1.

Record Nr.

UNINA9910438147603321

Titolo

Statistical methods for spatial planning and monitoring / / Silvestro Montrone, Paola Perchinunno, editors

Pubbl/distr/stampa

Milano, : Springer, 2012

ISBN

1-283-74096-6

88-470-2751-9

Edizione

[1st ed. 2013.]

Descrizione fisica

1 online resource (166 p.)

Collana

Contributions to statistics, , 1431-1968

Altri autori (Persone)

MontroneSilvestro

PerchinunnoPaola

Disciplina

519.5

Soggetti

Spatial analysis (Statistics)

Mathematical statistics

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references and index.

Nota di contenuto

1. Geographical Disparities in Mortality Rates: Spatial Data Mining and Bayesian Hierarchical Modeling -- 2. A Fuzzy Approach to Ward’s Method of Classification: an Application Case To the Italian University System -- 3. Geostatistics and the Role of Variogram in Time Series Analysis: a Critical Review -- 4. Geostatistics and GIS: Tools for Environmental Risk Assessment -- 5. Socio-Economic Zoning: Comparing Two Statistical Methods -- 6. A Geostatistical Approach to Measure Shrinking Cities: the Case of Taranto -- 7. Social Identity as Determinant of Real Estate Economy in Manhattan.  .

Sommario/riassunto

The book aims to investigate methods and techniques for spatial statistical analysis suitable to model spatial information in support of decision systems. Over the last few years there has been a considerable interest in these tools and in the role they can play in spatial planning and environmental modelling. One of the earliest and most famous definition of spatial planning was “a geographical expression to the economic, social, cultural and ecological policies of society”:  borrowing from this point of view, this text shows how an interdisciplinary approach is an effective way to an harmonious integration of national policies with regional and local analysis. A wide range of spatial models and techniques is, also, covered: spatial data mining, point processes



analysis, nearest neighbor statistics and cluster detection, Fuzzy Regression model and local indicators of spatial association; all of these tools provide the policy-maker with a valuable support to policy development.