Analisis Pola Kebakaran Lahan di Kalimantan Timur dengan MODIS dan VIIRS

2020 ◽  
Vol 21 (1) ◽  
pp. 84
Author(s):  
Aditya Pranata Wibowo ◽  
Frederik Samuel Papilaya
Keyword(s):  
Spatial Autocorrelation ◽  
Nearest Neighbor ◽  
Directional Distribution

Kebakaran adalah suatu peristiwa timbulnya reaksi oksidasi saat adanya bahan bakar, oksigen, dan energi panas yang menyebabkan pembakaran yg tidak terkendali dan menyebabkan kerugian. Pemantauan secara spasial terhadap kebakaran menjadi suatu hal yang sangat penting untuk dikaji. Penelitian ini bertujuan untuk mengetahui daerah manakah yang paling banyak mengalami kebakaran dan juga pola dari kebakaran tersebut. Sumber data didapatkan dari website FIRMS yang merupakan data yang bersifat kuantitatif dan data primer. Metode analisis yang digunakan adalah metode analisis Spatial Autocorrelation, Average Nearest Neighbor, Optimized Hotspot, Directional Distribution (Standard Devitional Ellipse), dan Temporal Collect Event. Hasil yang telah didapatkan dari analisis bermetode Directional Distribution, Optimized Hotspot, dan Temporal Collect Event adalah terdapat banyak titik api yang berada di Kecamatan Kutai Kartanegara, Kutai Barat, Kutai Timur, Berau, dan Paser. Dalam analisis Spatial Autocorrelation ditemukan bahwa terdapat korelasi antara lokasi terjadinya titik api dan ukuran sejati dari titik api. Analisis Average Nearest Neighbor menunjukkan bahwa titik api terkumpul pada beberapa tempat dan tidak tersebar merata.

Spatial Pattern Analysis on Dengue Cases in Bangi district, Selangor, Malaysia

2020 ◽  
Author(s):  
Nuriah Abd Majid ◽  
Ruslan Rainis ◽  
Mazrura Sahani ◽  
Ahmad Fariz Mohamed ◽  
Sarah Aziz Abdul Ghani Aziz ◽  
...  
Keyword(s):  
Spatial Pattern ◽  
Distribution Pattern ◽  
Pattern Analysis ◽  
Nearest Neighbor ◽  
Statistical Analyses ◽  
Spatial Pattern Analysis ◽  
Study Region ◽  
Directional Distribution ◽  
Standard Distance ◽  
Positive Factor

Abstract Background: Dengue outbreak has proliferated around the developing countries, including Malaysia, in recent decades. Thus, understanding the distribution pattern is essential for urbanization livelihood. Method: The objective of this study is to determine the trend of dengue cases reported from year 2014 to 2018 and the spatial pattern for dengue spread with reference to weather elements in Bangi town. Results: Spatial statistical analyses conducted found that the distribution pattern and spatial mean center for dengue cases was clustered at the east of Bangi region. Directional distribution observed that the elongated polygon of dengue cluster stretched from the northeast to the southwest of Bangi district. Standard distance for dengue cases was the smallest for the year 2014 (0.017 m), and the largest was in the year 2016 (0.019 m), whereas dengue cases in year 2015, 2017, and 2018 were measured at 0.018 m. The average nearest neighbor analysis also observed clustered patterns for dengue cases in Bangi district. Pearson’s correlation analysis found that temperature (r = -0.269) was negatively correlated with dengue cases for year 2014 and 2018; however, rainfall amount (r = 0.286) and rain days (r = 0.250) were positively correlated with dengue cases in year 2018.Conclusions: The three spatial statistical analyses (spatial mean center, standard distance, and directional distribution) findings illustrated that the dengue cases from the year 2014 to 2018 are clustered on the northeast to the southwest of the study region. The rainfall element is found to be a significant positive factor correlated for most study years compared to temperature element.

Conditional Spatial Patterning: Beyond the Nearest Neighbor

1987 ◽  
Vol 52 (3) ◽  
pp. 500-521 ◽  
Author(s):  
Albertus Voorrips ◽  
John M. O'Shea
Keyword(s):  
Computer Simulation ◽  
Spatial Autocorrelation ◽  
Nearest Neighbor ◽  
Spatial Patterning ◽  
Late Mesolithic ◽  
Count Statistic

This paper discusses a method for the analysis of spatial patterning which is based on aspects of the study of spatial autocorrelation. By means of computer simulation it is shown that the join count statistic (Cliff and Ord 1973; Moran 1950) has a wider validity than was presumed originally. Some archaeological applications from the analysis of a late Mesolithic cemetery in Karelia, USSR, are presented.

Observation of Superlattice Dislocations on Cube Planes in Ni3Al

1973 ◽  
Vol 31 ◽  
pp. 174-175 ◽  
Author(s):  
J. M. Oblak ◽  
W. H. Rand
Keyword(s):  
Nearest Neighbor ◽  
Antiphase Boundary ◽  
Nearest Neighbors ◽  
High Energy ◽  
Cross Slip ◽  
Octahedral Plane ◽  
Trapping Mechanism ◽  
Slip Traces

The energy of an a/2 <110> shear antiphase. boundary in the Ll2 expected to be at a minimum on {100} cube planes because here strue ture is there is no violation of nearest-neighbor order. The latter however does involve the disruption of second nearest neighbors. It has been suggested that cross slip of paired a/2 <110> dislocations from octahedral onto cube planes is an important dislocation trapping mechanism in Ni3Al; furthermore, slip traces consistent with cube slip are observed above 920°K.Due to the high energy of the {111} antiphase boundary (> 200 mJ/m2), paired a/2 <110> dislocations are tightly constricted on the octahedral plane and cannot be individually resolved.

Application of Lattice Imaging Techniques to Amorphous Films

1975 ◽  
Vol 33 ◽  
pp. 8-9
Author(s):  
S. R. Herd ◽  
P. Chaudhari
Keyword(s):  
Nearest Neighbor ◽  
Random Network ◽  
Imaging Techniques ◽  
Network Models ◽  
Accurate Method ◽  
Direct Transmission ◽  
Lattice Imaging ◽  
Transmission Electron ◽  
Lattice Planes ◽  
Nearest Neighbor Distances

Electron diffraction and direct transmission have been used extensively to study the local atomic arrangement in amorphous solids and in particular Ge. Nearest neighbor distances had been calculated from E.D. profiles and the results have been interpreted in terms of the microcrystalline or the random network models. Direct transmission electron microscopy appears the most direct and accurate method to resolve this issue since the spacial resolution of the better instruments are of the order of 3Å. In particular the tilted beam interference method is used regularly to show fringes corresponding to 1.5 to 3Å lattice planes in crystals as resolution tests.

Machine Learning Verdict of EEG Signals in Brain Computer Interface

2018 ◽  
pp. 429-441
Author(s):  
M. Jeyanthi ◽  
C. Velayutham
Keyword(s):  
Nearest Neighbor ◽  
Technology Development ◽  
Vital Role ◽  
Svm Classifier ◽  
K Nearest Neighbor ◽  
Data Mining Technique ◽  
Data Set ◽  
Eeg Data ◽  
Irrelevant Attributes

In Science and Technology Development BCI plays a vital role in the field of Research. Classification is a data mining technique used to predict group membership for data instances. Analyses of BCI data are challenging because feature extraction and classification of these data are more difficult as compared with those applied to raw data. In this paper, We extracted features using statistical Haralick features from the raw EEG data . Then the features are Normalized, Binning is used to improve the accuracy of the predictive models by reducing noise and eliminate some irrelevant attributes and then the classification is performed using different classification techniques such as Naïve Bayes, k-nearest neighbor classifier, SVM classifier using BCI dataset. Finally we propose the SVM classification algorithm for the BCI data set.

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