevance of ENSO-based seasonal forecasts. In this analysis, three putative types of El Nino are identified among the 24 occurrences since the beginning of the twentieth century. The three types are based on coherent spatial patterns (footprints) found in the El Nino impact on Australian wheat yield. This bioindicator reveals aligned spatial patterns in rainfall anomalies, indicating linkage to atmospheric drivers. Analysis of the associated ocean-atmosphere dynamics identifies three types of El Nino differing in the timing of onset and location of major ocean temperature and atmospheric pressure anomalies. Potential causal mechanisms associated with these differences in anomaly patterns need to be investigated further using the increasing capabilities of general circulation models. Any improved predictability would be extremely valuable in forecasting effects of individual El Nino events on agricultural systems.
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Summarizing topological relations is fundamental to many spatial applications including spatial query optimization. In this article, we present several novel techniques to effectively construct cell density based spatial histograms for range (window) summarizations restricted to the four most important level-two topological relations: contains, contained, overlap, and disjoint. We first present a novel framework to construct a multiscale Euler histogram in 2D space with the guarantee of the exact summarization results for aligned windows in constant time. To minimize the storage space in such a multiscale Euler histogram, an approximate algorithm with the approximate ratio 19/12 is presented, while the problem is shown NP-hard generally. To conform to a limited storage space where a multiscale histogram may be allowed to have only k Euler histograms, an effective algorithm is presented to construct multiscale histograms to achieve high accuracy in approximately summarizing aligned windows. Then, we present a new approximate algorithm to query an Euler histogram that cannot guarantee the exact answers; it runs in constant time. We also investigate the problem of nonaligned windows and the problem of effectively partitioning the data space to support nonaligned window queries. Finally, we extend our techniques to 3D space. Our extensive experiments against both synthetic and real world datasets demonstrate that the approximate multiscale histogram techniques may improve the accuracy of the existing techniques by several orders of magnitude while retaining the cost efficiency, and the exact multiscale histogram technique requires only a storage space linearly proportional to the number of cells for many popular real datasets.
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Traditional vegetation mapping methods use high cost, labour-intensive aerial photography interpretation. This approach can be subjective and is limited by factors such as the extent of remnant vegetation, and the differing scale and quality of aerial photography over time. An alternative approach is proposed which integrates a data model, a statistical model and an ecological model using sophisticated Geographic Information Systems (GIS) techniques and rule-based systems to support fine-scale vegetation community modelling. This approach is based on a more realistic representation of vegetation patterns with transitional gradients from one vegetation community to another. Arbitrary, though often unrealistic, sharp boundaries can be imposed on the model by the application of statistical methods. This GIS-integrated multivariate approach is applied to the problem of vegetation mapping in the complex vegetation communities of the Innisfail Lowlands in the Wet Tropics bioregion of Northeastern Australia. The paper presents the full cycle of this vegetation modelling approach including sampling sites, variable selection, model selection, model implementation, internal model assessment, model prediction assessments, models integration of discrete vegetation community models to generate a composite pre-clearing vegetation map, independent data set model validation and model prediction's scale assessments. An accurate pre-clearing vegetation map of the Innisfail Lowlands was generated (0.83r(2)) through GIS integration of 28 separate statistical models. This modelling approach has good potential for wider application, including provision of. vital information for conservation planning and management; a scientific basis for rehabilitation of disturbed and cleared areas; a viable method for the production of adequate vegetation maps for conservation and forestry planning of poorly-studied areas. (c) 2006 Elsevier B.V. All rights reserved.