| 000 | 05234nam a22005655i 4500 | ||
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| 001 | 978-3-642-19733-8 | ||
| 003 | DE-He213 | ||
| 005 | 20140220083758.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 110330s2011 gw | s |||| 0|eng d | ||
| 020 |
_a9783642197338 _9978-3-642-19733-8 |
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| 024 | 7 |
_a10.1007/978-3-642-19733-8 _2doi |
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| 050 | 4 | _aTA329-348 | |
| 050 | 4 | _aTA640-643 | |
| 072 | 7 |
_aTBJ _2bicssc |
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| 072 | 7 |
_aMAT003000 _2bisacsh |
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| 082 | 0 | 4 |
_a519 _223 |
| 100 | 1 |
_aMurgante, Beniamino. _eeditor. |
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| 245 | 1 | 0 |
_aGeocomputation, Sustainability and Environmental Planning _h[electronic resource] / _cedited by Beniamino Murgante, Giuseppe Borruso, Alessandra Lapucci. |
| 264 | 1 |
_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg, _c2011. |
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| 300 |
_aVI, 274 p. _bonline resource. |
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| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_acomputer _bc _2rdamedia |
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| 338 |
_aonline resource _bcr _2rdacarrier |
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| 347 |
_atext file _bPDF _2rda |
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| 490 | 1 |
_aStudies in Computational Intelligence, _x1860-949X ; _v348 |
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| 505 | 0 | _aSustainable Development: Concepts and Methods for Its Application in Urban and Environmental Planning -- Urban Land-use Projections Supporting Adaptation Strategies to Climate Changes in the Coastal Zone -- A Multiple Criteria Heuristic Solution Method for Locating Near to Optimal Contiguous and Compact Sites in Raster Maps -- Renewable Energy Sources: The Case of Wind Farms Analysis -- Identifying Viewshed: New Approaches to Visual Impact Assessment -- Agricultural Terraced Landscapes in the Province of Trieste (Northeastern Italy) -- Estimation of Population Density of Census Sectors Using Remote Sensing Data and Spatial Regression -- Using Environmental Geostatistics for the Geochemical Characterization of Soils from the Polluted Site of National Interest of Tito (PZ – Italy) -- Evaluating the Impact of Resolution on the Predictions of an Air Quality Model over Madrid area (Spain) -- Spatial OnLine Analytical Processing of Geographic Data through the Google Earth Interface -- Nonlinear Black-Box Models for Short-Term Forecasting of Air Temperature in the Town of Palermo -- Automatic Mapping and Classification of Spatial Environmental Data -- Detecting Landforms Using Quantitative Radar Roughness Characterization and Spectral Mixing Analysis -- A framework of map comparison methods to evaluate geosimulation models from a geospatial perspective. | |
| 520 | _aThe experience developed by Ian McHarg represents the first attempt to base environmental planning on more objective methods. In particular, he supposed that the real world can be considered as a layer cake and each layer represents a sectoral analysis. This metaphor represents the fundamental of overlay mapping. At the beginning, these principles have been applied only by hand, just considering the degree of darkness, produced by layer transparency, as a negative impact. In the following years, this craftmade approach, has been adopted for data organization in Geographical Information Systems producing analyses with a high level of quality and rigour. Nowadays, great part of studies in environmental planning field have been developed using GIS. The next step relative to the simple use of geographic information in supporting environmental planning is the adoption of spatial simulation models, which can predict the evolution of phenomena. As the use of spatial information has definitely improved the quality of data sets on which basing decision-making process, the use of Geostatistics, spatial simulation and, more generally, geocomputation methods allows the possibility of basing the decision-making process on predicted future scenarios. It is very strange that a discipline such as planning which programs the territory for the future years in great part of cases is not based on simulation models. Sectoral analyses, often based on surveys, are not enough to highlight dynamics of an area. Better knowing urban and environmental changes occurred in the past, it is possible to provide better simulations to predict possible tendencies. The aim of this book is to provide an overview of the main methods and techniques adopted in the field of environmental geocomputation in order to produce a more sustainable development. | ||
| 650 | 0 | _aEngineering. | |
| 650 | 0 | _aMathematical geography. | |
| 650 | 0 | _aArtificial intelligence. | |
| 650 | 0 | _aRegional planning. | |
| 650 | 0 | _aEngineering mathematics. | |
| 650 | 0 | _aEnvironmental sciences. | |
| 650 | 1 | 4 | _aEngineering. |
| 650 | 2 | 4 | _aAppl.Mathematics/Computational Methods of Engineering. |
| 650 | 2 | 4 | _aLandscape/Regional and Urban Planning. |
| 650 | 2 | 4 | _aArtificial Intelligence (incl. Robotics). |
| 650 | 2 | 4 | _aMath. Appl. in Environmental Science. |
| 650 | 2 | 4 | _aComputer Applications in Earth Sciences. |
| 700 | 1 |
_aBorruso, Giuseppe. _eeditor. |
|
| 700 | 1 |
_aLapucci, Alessandra. _eeditor. |
|
| 710 | 2 | _aSpringerLink (Online service) | |
| 773 | 0 | _tSpringer eBooks | |
| 776 | 0 | 8 |
_iPrinted edition: _z9783642197321 |
| 830 | 0 |
_aStudies in Computational Intelligence, _x1860-949X ; _v348 |
|
| 856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/978-3-642-19733-8 |
| 912 | _aZDB-2-ENG | ||
| 999 |
_c107629 _d107629 |
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