986 resultados para Spatial database
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Extensive data used to quantify broad soil C changes (without information about causation), coupled with intensive data used for attribution of changes to specific management practices, could form the basis of an efficient national grassland soil C monitoring network. Based on variability of extensive (USDA/NRCS pedon database) and intensive field-level soil C data, we evaluated the efficacy of future sample collection to detect changes in soil C in grasslands. Potential soil C changes at a range of spatial scales related to changes in grassland management can be verified (alpha=0.1) after 5 years with collection of 34, 224, 501 samples at the county, state, or national scales, respectively. Farm-level analysis indicates that equivalent numbers of cores and distinct groups of cores (microplots) results in lowest soil C coefficients of variation for a variety of ecosystems. Our results suggest that grassland soil C changes can be precisely quantified using current technology at scales ranging from farms to the entire nation. (C) 2001 Elsevier Science Ltd. All rights reserved.
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Understanding the motion characteristics of on-site objects is desirable for the analysis of construction work zones, especially in problems related to safety and productivity studies. This article presents a methodology for rapid object identification and tracking. The proposed methodology contains algorithms for spatial modeling and image matching. A high-frame-rate range sensor was utilized for spatial data acquisition. The experimental results indicated that an occupancy grid spatial modeling algorithm could quickly build a suitable work zone model from the acquired data. The results also showed that an image matching algorithm is able to find the most similar object from a model database and from spatial models obtained from previous scans. It is then possible to use the matched information to successfully identify and track objects.
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The design and construction community has shown increasing interest in adopting building information models (BIMs). The richness of information provided by BIMs has the potential to streamline the design and construction processes by enabling enhanced communication, coordination, automation and analysis. However, there are many challenges in extracting construction-specific information out of BIMs. In most cases, construction practitioners have to manually identify the required information, which is inefficient and prone to error, particularly for complex, large-scale projects. This paper describes the process and methods we have formalized to partially automate the extraction and querying of construction-specific information from a BIM. We describe methods for analyzing a BIM to query for spatial information that is relevant for construction practitioners, and that is typically represented implicitly in a BIM. Our approach integrates ifcXML data and other spatial data to develop a richer model for construction users. We employ custom 2D topological XQuery predicates to answer a variety of spatial queries. The validation results demonstrate that this approach provides a richer representation of construction-specific information compared to existing BIM tools.
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Imagined Landscapes teams geocritical analysis with digital visualization techniques to map and interrogate films, novels, and plays in which space and place figure prominently. Drawing upon A Cultural Atlas of Australia, a database-driven interactive digital map that can be used to identify patterns of representation in Australia’s cultural landscape, the book presents an integrated perspective on the translation of space across narrative forms and pioneers new ways of seeing and understanding landscape. It offers fresh insights on cultural topography and spatial history by examining the technical and conceptual challenges of georeferencing fictional and fictionalized places in narratives. Among the items discussed are Wake in Fright, a novel by Kenneth Cook, adapted iconically to the screen and recently onto the stage; the Australian North as a mythic space; spatial and temporal narrative shifts in retellings of the story of Alexander Pearce, a convict who gained notoriety for resorting to cannibalism after escaping from a remote Tasmanian penal colony; travel narratives and road movies set in Western Australia; and the challenges and spatial politics of mapping spaces for which there are no coordinates.
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This thesis presents novel modelling applications for environmental geospatial data using remote sensing, GIS and statistical modelling techniques. The studied themes can be classified into four main themes: (i) to develop advanced geospatial databases. Paper (I) demonstrates the creation of a geospatial database for the Glanville fritillary butterfly (Melitaea cinxia) in the Åland Islands, south-western Finland; (ii) to analyse species diversity and distribution using GIS techniques. Paper (II) presents a diversity and geographical distribution analysis for Scopulini moths at a world-wide scale; (iii) to study spatiotemporal forest cover change. Paper (III) presents a study of exotic and indigenous tree cover change detection in Taita Hills Kenya using airborne imagery and GIS analysis techniques; (iv) to explore predictive modelling techniques using geospatial data. In Paper (IV) human population occurrence and abundance in the Taita Hills highlands was predicted using the generalized additive modelling (GAM) technique. Paper (V) presents techniques to enhance fire prediction and burned area estimation at a regional scale in East Caprivi Namibia. Paper (VI) compares eight state-of-the-art predictive modelling methods to improve fire prediction, burned area estimation and fire risk mapping in East Caprivi Namibia. The results in Paper (I) showed that geospatial data can be managed effectively using advanced relational database management systems. Metapopulation data for Melitaea cinxia butterfly was successfully combined with GPS-delimited habitat patch information and climatic data. Using the geospatial database, spatial analyses were successfully conducted at habitat patch level or at more coarse analysis scales. Moreover, this study showed it appears evident that at a large-scale spatially correlated weather conditions are one of the primary causes of spatially correlated changes in Melitaea cinxia population sizes. In Paper (II) spatiotemporal characteristics of Socupulini moths description, diversity and distribution were analysed at a world-wide scale and for the first time GIS techniques were used for Scopulini moth geographical distribution analysis. This study revealed that Scopulini moths have a cosmopolitan distribution. The majority of the species have been described from the low latitudes, sub-Saharan Africa being the hot spot of species diversity. However, the taxonomical effort has been uneven among biogeographical regions. Paper III showed that forest cover change can be analysed in great detail using modern airborne imagery techniques and historical aerial photographs. However, when spatiotemporal forest cover change is studied care has to be taken in co-registration and image interpretation when historical black and white aerial photography is used. In Paper (IV) human population distribution and abundance could be modelled with fairly good results using geospatial predictors and non-Gaussian predictive modelling techniques. Moreover, land cover layer is not necessary needed as a predictor because first and second-order image texture measurements derived from satellite imagery had more power to explain the variation in dwelling unit occurrence and abundance. Paper V showed that generalized linear model (GLM) is a suitable technique for fire occurrence prediction and for burned area estimation. GLM based burned area estimations were found to be more superior than the existing MODIS burned area product (MCD45A1). However, spatial autocorrelation of fires has to be taken into account when using the GLM technique for fire occurrence prediction. Paper VI showed that novel statistical predictive modelling techniques can be used to improve fire prediction, burned area estimation and fire risk mapping at a regional scale. However, some noticeable variation between different predictive modelling techniques for fire occurrence prediction and burned area estimation existed.
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Spatial Decision Support System (SDSS) assist in strategic decision-making activities considering spatial and temporal variables, which help in Regional planning. WEPA is a SDSS designed for assessment of wind potential spatially. A wind energy system transforms the kinetic energy of the wind into mechanical or electrical energy that can be harnessed for practical use. Wind energy can diversify the economies of rural communities, adding to the tax base and providing new types of income. Wind turbines can add a new source of property value in rural areas that have a hard time attracting new industry. Wind speed is extremely important parameter for assessing the amount of energy a wind turbine can convert to electricity: The energy content of the wind varies with the cube (the third power) of the average wind speed. Estimation of the wind power potential for a site is the most important requirement for selecting a site for the installation of a wind electric generator and evaluating projects in economic terms. It is based on data of the wind frequency distribution at the site, which are collected from a meteorological mast consisting of wind anemometer and a wind vane and spatial parameters (like area available for setting up wind farm, landscape, etc.). The wind resource is governed by the climatology of the region concerned and has large variability with reference to space (spatial expanse) and time (season) at any fixed location. Hence the need to conduct wind resource surveys and spatial analysis constitute vital components in programs for exploiting wind energy. SDSS for assessing wind potential of a region / location is designed with user friendly GUI’s (Graphic User Interface) using VB as front end with MS Access database (backend). Validation and pilot testing of WEPA SDSS has been done with the data collected for 45 locations in Karnataka based on primary data at selected locations and data collected from the meteorological observatories of the India Meteorological Department (IMD). Wind energy and its characteristics have been analysed for these locations to generate user-friendly reports and spatial maps. Energy Pattern Factor (EPF) and Power Densities are computed for sites with hourly wind data. With the knowledge of EPF and mean wind speed, mean power density is computed for the locations with only monthly data. Wind energy conversion systems would be most effective in these locations during May to August. The analyses show that coastal and dry arid zones in Karnataka have good wind potential, which if exploited would help local industries, coconut and areca plantations, and agriculture. Pre-monsoon availability of wind energy would help in irrigating these orchards, making wind energy a desirable alternative.
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This study describes the design and implementation of DSS for assessment of Mini, Micro and Small Schemes. The design links a set of modelling, manipulation, spatial analyses and display tools to a structured database that has the facility to store both observed and simulated data. The main hypothesis is that this tool can be used to form a core of practical methodology that will result in more resilient in less time and can be used by decision-making bodies to assess the impacts of various scenarios (e.g.: changes in land use pattern) and to review, cost and benefits of decisions to be made. It also offers means of entering, accessing and interpreting the information for the purpose of sound decision making. Thus, the overall objective of this DSS is the development of set of tools aimed at transforming data into information and aid decisions at different scales.
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Protein structure alignment is a crucial step in protein structure-function analysis. Despite the advances in protein structure alignment algorithms, some of the local conformationally similar regions are mislabeled as structurally variable regions (SVRs). These regions are not well superimposed because of differences in their spatial orientations. The Database of Structural Alignments (DoSA) addresses this gap in identification of local structural similarities obscured in global protein structural alignments by realigning SVRs using an algorithm based on protein blocks. A set of protein blocks is a structural alphabet that abstracts protein structures into 16 unique local structural motifs. DoSA provides unique information about 159 780 conformationally similar and 56 140 conformationally dissimilar SVRs in 74 705 pairwise structural alignments of homologous proteins. The information provided on conformationally similar and dissimilar SVRs can be helpful to model loop regions. It is also conceivable that conformationally similar SVRs with conserved residues could potentially contribute toward functional integrity of homologues, and hence identifying such SVRs could be helpful in understanding the structural basis of protein function.
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We present new data on the strength of oceanic lithosphere along the Ninetyeast Ridge (NER) from two independent methods: spectral analysis (Bouguer coherence) using the fan wavelet transform technique, and spatial analysis (flexure inversion) with the convolution method. The two methods provide effective elastic thickness (T-e) patterns that broadly complement each other, and correlate well with known surface structures and regional-scale features. Furthermore, our study presents a new high resolution database on the Moho configuration, which obeys flexural isostasy, and exhibit regional correlations with the T-e variations. A continuous ridge structure with a much lower T-e value than that of normal oceanic lithosphere provides strong support for the hotspot theory. The derived T-e values vary over the northern (higher T-e similar to 10-20 km), central (anomalously low T-e similar to 0-5 km), and southern (low T-e similar to 5 km) segments of the NER. The lack of correlation of the T-e value with the progressive aging of the lithosphere implies differences in thermo-mechanical setting of the crust and underlying mantle in different parts of the NER, again indicating diversity in their evolution. The anomalously low T-e and deeper Moho (similar to 22 km) estimates of the central NER (between 0.5 degrees N and 17 degrees S) are attributed to the interaction of a hotspot with the Wharton spreading ridge that caused significant thermal rejuvenation and hence weakening of the lithosphere. The higher mechanical strength values in the northern NER (north of 0.5 degrees N) may support the idea of off-ridge emplacement and a relatively large plate motion at the time of volcanism. The low T-e and deeper Moho (similar to 22 km) estimates in the southern part (south of 17 degrees S) suggest that the lithosphere was weak and therefore younger at the time of volcanism, and this supports the idea that the southern NER was emplaced on the edge of the Indian plate. (C) 2013 Elsevier B.V. All rights reserved.
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An attempt has been made to quantify the variability in the seismic activity rate across the whole of India and adjoining areas (0–45°N and 60–105°E) using earthquake database compiled from various sources. Both historical and instrumental data were compiled and the complete catalog of Indian earthquakes till 2010 has been prepared. Region-specific earthquake magnitude scaling relations correlating different magnitude scales were achieved to develop a homogenous earthquake catalog for the region in unified moment magnitude scale. The dependent events (75.3%) in the raw catalog have been removed and the effect of aftershocks on the variation of b value has been quantified. The study area was divided into 2,025 grid points (1°91°) and the spatial variation of the seismicity across the region have been analyzed considering all the events within 300 km radius from each grid point. A significant decrease in seismic b value was seen when declustered catalog was used which illustrates that a larger proportion of dependent events in the earthquake catalog are related to lower magnitude events. A list of 203,448 earth- quakes (including aftershocks and foreshocks) occurred in the region covering the period from 250 B.C. to 2010 A.D. with all available details is uploaded in the website http://www.civil.iisc.ernet.in/*sreevals/resource.htm.
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Large-scale estimates of the area of terrestrial surface waters have greatly improved over time, in particular through the development of multi-satellite methodologies, but the generally coarse spatial resolution (tens of kms) of global observations is still inadequate for many ecological applications. The goal of this study is to introduce a new, globally applicable downscaling method and to demonstrate its applicability to derive fine resolution results from coarse global inundation estimates. The downscaling procedure predicts the location of surface water cover with an inundation probability map that was generated by bagged derision trees using globally available topographic and hydrographic information from the SRTM-derived HydroSHEDS database and trained on the wetland extent of the GLC2000 global land cover map. We applied the downscaling technique to the Global Inundation Extent from Multi-Satellites (GIEMS) dataset to produce a new high-resolution inundation map at a pixel size of 15 arc-seconds, termed GIEMS-D15. GIEMS-D15 represents three states of land surface inundation extents: mean annual minimum (total area, 6.5 x 10(6) km(2)), mean annual maximum (12.1 x 10(6) km(2)), and long-term maximum (173 x 10(6) km(2)); the latter depicts the largest surface water area of any global map to date. While the accuracy of GIEMS-D15 reflects distribution errors introduced by the downscaling process as well as errors from the original satellite estimates, overall accuracy is good yet spatially variable. A comparison against regional wetland cover maps generated by independent observations shows that the results adequately represent large floodplains and wetlands. GIEMS-D15 offers a higher resolution delineation of inundated areas than previously available for the assessment of global freshwater resources and the study of large floodplain and wetland ecosystems. The technique of applying inundation probabilities also allows for coupling with coarse-scale hydro-climatological model simulations. (C) 2014 Elsevier Inc All rights reserved.
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It is often difficult to define ‘water quality’ with any degree of precision. One approach is that suggested by Battarbee (1997) and is based on the extent to which individual lakes have changed compared with their natural ‘baseline’ status. Defining the base-line status of artificial lakes and reservoirs however, is, very difficult. In ecological terms, the definition of quality must include some consideration of their functional characteristics and the extent to which these characteristics are self-sustaining. The challenge of managing lakes in a sustainable way is particularly acute in semi-arid, Mediterranean countries. Here the quality of the water is strongly influenced by the unpredictability of the rainfall as well as year-to-year variations in the seasonal averages. Wise management requires profound knowledge of how these systems function. Thus a holistic approach must be adopted and the factors influencing the seasonal dynamics of the lakes quantified over a range of spatial and temporal scales. In this article, the authors describe some of the ways in which both long-term and short-term changes in the weather have influenced the seasonal and spatial dynamics of phytoplankton in El Gergal, a water supply reservoir situated in the south of Spain. The quality of the water stored in this reservoir is typically very good but surface blooms of algae commonly appear during warm, calm periods when the water level is low. El Gergal reservoir is managed by the Empresa Municipal de Abastecimiento y Saneamiento (EMASESA) and supplies water for domestic, commercial and industrial use to an area which includes the city of Seville and twelve of its surrounding towns (ca. 1.3 million inhabitants). El Gergal is the last of two reservoirs in a chain of four situated in the Rivera de Huelva basin, a tributary of the Guadalquivir river. It was commissioned by EMASESA in 1979 and since then the company has monitored its main limnological parameters on, at least, a monthly basis and used this information to improve the management of the reservoir. As a consequence of these intensive studies the physical, chemical and biological information acquired during this period makes the El Gergal database one of the most complete in Spain. In this article the authors focus on three ‘weather-related’ effects that have had a significant impact on the composition and distribution of phytoplankton in El Gergal: (i) the changes associated with severe droughts; (ii) the spatial variations produced by short-term changes in the weather; (iii) the impact of water transfers on the seasonal dynamics of the dinoflagellate Ceratium.
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The primary objective of this project, “the Assessment of Existing Information on Atlantic Coastal Fish Habitat”, is to inform conservation planning for the Atlantic Coastal Fish Habitat Partnership (ACFHP). ACFHP is recognized as a Partnership by the National Fish Habitat Action Plan (NFHAP), whose overall mission is to protect, restore, and enhance the nation’s fish and aquatic communities through partnerships that foster fish habitat conservation. This project is a cooperative effort of NOAA/NOS Center for Coastal Monitoring and Assessment (CCMA) Biogeography Branch and ACFHP. The Assessment includes three components; 1. a representative bibliographic and assessment database, 2. a Geographical Information System (GIS) spatial framework, and 3. a summary document with description of methods, analyses of habitat assessment information, and recommendations for further work. The spatial bibliography was created by linking the bibliographic table developed in Microsoft Excel and exported to SQL Server, with the spatial framework developed in ArcGIS and exported to GoogleMaps. The bibliography is a comprehensive, searchable database of over 500 selected documents and data sources on Atlantic coastal fish species and habitats. Key information captured for each entry includes basic bibliographic data, spatial footprint (e.g. waterbody or watershed), species and habitats covered, and electronic availability. Information on habitat condition indicators, threats, and conservation recommendations are extracted from each entry and recorded in a separate linked table. The spatial framework is a functional digital map based on polygon layers of watersheds, estuarine and marine waterbodies derived from NOAA’s Coastal Assessment Framework, MMS/NOAA’s Multipurpose Marine Cadastre, and other sources, providing spatial reference for all of the documents cited in the bibliography. Together, the bibliography and assessment tables and their spatial framework provide a powerful tool to query and assess available information through a publicly available web interface. They were designed to support the development of priorities for ACFHP’s conservation efforts within a geographic area extending from Maine to Florida, and from coastal watersheds seaward to the edge of the continental shelf. The Atlantic Coastal Fish Habitat Partnership has made initial use of the Assessment of Existing Information. Though it has not yet applied the AEI in a systematic or structured manner, it expects to find further uses as the draft conservation strategic plan is refined, and as regional action plans are developed. It also provides a means to move beyond an “assessment of existing information” towards an “assessment of fish habitat”, and is being applied towards the National Fish Habitat Action Plan (NFHAP) 2010 Assessment. Beyond the scope of the current project, there may be application to broader initiatives such as Integrated Ecosystem Assessments (IEAs), Ecosystem Based Management (EBM), and Marine Spatial Planning (MSP).
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Land-use change is an important aspect of global environment change. It is, in a sense, the direct result of human activities influencing our physical environment. Supported by the dynamic serving system of national resources, including both the environment database and GIS technology, this paper analyzed the land-use change in northeastern China in the past ten years (1990 - 2000). It divides northeastern China into five land-use zones based on the dynamic degree (DD) of land-use: woodland/grassland - arable land conversion zone, dry land - paddy field conversion zone, urban expansion zone, interlocked zone of farming and pasturing, and reclamation and abandoned zone. In the past ten years, land-use change of northeastern China can be generalized as follows: increase of cropland area was obvious, paddy field and dry land increased by 74. 9 and 276. 0 thousand ha respectively; urban area expanded rapidly, area of town and rural residence increased by 76. 8 thousand ha; area of forest and grassland decreased sharply with the amount of 1399. 0 and 1521. 3 thousand ha respectively; area of water body and unused land increased by 148. 4 and 513. 9 thousand ha respectively. Besides a comprehensive analysis of the spatial patterns of land use, this paper also discusses the driving forces in each land-use dynamic zones. The study shows that some key biophysical factors affect conspicuously the conversion of different land- use types. In this paper, the relationships between land- use conversion and DEM, accnmlated temperature(>= 10 degrees C) and precipitation were analysed and represented. We conclude that the land- use changes in northeast China resulted from the change of macro social and economic factors and local physical elements. Rapid population growth and management changes, in some sense, can explain the shaping of woodland/grassland - cropland conversion zone. The conversion from dry land to paddy field in the dry land - paddy field conversion zone, apart from the physical elements change promoting the expansion of paddy field, results from two reasons: one is that the implementation of market-economy in China has given farmers the right to decide what they plant and how they plant their crops, the other factor is originated partially from the change of dietary habit with the social and economic development. The conversion from paddy field to dry land is caused primarily by the shortfall of irrigation water, which in turn is caused by poor water allocation managed by local governments. The shaping of the reclamation and abandoned zone is partially due to the lack of environment protection consciousness among pioneer settlers. The reason for the conversion from grassland to cropland is the relatively higher profits of fanning than that of pasturing in the interlocked zone of farming and pasturing. In northeastern China, the rapid expansion of built-up areas results from two factors: the first is its small number of towns; the second comes from the huge potential for expansion of existing towns and cities. It is noticeable that urban expansion in the northeastern China is characterized by gentle topographic relief and low population density. Physiognomy, transportation and economy exert great influences on the urban expansion.
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GIMMS NDVI database and geo-statistics were used to depict the spatial distribution and temporal stability of NDVI on the Mongolian Plateau. The results demonstrated that: (1) Regions of interest with high NDVI indices were distributed primarily in forested mountainous regions of the east and the north, areas with low NDVI indices were primarily distributed in the Gobi desert regions of the west and the southwest, and areas with moderate NDVI values were mainly distributed in a middle steppe strap from northwest to southeast. (2) The maximum NDVI values maintained for the past 22 years showed little variation. The average NDVI variance coefficient for the 22-year period was 15.2%. (3) NDVI distribution and vegetation cover showed spatial autocorrelations on a global scale. NDVI patterns from the vegetation cover also demonstrated anisotropy; a higher positive spatial correlation was indicated in a NW-SE direction, which suggested that vegetation cover in a NW-SE direction maintained increased integrity, and vegetation assemblage was mainly distributed in the same specific direction. (4) The NDVI spatial distribution was mainly controlled by structural factors, 88.7% of the total spatial variation was influenced by structural and 11.3% by random factors. And the global autocorrelation distance was 1178 km, and the average vegetation patch length (NW-SE) to width (NE-SW) ratio was approximately 2.4:1.0.