From Green Spaces to Squares: Mapping the Distribution of Taijiquan Organizations in London

Contributing to Taijiquan studies, this research uses spatial analysis tools in ArcGIS 10.3 and SPSS 23.0 to map out the spatial distributional pattern of the Taijiquan organizations in London, and then explores factors attributing to the spatial distribution of Taijiquan culture. The result shows that the distribution of Taijiquan organizations in London generally presents a spatial distribution structure of “dense center + sparse periphery”; the spatial distribution is unbalanced, showing a cohesive distribution; the directional distribution tends to be obvious in areas that are proximate to urban traffic arteries and afforestation in London. Through multivariate hierarchical regression analysis, the study explores the influential factors for the spatial distribution of Taijiquan organizations in London. The results show that: population size, economic level, and education level have little influence on the spatial distribution of Taijiquan organizations; however, the population density of people over 65 years old, the accessibility of public service facilities such as green spaces, and public urban traffic has a significant impact on the spatial distribution of Taijiquan organizations.

Spatial pattern of dengue cases: An analysis in Bangi District, Selangor, Malaysia

In recent decades, dengue outbreaks have become increasingly common around the developing countries, including Malaysia. Thus, it is essential for rural as well as urbanised livelihood to understand the distribution pattern of this infection. The objective of this study is to determine the trend of dengue cases reported from the year 2014 to 2018 and the spatial pattern for this spread. Spatial statistical analyses conducted found that the distribution pattern and spatial mean centre for dengue cases were clustered in the eastern part of the Bangi region. Directional distribution observed that the elongated polygon of dengue cluster stretched from the Northeast to the Southwest of Bangi District. The standard distance observed for dengue cases was smallest in the year 2014 (0.017 m), and largest in 2016 (0.019 m), whereas in the year 2015, 2017 and 2018, it measured 0.018 m. The average nearest neighbour analysis also displayed clustered patterns for dengue cases in the Bangi District. The three spatial statistical analyses (spatial mean centre, standard distance and directional distribution) findings illustrate that the dengue cases from the year 2014 to 2018 are clustered in the Northeast to the Southwest of the study region.

Spatio-temporal pattern of tropical cyclones: The case of cyclones of the bay of Bengal

For the last few decades, the generalized pattern of tropical cyclones has gone through an unstable system transformation in the global changing climatic scenario. Thus, the broad aim of this research work was to explore the spatio-temporal changing pattern of tropical cyclones in the basin of the Bay of Bengal between 1985 and 2019. Cyclone track information data have been collected from Emergency Events Database (EM-DAT) server and Bangladesh Meteorological Department. The loss and damage statistics has been collected from different published sources. Geographical distributional characteristics such as mean center and standard directional distribution have been explored using the spatial statistical tool of ArcMap. The mean geographic center has been identified near the district of Bhola and Patuakhali. The cyclonic occurrences in the research area are oriented north-west to south-east according to standard directional distribution. Hot spot analysis was used to identify the most affected parts in the study area and found that there are no significant hotspots, but the distribution pattern is rather random. However, there are two minor concentration zones in the study area, one near Barguna and another one near Sandwip coast. SPSS software was also used here to analyze the relationship between cyclonic events and the loss/damage scenarios of the study area. The relationship between cyclonic velocity and damage of life and livelihood showed a strong correlation of .804 with a significance level of 99% (p < .01). Random cyclonic trends and patterns indicate a change in this region's climatic variability over the past 35 years.

Microsaccadic rate signatures correlate under monocular and binocular stimulation conditions

Microsaccades are involuntary eye movements occurring naturally during fixation. In this study, microsaccades were investigated under monocularly and binocularly stimulated conditions with respect to their directional distribution and rate signature, that refers to a curve reporting the frequency modulation of microsaccades over time. For monocular stimulation the left eye was covered by an infrared filter. In both stimulation conditions, participants fixated a Gabor patch presented randomly in orientation of 45° or 135° over a wide range of spatial frequencies appearing in the center of a monitor. Considering the microsaccadic directions, this study showed microsaccades to be preferably horizontally oriented in their mean direction, regardless of the spatial characteristics of the grating. Furthermore, this outcome was found to be consistent between both stimulation conditions. Moreover, this study found that the microsaccadic rate signature curve correlates between both stimulation conditions, while the curve given for binocular stimulation was already proposed as a tool for estimation of visual performance in the past. Therefore, this study extends the applicability of microsaccades to clinical use, since parameters as contrast sensitivity, has been measured monocularly in the clinical attitude.

Analisis Pola Kebakaran Lahan di Kalimantan Timur dengan MODIS dan VIIRS

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

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.

POLA SPASIAL TEMPORAL KECELAKAAN LALU LINTAS DI DAERAH ISTIMEWA YOGYAKARTA

This study aims to determine the area of traffic accident prone (hotspots) and determine the temporal spatial development of traffic accident areas in the Special Region of Yogyakarta, from 2016 to 2018. The method used is Optimized Hotspot Analysis and Directional Distribution with the help of ArcGIS software. The results of this study indicate that the location of traffic accidents in the Special Region of Yogyakarta is spread throughout the Special Region of Yogyakarta, with hotspots in 2016 located in 114 villages, in 2017 located in 110 villages, and in 2018 in 112 villages. The temporal spatial development of traffic accident locations in the Special Region of Yogyakarta changed from 2016 to 2018, with rotation in 2016 of 102.32 degrees, in 2017 of 37.59 degrees, and in 2018 of 45.55 degrees. Keywords: traffic accidents, traffic accident locations, traffic accident prone areas, hotspots Abstrak Penelitian ini bertujuan untuk menentukan daerah rawan kecelakaan lalu lintas (hotspots) dan menentukan perkembangan spasial temporal daerah kecelakaan lalu lintas di Daerah Istimewa Yogyakarta, dari tahun 2016 hingga tahun 2018. Metode yang digunakan adalah Optimized Hotspot Analysis dan Directional Distribution dengan bantuan perangkat lunak ArcGIS. Hasil penelitian ini menunjukkan bahwa lokasi kecelakaan lalu lintas di Daerah Istimewa Yogyakarta menyebar di seluruh wilayah Daerah Istimewa Yogyakarta, dengan wilayah hotspots tahun 2016 berada di 114 desa/kelurahan, tahun 2017 di 110 desa/kelurahan, dan tahun 2018 di 112 desa/kelurahan. Perkembangan spasial temporal lokasi kecelakaan lalu lintas di Daerah Istimewa Yogyakarta berubah dari tahun 2016 hingga tahun 2018, dengan rotasi di tahun 2016 sebesar 102,32 derajat, di tahun 2017 sebesar 37,59 derajat, dan di tahun 2018 sebesar 45,55 derajat. Kata-kata kunci: kecelakaan lalu lintas, lokasi kecelakaan lalu lintas, daerah rawan kecelakaan lalu lintas, hotspots