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dc.contributor.authorIndarto
dc.date.accessioned2012-05-01T04:07:00Z
dc.date.available2012-05-01T04:07:00Z
dc.date.issued2011-12
dc.identifier.citationAnna, A. N., Suharjo, Cholil, M. (2011). Analisis Flktuasi Hjan dan Morfologi Sungai terhadap Konsentrasi Banjir daerah Surakarta. Forum Geografi. Vol. 25, No. 1, Pp. 41-52. Cressie, N. (1993). Statistics for Spatial Data, Revised Edition, Wiley: New York. De Smith, M.J., Goodchild, M.F., and Longley, P.A. (2007). Geospatial Analysis. A Comprehensive Guide to principles, Techniques and Software Tools. Matador, Leiceister, UK. www.spatialanalysisonline.com Johnston, K. Ver Hoef,J.M., Krivoruchko, K., and Lucas, N. (2001). Using ArcGIS Geostatistical Analyst. GIS by ESRI. Lowe, J.W. (2008). Emerging Tools and Concepts of Exploratory Spatial Data Analysis. http:// www.giswebsite.com/pubs/200307/nr200307_p1.html [10 Mei 2011] Robertson, G.P. (2008). GS+: Geostatistics for the Environmental Sciences. Gamma Design Software, Plainwell, Michigan USA. https://geoda.uiuc.edu http://www.giswebsite.com/pubs/200307/nr200307_p1.html http://www.satscan.org http://regal.sdsu.edu/index.php/main/STARen_US
dc.identifier.issn0852-0682
dc.identifier.urihttp://hdl.handle.net/11617/1274
dc.description.abstractThis article expose the spatial variability of monthly-rainfall (MR) in East Java region. Monthly rainfall data were collected from 943 pluviometres spread around the regions. Spatial statistics analysed by means of ESDA (Exploratory Spatial Data Analysis) techniques available on Geostatistical Analyst extention of ArcGIS (9.3). Statistical tools exploited to analise the data include: (1) Histogram, (2) Voronoi Map, and (3) QQ-Plot. The result show that histogram and QQ-Plot of Monthly Rainfall data are leptocurtosis. Statistical value obtained from the analysis are: minimum = 54 mm/month, average = 155,5 mm/month, maximum = 386 mm/month, and median = 150 mm/month. Other statistical value summarised are: standard deviation = 44,2 ; skewness = 0,95; dan curtosis = 5,09. Finally, monthly rainfall-maps are produced by interpolating the data using Inverse Distance Weighed (IDW) interpolation method. The research demonstrate the capability and benefit of those statistical tool to describe detailed spatial variability of rainfall.en_US
dc.publisherlppmumsen_US
dc.subjectspatial variabilityen_US
dc.subjectMonthly Rainfallen_US
dc.subjectESDAen_US
dc.subjectEast Javaen_US
dc.titleAPLIKASI ESDA UNTUK STUDI VARIABILITAS SPASIAL HUJAN BULANAN DI JAWA TIMURen_US
dc.title.alternativeApplication of Exploratory Spatial Data Analysis to Study The Spatial Variability of Monthly-Rainfall in East Java Regionen_US
dc.typeArticleen_US


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