Complete Spatial Randomness

2018 ◽  
pp. 1-5
Author(s):  
Philip M. Dixon
Keyword(s):  
Complete Spatial Randomness ◽  
Spatial Randomness

Analisis Perubahan Tata Guna Lahan di Kabupaten Bantul Menggunakan Metode Global Moran’s I

2017 ◽  
Vol 8 (4) ◽  
Author(s):  
Matheus Supriyanto Rumetna ◽  
Eko Sediyono ◽  
Kristoko Dwi Hartomo
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Spatial Autocorrelation ◽  
Land Use Changes ◽  
Geographical Information ◽  
Moran’S I ◽  
Complete Spatial Randomness ◽  
Moran's I ◽  
Global Moran’S I ◽  
Spatial Randomness

Abstract. Bantul Regency is a part of Yogyakarta Special Province Province which experienced land use changes. This research aims to assess the changes of shape and level of land use, to analyze the pattern of land use changes, and to find the appropriateness of RTRW land use in Bantul District in 2011-2015. Analytical methods are employed including Geoprocessing techniques and analysis of patterns of distribution of land use changes with Spatial Autocorrelation (Global Moran's I). The results of this study of land use in 2011, there are thirty one classifications, while in 2015 there are thirty four classifications. The pattern of distribution of land use change shows that land use change in 2011-2015 has a Complete Spatial Randomness pattern. Land use suitability with the direction of area function at RTRW is 24030,406 Ha (46,995406%) and incompatibility of 27103,115 Ha or equal to 53,004593% of the total area of Bantul Regency.Keywords: Geographical Information System, Land Use, Geoprocessing, Global Moran's I, Bantul Regency. Abstrak. Analisis Perubahan Tata Guna Lahan di Kabupaten Bantul Menggunakan Metode Global Moran’s I. Kabupaten Bantul merupakan bagian dari Provinsi Daerah Istimewa Yogyakarta yang mengalami perubahan tata guna lahan. Penelitian ini bertujuan untuk mengkaji perubahan bentuk dan luas penggunaan lahan, menganalisis pola sebaran perubahan tata guna lahan, serta kesesuaian tata guna lahan terhadap RTRW yang terjadi di Kabupaten Bantul pada tahun 2011-2015. Metode analisis yang digunakan antara lain teknik Geoprocessing serta analisis pola sebaran perubahan tata guna lahan dengan Spatial Autocorrelation (Global Moran’s I). Hasil dari penelitian ini adalah penggunaan tanah pada tahun 2011, terdapat tiga puluh satu klasifikasi, sedangkan pada tahun 2015 terdapat tiga puluh empat klasifikasi. Pola sebaran perubahan tata guna lahan menunjukkan bahwa perubahan tata guna lahan tahun 2011-2015 memiliki pola Complete Spatial Randomness. Kesesuaian tata guna lahan dengan arahan fungsi kawasan pada RTRW adalah seluas 24030,406 Ha atau mencapai 46,995406 % dan ketidaksesuaian seluas 27103,115 Ha atau sebesar 53,004593 % dari total luas wilayah Kabupaten Bantul. Kata Kunci: Sistem Informasi Georafis, tata guna lahan, Geoprocessing, Global Moran’s I, Kabupaten Bantul.

scholarly journals ANÁLISE DO PADRÃO DE DISTRIBUIÇÃO ESPACIAL DOS CASOS DE TUBERCULOSE EM ARAPIRACA/AL, PERÌODO 2000-2005

2018 ◽  
Vol 1 (1) ◽  
pp. 38
Author(s):  
Carlos Mauricio Rocha Barroso ◽  
José Vicente Ferreira Neto
Keyword(s):  
Complete Spatial Randomness ◽  
Spatial Randomness

Avaliou-se o padrão de distribuição espacial dos novos casos de tuberculose (TB) entre 2000 e 2005, na zona urbana do município de Arapiraca, Estado de Alagoas. Para a análise do padrão pontual dos eventos considerados (aleatoriedade, regularidade ou aglomerados), foi aplicado o modelo de Aleatoriedade Espacial Completa (Complete Spatial Randomness-CSR), através da função K que considera os efeitos de segunda ordem. A função K aplicada às localizações geográficas das ocorrências dos casos de TB mostrou que o padrão da distribuição dos casos de tuberculose não é aleatório, indicando agrupamentos em todos os anos do período estudado. O método Kernel ratificou a presença de aglomeração espacial dos casos, assim como permitiu detectar onde os eventos estavam concentrados. As áreas Centro – Nordeste e Centro-Sudeste destacam-se, sendo a primeira com maior intensidade.

scholarly journals Generalized index for spatial data sets as a measure of complete spatial randomness

2012 ◽  
Vol 85 (6) ◽  
Author(s):  
Emily J. Hackett-Jones ◽  
Kale J. Davies ◽  
Benjamin J. Binder ◽  
Kerry A. Landman
Keyword(s):  
Spatial Data ◽  
Data Sets ◽  
Complete Spatial Randomness ◽  
Spatial Data Sets ◽  
Spatial Randomness

Analytical heat conduction model of a composite material based on complete spatial randomness of filler in base matrix

2017 ◽  
Vol 118 ◽  
pp. 292-302 ◽  
Author(s):  
Ravi Verma ◽  
Aritra Chatterjee ◽  
Azlaan Mustafa ◽  
N.C. Shivaprakash ◽  
S. Kasthurirengan ◽  
...  
Keyword(s):  
Composite Material ◽  
Heat Conduction ◽  
Complete Spatial Randomness ◽  
Conduction Model ◽  
Heat Conduction Model ◽  
Base Matrix ◽  
Spatial Randomness

FINDING OUTLIERS AT MULTIPLE SCALES

2005 ◽  
Vol 04 (02) ◽  
pp. 251-262 ◽  
Author(s):  
TIANMIN HU ◽  
SAM YUAN SUNG
Keyword(s):  
Data Structure ◽  
Outlier Detection ◽  
Multiple Scales ◽  
Low Density ◽  
Complete Spatial Randomness ◽  
Multi Scale ◽  
Spatial Randomness

Outlier detection targets those exceptional data whose pattern is rare and lie in low density regions. In this paper, under the assumption of complete spatial randomness inside clusters, we propose an MDV (Multi-scale Deviation of the Volume) approach to identifying outliers. In addition to assigning an outlier score for each object, it directly outputs a crisp outlier set. It also offers a plot showing the data structure in every object's vicinity, which is useful in explaining why it may be outlying. Finally, the effectiveness of MDV is demonstrated with both artificial and real datasets.

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