ANALISIS VARIABILITAS SPASIAL HUJAN BULANAN DAN TAHUNAN MENGGUNAKAN HISTOGRAM, VORONOI, DAN METODE INTERPOLASI

Analisa variabilitas spasial digunakan untuk mempelajari variablitas hujan yang diterima pada luasan tertentu. Analisis tersebut juga dapat digunakan untuk menentukan kalender tanam, mitigasi banjir, kekeringan, dan potensi bencana hidro-meteorologi terkait. Penelitian ini bertujuan menganalisis variabilitas spasial hujan bulanan dan tahunan di wilayah Kabupaten Jombang, Kediri, dan Nganjuk. Data diperoleh dari 137 stasiun hujan dengan panjang rekaman data dari tahun 1990 sampai dengan 2016. Tahap penelitian mencakup: (1) pengolahan data, (2) Exploratory Spatial Data Analysis (ESDA) menggunakan tool histogram, Voronoi-map dan Normal QQ-plot, (3) interpolasi, dan 4) analisis regresi-korelasi. Hasil analisis menunjukkan bahwa data hujan yang digunakan tidak terdistribusi normal. Nilai standar deviasi 126,9 mm untuk hujan bulanan dan 629,1 mm untuk hujan tahunan. Peta tematik menunjukkan bahwa sebagian besar wilayah penelitian menerima hujan bulanan maksimum 621 – 760 mm/bulan, dan mengalami hujan tahunan maksimum 2.178 – 3.202 mm/tahun. Analisis korelasi regresi menunjukkan adanya hubungan yang kuat antara ketinggian tempat dengan besarnya hujan yang diterima.

Evaluation of spatial differentiation in the Pilsen region from a socioeconomic perspective

The main objective of this article is to evaluate spatial differentiation in the Pilsen region in the Czech Republic, to create a typology of territorial units, and to evaluate the potential for development and possible threats to development in relation to individual territorial types. To this end, municipal statistical indicators pertaining to population, employment, and economy, were gathered from each of the given territories. The Voronoi map technique was applied to interpolate the values of selected indicators. The typology was created using one of the multivariate statistical methods, namely, the cluster analysis. Furthermore, typological regions and strategies for their development were created.

Aplikasi ESDA untuk Studi Variabilitas Spasial Hujan Bulanan di Jawa Timur

This 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; and 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.

Invariant colorings of random planar maps

We show that every locally finite random graph embedded in the plane with an isometry-invariant distribution can be five-colored in an invariant and deterministic way, under some non-triviality assumption and a mild assumption on the tail of edge lengths. The assumptions hold for any Voronoi map on a point process that has no non-trivial symmetries almost surely, hence we improve and generalize previous results on six-coloring the Voronoi map on a Poisson point process (see Angel, Benjamini, Gurel-Gurevich, Mayerovitch and Peled [Stationary map coloring. Preprint, 2008]).