Qualitative Regionalization of Bay of Bengal

Clustering is an essential statistical technique to find subgroups within a dataset. Clustering helps to uncover hidden relationships among the observational variables in the data. Many researchers have applied clustering techniques across a number of knowledge domains with success. Here we focus on application to ocean science, more particularly to the north region of the Indian Ocean, i.e., the Bay of Bengal. In this article, Regionalization is carried out for the Bay of Bengal to group the regions with similar characteristics using a graph-based clustering technique called SKATER (Spatial ‘K’luster Analysis by Tree Edge Removal). These subgroups are consistent with observations that characterize the near-surface features of the Bay of Bengal.

SPATIAL CLUSTER UNTUK PENGELOMPOKKAN WILAYAH SETIAP PROVINSI DI INDONESIA BERDASARKAN KARAKTERISTIK KESENJANGAN EKONOMI

Kesenjangan ekonomi antar wilayah merupakan fenomena global yang sering terjadi di negara berkembang, termasuk Indonesia. Kesenjangan ekonomi dapat dilihat dari pendapatan antar daerah yang tidak merata di setiap wilayah. Analisis yang dapat digunakan untuk mengelompokkan 34 provinsi di Indonesia berdasarkan karakteristik kesenjangan ekonomi salah satunya adalah metode spasial cluster. Penelitian ini bertujuan untuk mengetahui pengelompokan provinsi dengan metode SKATER (K’luster Analysis by Tree Edge Removal). Berdasarkan metode tersebut akan dibentuk 3 cluster dan 5 cluster untuk dibandingkan dan mendapatkan metode mana yang paling baik dengan analisis MANOVA. Hasil pengelompokan dari 3 cluster yang terbentuk dengan metode SKATER diperoleh hasil cluster 1 dengan 16 anggota provinsi. Cluster 2 dengan 2 anggota provinsi. Cluster 3 dengan 16 anggota provinsi. Hasil pengelompokan dari 5 cluster yang terbentuk dengan metode SKATER diperoleh hasil cluster 1 dengan 12 anggota provinsi. Cluster 2 dengan 1 anggota provinsi. Cluster 3 dengan 16 anggota provinsi. Cluster 4 dengan 1 anggota provinsi. Cluster 5 dengan 4 anggota provinsi. Dari analisis MANOVA didapatkan nilai Pillai’s Trace untuk metode SKATER dengan 3 Cluster sebesar 1,177 dan SKATER dengan 5 Cluster sebesar 1,355. Hal ini dapat disimpulkan bahwa metode SKATER dengan 5 Cluster lebih baik dari pada 3 Cluster.

Exploring the Evolution of Drought Characteristics in Balochistan, Pakistan

In the wake of a rapidly changing climate, droughts have intensified, in both duration and severity, across the globe. The Germanwatch long-term Climate Risk Index ranks Pakistan among the top 10 countries most affected by the adverse effects of climate change. Within Pakistan, the province of Balochistan is among the most vulnerable regions due to recurring prolonged droughts, erratic precipitation patterns, and dependence on agriculture and livestock for survival. This study aims to explore how the characteristics of droughts have evolved in the region from 1902–2015 using 3-month and 12-month timescales of a popular drought index, the Standardized Precipitation Evapotranspiration Index (SPEI). The region was divided into six zones using Spatial “K”luster Analysis using Tree Edge Removal (SKATER) method, and run theory was applied to characterize droughts in terms of duration, severity, intensity, and peak. The results of the non-parametric Mann–Kendall trend test applied to SPEI indicate prevailing significant negative trends (dryer conditions) in all the zones. Balochistan experienced its most severe droughts in the 1960s and around 2000. The effects of climate change are also evident in the fact that all the long duration droughts occurred after 1960. Moreover, the number of droughts identified by 3-month SPEI showed a significant increase after 1960 for all six zones. The same trend was found in the 12-month SPEI but for only three zones.

Municipal expenditures using own-source revenues and resilience of territorial inequalities in health

The objective of this study is to assess the importance of municipal expenses executed with own-source revenues for the maintenance of the territorial inequalities between resources allocated by Brazilian municipalities in the health sector, in spite of the redistributive effects attributed to the vertical transfers of the Brazilian National Health System. The formation of municipal own-source revenues is strongly impacted by regional economic inequalities, corresponding to almost 60% of the resources allocated by municipalities to health in recent years. Based on the Tree Edge Removal method, the total expenditures and those executed with own-source revenues by the municipalities were spatially distributed, thereby enabling identification of clusters from 2005 to 2015 in both cases. Central and dispersion measures were calculated for the two types of expenditure in this interval for the clusters. In the end, we found municipal expenditures with own-source revenues show levels of inequality which are significantly higher than those of the total municipal health expenditure, and even more significant is that these inequalities increase in time with higher intensity in the case of the former. Since municipalities are the main implementers of public health policy, results suggest higher levels of territorial equity will necessarily require adjustments in fiscal federalism in this sector.

Spatio-Temporal Variability of Drought in Pakistan Using Standardized Precipitation Evapotranspiration Index

Pakistan is among the top ten countries adversely affected by climate change. More specifically, there is concern that climate change may cause longer and severer spells of droughts. To quantify the change in the characteristics of droughts in Pakistan over the years, we have evaluated spatio-temporal trends of droughts in Pakistan over the period 1902–2015 using Standardized Precipitation Evapotranspiration Index (SPEI). Additionally, the Spatial “K” luster Analysis using Tree Edge Removal (SKATER) method was employed to regionalize droughts into five contiguous zones. The run theory was then applied to each zone to identify drought events and characterize them in terms of duration, severity, intensity, and peak. Moreover, the Modified Mann–Kendall trend test was applied to identify statistically significant trends in SPEI and drought characteristics in each zone. It was found that the southern areas of Pakistan, encompassing Sindh and most of Baluchistan, have experienced a decrease in SPEI, indicating a drying trend. Central Pakistan has witnessed a wetting trend as demonstrated by an increase in SPEI over time, whereas no statistically significant trend was observed for the northern areas of Pakistan. On a zonal basis, the longest duration drought to occur in Pakistan lasted 22 months in zone 5 (Sindh) from 1968 to 1970. In addition, the drought of 1920 and 2000 can be said to be the worst drought in the history of the region as it affected all the zones and lasted for more than 10-months in three zones.

Tracing Paths and Connecting Multiple Design Domains: An Information Visualisation Approach to Product Architecture Modelling

Visual representation of product architecture models is crucial in complex engineering systems design. However, when the number of entities in a model is large and when multiple levels of hierarchies are included, visual representations currently in use need to be more intuitive. As such, improved visual representations that enable better system overview and better communication of essential product- related information among design participants are needed. This paper uses interactive information visualisation techniques – collapsible hierarchical tree, edge bundling and alluvial diagram – and provides the foundations of a computerised tool that improves the traceability of connections between design domains, including stakeholders, requirements, functions, behaviours and structure. The case of a cleaning robot is used as an illustrative example. The approach supports designers by providing an enhanced overview during the development of complex product architecture models, in particular in the communication with external stakeholders, in the identification of change propagation paths across several design domains, and in capturing the design rationale of previous design decisions.

Focusing neighborhood context and self-rated health in the Pró-Saúde Study

The influence of neighborhood characteristics on self-rated health has been little studied. A multilevel approach using hierarchical models was applied to analyze the relationship between the socioeconomic characteristics in 621 neighborhoods (level 2) in the city of Rio de Janeiro, Brazil, and the self-rated health of 3,054 university employees (level 1) from the baseline of the Pró-Saúde Study. Neighborhoods were created using the SKATER algorithm (Spatial ‘K’luster Analysis by Tree Edge Removal) to cluster census tracts according to four indicators and a minimum population of 5,000 people. After adjustment for individual factors (per capita income, schooling, age, sex, ethnicity, health-related behavior and chronic diseases), low level of neighborhood income and higher numbers of members per household were significantly associated with poor self-rated health. Participants living in medium income-level neighborhoods were 34% more likely to self-rate their health as being poor. Those living in areas with a higher density of members per household were 50% more likely to present poor self-rated health. Neighborhood context influences self-rated health, beyond the effect of individual factors. Worsening neighborhood socioeconomic conditions affect health adversely, which in turn increasing the chance of poor self-rated health.

Application of modified Spatial K’luster Analysis by Tree Edge Removal Method (SKATER) on the level of Crime data in Way Kanan district, Lampung

<p>Modification of method Spatial K'luster Analysis by Tree Edge Removal (SKATER) is one of the regionalization method for clustering based on the location by spatial autocorrelation and spatial patterns. This method uses graph theory approach to identify the homogeneous location is the minimum spanning tree. In addition to clustering objects based on similarity characteristics, in everyday life, often found that there are significant spatial clustering that affect specific object. This study was conducted to determine the relationship of the crime rate between districts in Way Kanan, Lampung. Based on these results, the characteristics of the crime rate in terms of spoliation, robbery and gambling have spatial autocorrelation and spatial patterns. Further applied modifications of SKATER. Generate 4 cluster (k) graded of the 14 districts. on average k₁(17.67% ) k₂ (10.09%) k₃ (7.80%) k₄ (4.28%).</p>