Flood risk spatial index analysis in the coastal Pekalongan, Central Java, Indonesia

The North coast of Java is increasingly exposed to flood risks due to land subsidence and climate change, resulting in sea-level rise. This paper developed a flood risk spatial index model in the coastal Pekalongan. The model was systematically arranged from various flood risk indicators related to the social, economic, and environment of coastal Pekalongan based on surveys and interviews with the communities and regional governments. These indicators are then integrated into hazard and vulnerability as components of risk. Using the index system method and ArcGIS, the risk index is classified into five levels (very high, high, medium, low, very low) and generated into a flood risk spatial distribution map. We found that the risk in the study area varies between a medium to a very high level of risk. The very high level of risk was located in Tratebang, Pecakaran, and Tegaldowo Village. A risk spatial distribution map can be used to evaluate potential risks and flood mitigation.

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Time series analysis and spatial distribution map of aggregate risk index due to tropospheric NO2 and O3 based on satellite observation

Journal of Environmental Management ◽

10.1016/j.jenvman.2021.114202 ◽

2022 ◽

Vol 304 ◽

pp. 114202

Author(s):

Neda Shojaei Baghini ◽

Samereh Falahatkar ◽

Mohammad Sadegh Hassanvand

Keyword(s):

Time Series ◽

Spatial Distribution ◽

Time Series Analysis ◽

Risk Index ◽

Satellite Observation ◽

Distribution Map ◽

Series Analysis ◽

Aggregate Risk ◽

Tropospheric No2 ◽

Spatial Distribution Map

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Analisis Spektral Data Curah Hujan di Sulawesi Utara

Jurnal MIPA ◽

10.35799/jm.2.2.2013.3187 ◽

2013 ◽

Vol 2 (2) ◽

pp. 133

Author(s):

Novvria Sagita ◽

As'ari . ◽

Wandayantolis .

Keyword(s):

Fourier Transform ◽

Spatial Distribution ◽

Spectral Density ◽

Fast Fourier Transform ◽

Research Use ◽

Distribution Map ◽

North Sulawesi ◽

Rainfall Patterns ◽

Spatial Distribution Map

Penelitian ini mengkaji lebih dalam perbedaaan pola curah hujan di Sulawesi Utara. Penelitian menggunakan data 12 stasiun atau pos pengamatan curah hujan di Sulawesi Utara dengan menggunakan teknik Fast Fourier Transform (FFT). Tujuan penelitian ini adalah membuat peta distribusi spasial periodisitas spektral curah hujan di wilayah Sulawesi Utara, sehingga dapat dianalisis fenomena cuaca yang mempengaruhi curah hujan di beberapa wilayah di Sulawesi Utara. Hasil penelitian ini menunjukkan bahwa Sulawesi Utara diklasifikasikan menjadi 2 tipe periodisitas curah hujan yang memiliki kekuatan kerapatan spektral tertinggi dengan periode 36 dasarian dan periode 18 dasarian. Sulawesi Utara juga diklasifikasikan menjadi 5 tipe periodisitas curah hujan yang memiliki kekuatan kerapatan spektral tertinggi ke dua dengan periode 3-11 dasarian, periode 18 dasarian, periode 36 dasarian, periode 60-110 dasarian dan periode 359 dasarian.This research examines more deeply the differences in rainfall patterns in Northern Sulawesi. This research use the data from 12 stations or rainfall observation posts in North Sulawesi by using the technique of Fast Fourier Transform (FFT). The purpose of this research is to create a spatial distribution map of rainfall spectral periodicity in North Sulawesi in order to analyze weather phenomena that affect rainfall in some areas in North Sulawesi. Based on the results of this study, North Sulawesi is classified into 2 types of rainfall periodicity having the highest spectral density power with the period of 36 ten-days (dasarian) and the period of 18 ten-days. North Sulawesi is also classified into 5 types of rainfall periodicity having the second highest spectral density power with the period of 3-11 ten-days, the period of 18 ten-days, the period of 36 ten-days, the period of 60-110 ten-days and the period of 359 ten-days.

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Study of soil erosion risks using RUSLE Model and remote sensing: case of the Bouregreg watershed (Morocco)

Proceedings of the International Association of Hydrological Sciences ◽

10.5194/piahs-383-159-2020 ◽

2020 ◽

Vol 383 ◽

pp. 159-162

Author(s):

Fatima Hara ◽

Mohammed Achab ◽

Anas Emran ◽

Gil Mahe

Keyword(s):

High Risk ◽

Soil Erosion ◽

Water Erosion ◽

Distribution Map ◽

Average Annual Rate ◽

The North ◽

Spatial Distribution Map ◽

North Western ◽

Very High ◽

Semi Arid

Abstract. The Bouregreg watershed is located to the north-western center of Morocco, characterized by a semi-arid climate. It covers a total area of approximately 10 000 km2. This basin is a very sensitive area to water erosion. This causes the degradation of its vegetation cover and its land. The most sensitive and poorly protected soils erode much more easily and lose their fertility.The objective of this work is to quantify soil losses by water erosion in the Bouregreg watershed using the Revised Universal Loss Equation (RUSLE) and Geographic Information Systems. The average annual rate of soil erosion in the Bouregreg watrershed are estimated at 20 t ha−1 yr−1. The spatial distribution map of soil erosion show that 71 % of the total area has low risk of soil erosion (<3 t ha−1 yr−1), while 28 % of the study area shows moderate to high risk of erosion (20–60 t ha−1 yr−1). Areas of very high risk of erosion are also present in some sectors of the watershed covering 1 % of the total surface.

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Measuring And Mapping The State Of Food Insecurity In Rajasthan, India

GEOGRAPHY ENVIRONMENT SUSTAINABILITY ◽

10.24057/2071-9388-2020-67 ◽

2021 ◽

Vol 14 (1) ◽

pp. 33-40

Author(s):

Rajput Swati ◽

Arora Kavita

Keyword(s):

Spatial Distribution ◽

Food Security ◽

Food Insecurity ◽

Four Dimensions ◽

Multiple Factors ◽

Global Issue ◽

The Government ◽

High Level ◽

The Relationship ◽

Very High

Food insecurity is a global issue that persists at various scales and intensity. It is linked to irregularity or uncertainty of food, water and fuel and can develop under the influence of multiple factors. Food availability, accessibility, consumption and stability are the four broad dimensions of food security. This paper analyses the relationship between these four dimensions and food insecurity for 33 districts in Rajasthan, India, using the data collected from the published documents, periodicals and websites of the government or other authentic sources. To analyse the link between these four dimensions, several indicators were taken into consideration. The collected data was used to rank the districts based on their level of food insecurity. Thus, the results include categorization of the districts into four zones based on the values of the variables. The results are presented through maps, which show the spatial distribution of food insecurity. It can be concluded, that the districts of Banswara, Dungarpur, Udaipur, Bharatpur, Rajsamand, Dhaulpur and Jalore have a very high level of food insecurity.

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Distribution of PM2.5 Air Pollution in Mexico City: Spatial Analysis with Land-Use Regression Model

Applied Sciences ◽

10.3390/app9142936 ◽

2019 ◽

Vol 9 (14) ◽

pp. 2936 ◽

Cited By ~ 3

Author(s):

Israel Hinojosa-Baliño ◽

Oscar Infante-Vázquez ◽

Maite Vallejo

Keyword(s):

Land Use ◽

Air Pollution ◽

Spatial Distribution ◽

Spatial Analysis ◽

Mexico City ◽

Land Use Regression ◽

Personal Exposures ◽

High Concentrations ◽

Spatial Distribution Map ◽

Very High

In this study, the spatial distribution of PM2.5 air pollution in Mexico City from 37 personal exposures was modeled. Meteorological, demographic, geographic, and social data were also included. Geographic information systems (GIS), spatial analysis, and Land-Use Regression (LUR) were used to generate the final predictive model and the spatial distribution map which revealed two areas with very high concentrations (up to 109.3 µg/m3) and two more with lower concentrations (between 72 to 86.5 µg/m3) (p < 0.05). These results illustrate an overview trend of PM2.5 in relation to human activity during the studied periods in Mexico City and show a general approach to understanding the spatial variability of PM2.5.

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A new spatial distribution map ofδ18O in Antarctic surface snow

Geophysical Research Letters ◽

10.1029/2008gl036939 ◽

2009 ◽

Vol 36 (6) ◽

Cited By ~ 7

Author(s):

Yetang Wang ◽

Shugui Hou ◽

Valérie Masson-Delmotte ◽

Jean Jouzel

Keyword(s):

Spatial Distribution ◽

Distribution Map ◽

Surface Snow ◽

Spatial Distribution Map

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Study on the Spatial Distribution of Gansu Longshen Cult in Qing Dynasty Based on ArcGIS

E3S Web of Conferences ◽

10.1051/e3sconf/202129003023 ◽

2021 ◽

Vol 290 ◽

pp. 03023

Author(s):

Zhang keze

Keyword(s):

Spatial Distribution ◽

Qing Dynasty ◽

Traditional Society ◽

Distribution Map ◽

The Times ◽

Spatial Distribution Map

Influenced by the limitations of the times, the agricultural belief and sacrificial system are developed and widely used in the traditional society of China, and the Longshen cult is a typical one. Taking the Gansu Longshen cult in Qing Dynasty as a case, this paper considered that the Longshen temple throughout Gansu are mainly the result of the correspondence between the rain function of Longshen and the characteristics of climate drought. Based on the statistics of the number of Longshen temple, the spatial distribution map of Gansu Longshen cult in Qing Dynasty was drawn by ArcGIS software.

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An analysis of the causes and consequences of firefighters’ accidents at work in the State Fire Service in 2010 – 2016

Occupational Safety – Science and Practice ◽

10.5604/01.3001.0012.1739 ◽

2018 ◽

Vol 562 (7) ◽

pp. 16-20

Author(s):

Dominik Grzybowski ◽

Magdalena Młynarczyk

Keyword(s):

Fire Service ◽

The State ◽

Wide Range ◽

High Level ◽

Very High ◽

Level Of Risk

The wide range of tasks performed by firefighters of the State Fire Service – and the multitude of risks they are exposed to – have contributed to qualifying this profession as carrying a very high level of risk. The article analyzes the causes and effects of firefighters’ accidents in the State Fire Service in 2010 – 2016.

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Impacts of culture-wise shrimp farming activities on hydrogeochemistry: a case study from Chidambaram taluk, Cuddalore district, Tamil Nadu, India

Applied Water Science ◽

10.1007/s13201-019-1097-3 ◽

2019 ◽

Vol 10 (1) ◽

Author(s):

Gangadharan Rajendran ◽

Nila Rekha Peter

Keyword(s):

Spatial Distribution ◽

Ion Exchange ◽

Tamil Nadu ◽

Shrimp Farming ◽

Distribution Map ◽

Exchange Reactions ◽

Farming Area ◽

Reverse Ion Exchange ◽

Shrimp Farms ◽

Spatial Distribution Map

AbstractShrimp farming is one of the most important aquaculture practices in terms of area, production, employment and foreign exchange generation in India. In recent years, the growth and intensification of shrimp farms in the study area have been explosive, and setting up of new shrimp farms along the coastal areas has also become a matter of apprehension among the environmentalists. An extensive survey made by environmentalists elsewhere shows mixed opinion, but ascertains the real scenario as facts. A total of about 46 groundwater samples were collected in five phases: pre-culture, summer culture, immediately after summer harvest (IASH), winter culture and immediately after winter culture, respectively. The results revealed that the high value of TDS, Na, Cl and Br is observed in IASH, and also, the spatial distribution map confirmed that higher concentration is observed near to the creek and sea. Moreover, the abundance of these ions is in the following order: Na > Ca > Mg > k and Cl > HCO3 > SO4 > CO3 > NO3 > Br for different culture periods, respectively. Piper diagram depicts that the groundwater was controlled by ion exchange reactions. Further, Chadha’s classification revealed that the reverse ion exchange was the dominated feature, and it is supported by various ionic indices such as Na/Cl versus EC, (Ca + Mg) versus (SO4 + HCO3), (Na–Cl) versus (Ca + Mg–HCO3–SO4), (Ca + Mg) versus Cl and Na/Cl versus Cl, respectively. The result of factor analysis shows that most of the variations are elucidated by the seawater intrusion, rock–water interactions and anthropogenic activities during different culture periods. The spatial distribution map of factor scores clearly delineates that the positive values are observed near to the creek and sea and in that, shrimp farming area is not predominated. R-mode cluster analysis shows that groundwater quality does not vary extensively as a function of culture periods. Moreover, Q-mode classification consists of two clusters: the first cluster has a high saline water concentration comprising samples location near to the creek and sea. The second cluster mainly depends upon rock–water interactions and the majority of shrimp farming area are grouped under these categories. The above statements clearly indicate that groundwater parameters mainly depend upon the geological process and that shrimp farming cannot be targeted as the root cause for groundwater salinization.

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