scholarly journals MARINE ENVIRONMENTAL VULNERABILITY OF EACH PROVINCE IN INDONESIA

2012 ◽  
Vol 4 (1) ◽  
Author(s):  
Adi Wibowo
Keyword(s):  
Spatial Analysis ◽  
Population Growth ◽  
Spatial Pattern ◽  
Problem Statement ◽  
Tropical Island ◽  
Coast Line ◽  
Environmental Vulnerability ◽  
High Level ◽  
Marine Environmental ◽  
Very High

Interaction between mainland and ocean are not balance. That means condition in mainland will higher affect the ocean, but not vice versa. Indonesia as a tropical island country has very long beaches and many rivers flow into the sea. The increased population in each province will have an impact on increasing contaminant into the river, so those are will cause the contaminant into the sea increasing. The problem statement is at what level of the marine environmental vulnerability in each province? Using methods of spatial analysis those find the spatial pattern of the marine environmental vulnerabilities in Indonesia. Level of the marine environmental vulnerability is generated based on numbers of regency along the coast line, including the total of population and population growth in each province and the number of rivers along the coast line. Conclusion in this research is province with the very high level of the marine environmental vulnerability is eleventh provinces, fifteenth provinces with high level, five provinces with moderate level, and two provinces with the lowest level. The province with very high level is caused by variation combination from the high number of regency along the coast line, including the highest number of population and population growth and the highest number of river. Such conditions may cause high vulnerability in some provinces such as Nanggroe Aceh Darusallam, Bangka Belitung, Kepulauan Riau, Banten, Bali, Nusa Tenggara Barat, Nusa Tenggara Timur, Sulawesi Utara, Sulawesi Tengah and Sulawesi Tenggara.Keywords: Vulnerability, marine environmental, spatial analysis

scholarly journals MARINE ENVIRONMENTAL VULNERABILITY OF EACH PROVINCE IN INDONESIA

2012 ◽  
Vol 4 (1) ◽  
Author(s):  
Adi Wibowo
Keyword(s):  
Spatial Analysis ◽  
Population Growth ◽  
Spatial Pattern ◽  
Problem Statement ◽  
Tropical Island ◽  
Coast Line ◽  
Environmental Vulnerability ◽  
High Level ◽  
Marine Environmental ◽  
Very High

<p>Interaction between mainland and ocean are not balance. That means condition in mainland will higher affect the ocean, but not vice versa. Indonesia as a tropical island country has very long beaches and many rivers flow into the sea. The increased population in each province will have an impact on increasing contaminant into the river, so those are will cause the contaminant into the sea increasing. The problem statement is at what level of the marine environmental vulnerability in each province? Using methods of spatial analysis those find the spatial pattern of the marine environmental vulnerabilities in Indonesia. Level of the marine environmental vulnerability is generated based on numbers of regency along the coast line, including the total of population and population growth in each province and the number of rivers along the coast line. Conclusion in this research is province with the very high level of the marine environmental vulnerability is eleventh provinces, fifteenth provinces with high level, five provinces with moderate level, and two provinces with the lowest level. The province with very high level is caused by variation combination from the high number of regency along the coast line, including the highest number of population and population growth and the highest number of river. Such conditions may cause high vulnerability in some provinces such as Nanggroe Aceh Darusallam, Bangka Belitung, Kepulauan Riau, Banten, Bali, Nusa Tenggara Barat, Nusa Tenggara Timur, Sulawesi Utara, Sulawesi Tengah and Sulawesi Tenggara.</p><p>Keywords: Vulnerability, marine environmental, spatial analysis</p>

scholarly journals An Exploratory Analysis in Mapping of Asthma Risk in Western Australia

2018 ◽  
Vol 50 (1) ◽  
pp. 97
Author(s):  
Hendra Kurnia Febriawan ◽  
Carla Maria Da Silva Sodre
Keyword(s):  
Spatial Analysis ◽  
Spatial Pattern ◽  
Western Australia ◽  
Exploratory Analysis ◽  
Annual Rainfall ◽  
Asthma Prevalence ◽  
Low Level ◽  
Asthma Risk ◽  
Confirmatory Analysis ◽  
High Level

Exploratory Analysis as one of the spatial analysis tools that has been used widely in many study fields. This tool is usually intended to obtain the spatial pattern to observe and get relationship between study variables. The exploratory analysis is usually followed by the confirmatory analysis to exhibit the hypothesis that already obtain in the exploratory analysis. This study is aimed to investigate the prevalence of asthma in Western Australia since there are many factors that cause the asthma dispersion.  Many provided variables have been tested to get the best correlation with the asthma percentage variable and four variables (humidity, annual rainfall, EVI and SEIFA) were chosen and tested with high asthma percentage variable. The result of confirmatory analysis indicates that the high level of humidity and low level of SEIFA confirm with the hypothesis and means that those factors can contribute significantly in Asthma prevalence in Western Australia.

scholarly journals Identification and Spatial Pattern of Kao Bay Bathymetry Based on UNCLOS

2015 ◽  
Vol 29 (1) ◽  
Author(s):  
Yulius Yulius ◽  
H L Salim
Keyword(s):  
Spatial Analysis ◽  
Spatial Pattern ◽  
Surface Area ◽  
Total Surface Area ◽  
Line Length ◽  
Coast Line ◽  
Nautical Chart ◽  
Bay Area ◽  
Full Compliance ◽  
Gis Software

Kao Bay is located in the province of North Maluku between Regency of North Halmahera and West Halmahera. The study aims are to identify bay criteria according to UNCLOS and bathymetry based on Nautical Chart. The methods used in this study are the identification of the bay area under UNCLOS and spatial analysis using GIS software. The result shows that Kao Bay has a coast line length of 127.7 km, a mouth bay cover line of 11.1 km, total surface area of  964.38  km2, and total surface semi-circular bay cover area of 48.4 km2. The total surface area larger than the area of the semicircle bay cover area. It has been full compliance with the criteria required by UNCLOS. Spatial analysis, found that for the depth of water in Kao Bay can be divided into six classes, these are: (1) 0 – 100 meter with area of 964,38 km2, (2) 100 - 200 meter with area of 667.25 km2, (3) 200 - 300 meter with area of 556.95 km2, (4) 300 - 400 meter with area of 376.89 km2, (5) 400 - 500 meter with area of 202.44 km2, (6) 500 - 600 meter with area of 2.22 km2.

التغير المناخي واثره في المقنن المائي لمحصول العنب في محافظة ديالى

2019 ◽  
Vol 1 (34) ◽  
pp. 391-422
Author(s):  
اشواق حسن حميد صالح
Keyword(s):  
Climate Change ◽  
Statistical Analysis ◽  
Wind Speed ◽  
Extreme Temperature ◽  
Solar Brightness ◽  
The Subject ◽  
Climate Station ◽  
The Times ◽  
High Level ◽  
Very High

Climate change and its impact on water resources is the problem of the times. Therefore, this study is concerned with the subject of climate change and its impact on the water ration of the grape harvest in Diyala Governorate. The study was based on the data of the Khanaqin climate station for the period 1973-2017, (1986-2017) due to lack of data at governorate level. The general trend of the elements of the climate and its effect on the water formula was extracted. The equation of change was extracted for the duration of the study. The statistical analysis was also used between the elements of the climate (actual brightness, normal temperature, micro and maximum degrees Celsius, wind speed m / s, relative humidity% The results of the statistical analysis confirm that the water ration for the study area is based mainly on the X7 evaporation / netting variable, which is affected by a set of independent variables X1 Solar Brightness X4 X5 Extreme Temperature Wind Speed ​​3X Minimal Temperature and Very High Level .

Difusi dan Pola Spasial Sebaran Penyakit Demam Berdarah Dengue (DBD) Di Kota Bandar Lampung

2018 ◽  
Vol 1 (1) ◽  
pp. 87-95
Author(s):  
Nurul Qamila ◽  
Agel Vidian Krama
Keyword(s):  
Public Health ◽  
Spatial Analysis ◽  
Aedes Aegypti ◽  
Dengue Virus ◽  
Spatial Pattern ◽  
Dengue Hemorrhagic Fever ◽  
Health Problem ◽  
Public Health Problem ◽  
Hemorrhagic Fever ◽  
Descriptive Method

Dengue hemorrhagic fever (DHF) is a contagious disease caused by the dengue virus and is transmitted by the mosquito Aedes aegypti (Aa.aegypti). The population is still a public health problem that increases the number of sufferers and also widespread, with population and education. This study aims to reveal the spatial pattern and distribution of Dengue Hemorrhagic Fever (DHF) with the spatial pattern and the spread of Dengue Hemorrhagic Fever (DHF) can result in different locations of these allegations. From the map that can be used for the prevention of Dengue Hemorrhagic Fever (DBD) in Bandar Lampung City. This study aims to reveal the spatial pattern and distribution of Dengue Hemorrhagic Fever (DHF) with the descriptive method and spatial pattern of Dengue Hemorrhagic Fever (DHF) can result in different locations of these allegations. From the map that can be used for the prevention of Dengue Hemorrhagic Fever (DBD) in Bandar Lampung City. Keywords: DHF, Spatial Analysis

Relations between carbon removal rates, biofilm size and density of a novel anaerobic reactor: the inverse turbulent bed

2000 ◽  
Vol 41 (4-5) ◽  
pp. 253-260 ◽  
Author(s):  
P. Buffière ◽  
R. Moletta
Keyword(s):  
Removal Rate ◽  
Removal Rates ◽  
Carbon Removal ◽  
Biofilm Growth ◽  
Loading Rates ◽  
Biomass Activity ◽  
High Turbulence ◽  
The One ◽  
High Level ◽  
Very High

An anaerobic inverse turbulent bed, in which the biogas only ensures fluidisation of floating carrier particles, was investigated for carbon removal kinetics and for biofilm growth and detachment. The range of operation of the reactor was kept within 5 and 30 kgCOD· m−3· d−1, with Hydraulic Retention Times between 0.28 and 1 day. The carbon removal efficiency remained between 70 and 85%. Biofilm size were rather low (between 5 and 30 μm) while biofilm density reached very high values (over 80 kgVS· m−3). The biofilm size and density varied with increasing carbon removal rates with opposite trends; as biofilm size increases, its density decreases. On the one hand, biomass activity within the reactor was kept at a high level, (between 0.23 and 0.75 kgTOC· kgVS· d−1, i.e. between 0.6 and 1.85 kgCOD·kgVS · d−1).This result indicates that high turbulence and shear may favour growth of thin, dense and active biofilms. It is thus an interesting tool for biomass control. On the other hand, volatile solid detachment increases quasi linearly with carbon removal rate and the total amount of solid in the reactor levels off at high OLR. This means that detachment could be a limit of the process at higher organic loading rates.

A Tight Connection Among Wealth, Income, Sustainability, and Accounting in an Ultra-Simplified Setting

2017 ◽  
Author(s):  
Martin L. Weitzman
Keyword(s):  
Economic Theory ◽  
Quantitative Relationship ◽  
Theoretical Relationship ◽  
Level Of Abstraction ◽  
Tight Connection ◽  
Basic Concepts ◽  
High Level ◽  
Very High

In theory, and under some very strong assumptions, there exists a tight quantitative relationship among the following four fundamental economic concepts: (1) ‘wealth’; (2) ‘income’; (3) ‘sustainability’; (4) ‘accounting’. These four basic concepts are placed in quotation marks here because a necessary first step will be to carefully and rigorously define what exactly is meant by each. This chapter reviews what is known about this important fourfold quantitative relationship in an ultra-simplified setting. It identifies some basic applications of this simplified economic theory of wealth and income (and sustainability and accounting). While the contents of this chapter are expressed at a very high level of abstraction and require many restrictive assumptions, the fundamental fourfold relationship it sharply highlights should be useful for conceptualizing, at least in principle, what is ‘wealth’ and what is its theoretical relationship to ‘income’, ‘sustainability’, and ‘accounting’.

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