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020 _a9783540899303
_99783540899303
024 7 _a10.1007/9783540899303
_2doi
035 _avtls000352602
039 9 _a201509030941
_bVLOAD
_c201405060308
_dVLOAD
_y201402180924
_zstaff
040 _aMX-SnUAN
_bspa
_cMX-SnUAN
_erda
050 4 _aTA329-348
100 1 _aMurgante, Beniamino.
_eeditor.
_9336018
245 1 0 _aGeocomputation and Urban Planning /
_cedited by Beniamino Murgante, Giuseppe Borruso, Alessandra Lapucci.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg,
_c2009.
300 _brecurso en línea.
336 _atexto
_btxt
_2rdacontent
337 _acomputadora
_bc
_2rdamedia
338 _arecurso en línea
_bcr
_2rdacarrier
347 _aarchivo de texto
_bPDF
_2rda
490 0 _aStudies in Computational Intelligence,
_x1860-949X ;
_v176
500 _aSpringer eBooks
505 0 _aGeocomputation and Urban Planning -- Detection of Urban Socio-economic Patterns Using Clustering Techniques -- A Tale of Two Cities: Density Analysis of CBD on Two Midsize Urban Areas in Northeastern Italy -- Identification of “Hot Spots” of Social and Housing Difficulty in Urban Areas: Scan Statistics for Housing Market and Urban Planning Policies -- The Town at the End of the Town: Integration and Segregation in Suburbia -- Planning Evacuation by Means of a Multi-modal Mesoscopic Dynamic Traffic Simulation Model -- Improving Moran’s Index to Identify Hot Spots in Traffic Safety -- Visual Impact Assessment in Urban Planning -- Urban Roughness Parameters Calculation in the City of Rome by Applying Analytical and Simplified Formulations: Comparison of Results -- An Object-Oriented Model for the Sustainable Management of Evolving Spatio-temporal Information -- GIS and LIDAR Data Analysis for the Integration of Multidimensional Indicators on Urban Morphogenesis Multi-agent Vector Based Geosimulation -- Urban Pattern Morphology Time Variation in Southern Italy by Using Landsat Imagery -- Predicting the Urban Spread Using Spatio-morphological Models -- A Multi-Agent Geosimulation Infrastructure for Planning -- A Participative Multi Agent System for Urban Sustainable Mobility.
520 _aSixteen years ago, Franklin estimated that about 80% of data contain geo-referenced information. To date, the availability of geographic data and information is growing, together with the capacity of users to operate with IT tools and instruments. Spatial data infrastructures are growing and allow a wide number of users to rely on them. This growth has not been fully coupled to an increase of knowledge to support spatial decisions. Spatial analytical techniques, geographical analysis and modelling methods are therefore required to analyse data and to facilitate the decision process at all levels. Old geographical issues can find an answer thanks to new methods and instruments, while new issues are developing, challenging researchers towards new solutions. This volume aims to contribute to the development of new techniques and methods to improve the process of knowledge acquisition. The Geocomputational expression is related to the development and the application of new theories, methods and tools in order to provide better solutions to complex geographical problems. The geocomputational analysis discussed in this volume, could be classified according to three main domains of applications; the first one related to spatial decision support system and to spatial uncertainty, the second connected to artificial intelligence, the third based on all spatial statistics techniques.
590 _aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700 1 _aBorruso, Giuseppe.
_eeditor.
_9336019
700 1 _aLapucci, Alessandra.
_eeditor.
_9336020
710 2 _aSpringerLink (Servicio en línea)
_9299170
776 0 8 _iEdición impresa:
_z9783540899297
856 4 0 _uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-3-540-89930-3
_zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
942 _c14
999 _c299210
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