Natural Disasters Deaths

People killed in natural disasters by country by year

About this dataset

How much do natural disasters cost us? In lives, in dollars, in infrastructure? This dataset attempts to answer those questions, tracking the death toll and damage cost of major natural disasters since 1985. Disasters included are storms ( hurricanes, typhoons, and cyclones ), floods, earthquakes, droughts, wildfires, and extreme temperatures

How to use the dataset

This dataset contains information on natural disasters that have occurred around the world from 1900 to 2017. The data includes the date of the disaster, the location, the type of disaster, the number of people killed, and the estimated cost in US dollars

Research Ideas

• An all-in-one disaster map displaying all recorded natural disasters dating back to 1900.
• Natural disaster hotspots - where do natural disasters most commonly occur and kill the most people?
• A live map tracking current natural disasters around the world

Acknowledgements

License

See the dataset description for more information.

The EM-DAT Public Table is a flat representation of EM-DAT data in a single downloadable table. Most impact variables are part of the public table (see Impact Variables). The public table provides a flat view of the general structure in which each record (row) corresponds to a disaster impacting a country.

I used pivot tables in combination with a heat map to quickly show the severity (by deaths) of each type of disaster, by region as a drop down, each year. https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F21036995%2F9a85181a2764627469832038bdbac6da%2FEM_Data.png?generation=1723575827178988&alt=media" alt="">

Data Dictionary https://doc.emdat.be/docs/data-structure-and-content/emdat-public-table/

License information: UCLouvain 2023

This Database License Agreement (the Agreement) is made between yourself (the Licensee) and Université catholique de Louvain (UCLouvain), a Belgian University with its registered office located at Place de l’Université, 1, B-1348 Louvain-la-Neuve, Belgium, acting through its Research Group “Center for Research on the Epidemiology of Disasters” or CRED (the Licensor).

WHEREAS the Licensor has developed the EM-DAT database (hereinafter the Database) made available on the internet subject to its conditions of use;

WHEREAS the Database aims at providing an objective basis for impact and vulnerability assessment and rational decision-making in disaster situations by collecting, organizing, and giving access to validated data on the human impact of disasters (such as the number of people killed, injured, or affected), and the disaster-related economic damage estimates;

The Licensor wishes to lay down the conditions enabling the Licensee to use the Database for Commercial Purposes.

Source: The Emergency Events Database (EM-DAT) , Centre for Research on the Epidemiology of Disasters (CRED) / Université catholique de Louvain (UCLouvain), Brussels, Belgium – www.emdat.be.Category: Climate and WeatherData series: Climate related disasters frequency, Number of Disasters: TOTAL  Climate related disasters frequency, Number of Disasters: Drought  Climate related disasters frequency, Number of Disasters: Extreme temperature  Climate related disasters frequency, Number of Disasters: Flood  Climate related disasters frequency, Number of Disasters: Landslide  Climate related disasters frequency, Number of Disasters: Storm  Climate related disasters frequency, Number of Disasters: Wildfire Climate related disasters frequency, People Affected: Drought  Climate related disasters frequency, People Affected: Extreme temperature  Climate related disasters frequency, People Affected: Flood  Climate related disasters frequency, People Affected: Landslide  Climate related disasters frequency, People Affected: Storm  Climate related disasters frequency, People Affected: Wildfire Climate related disasters frequency, People Affected: TOTAL  Disaster IntensityMetadata:EM-DAT: The International Disasters Database - Centre for Research on the Epidemiology of Disasters (CRED), part of the University of Louvain (UCLouvain) www.emdat.be, Brussels, Belgium. Only climate related disasters (Wildfire, Storm, Landslide, Flood, Extreme Temperature, and Drought) are covered. See the CID Glossary for the definitions. EM-DAT records country level human and economic losses for disasters with at least one of the following criteria: i.          Killed ten (10) or more people  ii.         Affected hundred (100) or more people  iii.        Led to declaration of a state of emergency iv.        Led to call for international assistance   The reported total number of deaths “Total Deaths” includes confirmed fatalities directly imputed to the disaster plus missing people whose whereabouts since the disaster are unknown and so they are presumed dead based on official figures. “People Affected” is the total of injured, affected, and homeless people. Injured includes the number of people with physical injuries, trauma, or illness requiring immediate medical assistance due to the disaster. Affected includes the number of people requiring immediate assistance due to the disaster. Homeless includes the number of people requiring shelter due to their house being destroyed or heavily damaged during the disaster. Disaster intensity is calculated by summing “Total Deaths” and 30% of the “People Affected”, and then dividing the result by the total population. For each disaster and its corresponding sources, the population referred to in these statistics and the apportionment between injured, affected, homeless, and the total is checked by CRED staff members. Nonetheless, it is important to note that these are estimates based on certain assumptions, which have their limitations. For details on the criteria and underlying assumptions, please visit https://doc.emdat.be/docs/data-structure-and-content/impact-variables/human/. Methodology:Global climate related disasters are stacked to show the trends in climate related physical risk factors.

Number of people killed in natural disasters disaggregated by country and year

Context

Extracted from this paper: Neumayer, E., & Plümper, T. (2007). The gendered nature of natural disasters: The impact of catastrophic events on the gender gap in life expectancy, 1981–2002. Annals of the Association of American Geographers, 97(3), 551-566. https://doi.org/10.1111/j.1467-8306.2007.00563.x

from the paper: "To be recorded in the database, an event must fulfill at least one of the following conditions: (a) ten or more people reported as killed; (b) 100 people reported as affected; (c) a state of emergency has been declared; or (d) the country has issued a call for international assistance."

"Most natural disasters cost few if any lives, but the three most severe disasters—the droughts in Ethiopia and Sudan in 1984 and the flood in Bangladesh in 1991—account for almost half of all fatalities in our sample."

Content of dataset

Types of natural disasters Number of events Number of death and people affected for each natural disaster

Inspiration

We still don't have any comprehensive picture of threats to human species. If you know any similar dataset, please leave a comment.

Series Name: Number of people whose destroyed dwellings were attributed to disasters (number)Series Code: VC_DSR_PDYNRelease Version: 2021.Q2.G.03 This dataset is part of the Global SDG Indicator Database compiled through the UN System in preparation for the Secretary-General's annual report on Progress towards the Sustainable Development Goals.Indicator 13.1.1: Number of deaths, missing persons and directly affected persons attributed to disasters per 100,000 populationTarget 13.1: Strengthen resilience and adaptive capacity to climate-related hazards and natural disasters in all countriesGoal 13: Take urgent action to combat climate change and its impactsFor more information on the compilation methodology of this dataset, see https://unstats.un.org/sdgs/metadata/

Series Name: Number of people whose livelihoods were disrupted or destroyed attributed to disasters (number)Series Code: VC_DSR_PDLNRelease Version: 2021.Q2.G.03 This dataset is part of the Global SDG Indicator Database compiled through the UN System in preparation for the Secretary-General's annual report on Progress towards the Sustainable Development Goals.Indicator 13.1.1: Number of deaths, missing persons and directly affected persons attributed to disasters per 100,000 populationTarget 13.1: Strengthen resilience and adaptive capacity to climate-related hazards and natural disasters in all countriesGoal 13: Take urgent action to combat climate change and its impactsFor more information on the compilation methodology of this dataset, see https://unstats.un.org/sdgs/metadata/

this graph was created in OurDataWorld:

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F16731800%2F86a1028443da66dd072f82cf0c281931%2Fgraph1.png?generation=1716244016015643&alt=media" alt=""> https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F16731800%2F490911c5e52c7b49787de611e528b157%2Fgraph2.png?generation=1716244022139349&alt=media" alt=""> https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F16731800%2Fd6e83eb9faaa15a43580fd34fe84bfd7%2Fgraph3.png?generation=1716244027294399&alt=media" alt="">

In 1970, more than 300,000 people died when a strong cyclone hit the coast of Bangladesh.1 In 1985, another storm caused 15,000 deaths. Just six years later, another killed 140,000.

Fast-forward to 2020. Bangladesh was hit by cyclone Amphan, one of the strongest storms on record in the Bay of Bengal. The death toll was 26 — barely visible on the chart below, compared to these very deadly disasters.

That’s 26 too many deaths, and the cyclone also caused huge amounts of damage: millions of people were displaced, and there were large economic losses. But tens — possibly hundreds — of thousands of lives were saved through early warnings, evacuations, and increased resilience. People in Bangladesh are much better protected from disasters than they were a few decades ago.

This development is part of a longer-term and widespread success in reducing humanity’s vulnerability to storms, floods, earthquakes, and other hazards.

Bangladesh is not an isolated example. We can observe long-term improvements in the world's resilience.

Here, I will look at data published by the International Disaster Database, EM-DAT, which stretches back to 1900. In the chart below, I’ve shown the number of deaths from disasters, given as the decadal average. This is helpful as there is a lot of volatility in disasters from year to year.2 You can also explore this data annually.

The number of people killed in disasters has fallen a lot over the last century. That’s despite there being four times as many people. That means the decline in death rates has been even more dramatic.

Series Name: Number of deaths due to disaster (number)Series Code: VC_DSR_MORTRelease Version: 2020.Q2.G.03 This dataset is the part of the Global SDG Indicator Database compiled through the UN System in preparation for the Secretary-General's annual report on Progress towards the Sustainable Development Goals.Indicator 11.5.1: Number of deaths, missing persons and directly affected persons attributed to disasters per 100,000 populationTarget 11.5: By 2030, significantly reduce the number of deaths and the number of people affected and substantially decrease the direct economic losses relative to global gross domestic product caused by disasters, including water-related disasters, with a focus on protecting the poor and people in vulnerable situationsGoal 11: Make cities and human settlements inclusive, safe, resilient and sustainableFor more information on the compilation methodology of this dataset, see https://unstats.un.org/sdgs/metadata/

Context

Disasters include all geophysical, meteorological and climate events including earthquakes, volcanic activity, landslides, drought, wildfires, storms, and flooding. Decadal figures are measured as the annual average over the subsequent ten-year period.

Content

Thanks to Our World in Data, you can explore death from natural disasters by country and by date.

Acknowledgements

https://www.acacamps.org/sites/default/files/resource_library_images/naturaldisaster4.jpg" alt="Natural Disasters">

Inspiration

List of variables for inspiration: Number of deaths from drought Number of people injured from drought Number of people affected from drought Number of people left homeless from drought Number of total people affected by drought Reconstruction costs from drought Insured damages against drought Total economic damages from drought Death rates from drought Injury rates from drought Number of people affected by drought per 100,000 Homelessness rate from drought Total number of people affected by drought per 100,000 Number of deaths from earthquakes Number of people injured from earthquakes Number of people affected by earthquakes Number of people left homeless from earthquakes Number of total people affected by earthquakes Reconstruction costs from earthquakes Insured damages against earthquakes Total economic damages from earthquakes Death rates from earthquakes Injury rates from earthquakes Number of people affected by earthquakes per 100,000 Homelessness rate from earthquakes Total number of people affected by earthquakes per 100,000 Number of deaths from disasters Number of people injured from disasters Number of people affected by disasters Number of people left homeless from disasters Number of total people affected by disasters Reconstruction costs from disasters Insured damages against disasters Total economic damages from disasters Death rates from disasters Injury rates from disasters Number of people affected by disasters per 100,000 Homelessness rate from disasters Total number of people affected by disasters per 100,000 Number of deaths from volcanic activity Number of people injured from volcanic activity Number of people affected by volcanic activity Number of people left homeless from volcanic activity Number of total people affected by volcanic activity Reconstruction costs from volcanic activity Insured damages against volcanic activity Total economic damages from volcanic activity Death rates from volcanic activity Injury rates from volcanic activity Number of people affected by volcanic activity per 100,000 Homelessness rate from volcanic activity Total number of people affected by volcanic activity per 100,000 Number of deaths from floods Number of people injured from floods Number of people affected by floods Number of people left homeless from floods Number of total people affected by floods Reconstruction costs from floods Insured damages against floods Total economic damages from floods Death rates from floods Injury rates from floods Number of people affected by floods per 100,000 Homelessness rate from floods Total number of people affected by floods per 100,000 Number of deaths from mass movements Number of people injured from mass movements Number of people affected by mass movements Number of people left homeless from mass movements Number of total people affected by mass movements Reconstruction costs from mass movements Insured damages against mass movements Total economic damages from mass movements Death rates from mass movements Injury rates from mass movements Number of people affected by mass movements per 100,000 Homelessness rate from mass movements Total number of people affected by mass movements per 100,000 Number of deaths from storms Number of people injured from storms Number of people affected by storms Number of people left homeless from storms Number of total people affected by storms Reconstruction costs from storms Insured damages against storms Total economic damages from storms Death rates from storms Injury rates from storms Number of people affected by storms per 100,000 Homelessness rate from storms Total number of people affected by storms per 100,000 Number of deaths from landslides Number of people injured from landslides Number of people affected by landslides Number of people left homeless from landslides Number of total people affected by landslides Reconstruction costs from landslides Insured damages against landslides Total economic damages from landslides Death rates from landslides Injury rates from landslides Number of people affected by landslides per 100,000 Homelessness rate from landslides Total number of people affected by landslides per 100,000 Number of deaths from fog Number of people injured from fog Number of people affected by fog Number of people left homel...

Introduction

Vietnam’s geographic location and topography make it particularly susceptible to a wide range of disasters, both natural and technological.

This dataset provides data as uploaded, on the occurrence and impacts of mass disasters in Vietnam from 1953 to 2024. This includes both natural (biological, climatological, extra-terrestrial, geophysical, hydrological, meteorological), and technological (industrial accident) disasters. Data was extracted from The International Disaster Database (EM-DAT), maintained by the Centre for Research on the Epidemiology of Disasters (CRED), published by Open Development Vietnam.

It documents natural and human-related disasters in Vietnam from 1953 onward, with key fields related to: - Disaster types and sub types (e.g., storm, flood, drought, epidemic). - Start and end dates. - Human impact (deaths, injuries, people affected). - Economic damage (where data is available). - Geo-location and metadata (latitude/longitude, region, event name).

How Vietnam has changed since 1953, with a focus on climate change-driven disasters:

• Storms (including tropical cyclones).
• Floods.
• Droughts.

We explore long-term trends, decadal comparisons, regional distribution, and statistical correlations to understand Vietnam’s evolving climate vulnerability. The aim is to uncover data-driven insights that inform climate adaptation, disaster risk management, and sustainable development planning.

Recommended Reading

Saline Intrusion in the Mekong Delta (2021-2022). Part 1: The devastating effects of climate change; Mekong and Bengal Deltas. link - Kaggle

Rainfall & Temperature: Vietnam from 1901 to 2020. Part 3: The devastating effects of climate change; monsoon pattern changes. link - Kaggle

Trend Overview by Decade: vietnam_climate_disaster_trend_by_decade.csv

A markdown document with the R code for all the below visualisations. link

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Bar Chart: - Description: - This chart presents normalised values of four metrics; Event Count, Total Affected, Total Damage Adjusted, and Total Deaths. Aggregated by decade from the 1950's to the 2020's. The normalisation allows comparison across different scales.
- Observations: - The 2000's show the highest Event Count, indicating a peak in disaster frequency. - The 1960's had a significant Total Death component. In November 1964, the quick succession of three typhoons (Iris, Joan, and Kate), caused widespread flooding in Vietnam causing 7,000 deaths, as confirmed by dataset analysis. link - Wikipedia: November 1964 Vietnam floods - Total Affected and Total Damage Adjusted peak in the 1990's and 2000's, suggesting increased vulnerability or severity during these periods. - Insights: - This visualisation highlights temporal shifts in disaster impacts, with the 1960's notable for high mortality and the 2000's for frequency, reflecting historical disaster patterns. However, the 1964 Pacific typhoon season was the most active tropical cyclone season recorded globally, with a total of 39 tropical storms forming. It had no official bounds; it ran year-round in 1964, but most tropical cyclones tend to form in the northwestern Pacific Ocean between June and December. The unprecedented and extended tropical storm season of 1964, accounted for the large amount of deaths by disasters, during the 1960's in Vietnam.

*2020s data is partial

Summary

• Rising Disaster Frequency:
  • Climate-related disasters have increased sharply since the 1980's, particularly storms and floods.
  • From just 2 recorded events in the 195...

This dataset "Global hotspots of climate related disasters" shows the number of people impacted by climate-related disasters recorded in the EM-DAT database between 2000 and 2020. This dataset was used to prepare the maps and the analysis of the paper Donatti C.I., Nicholas K., Fedele G., Delforge D., Speybroeck N., Moraga P., Blatter J., Below R., Zvoleff A. 2024. Global hotspots of climate-related disasters. International Journal of Disaster Risk Reduction. https://doi.org/10.1016/j.ijdrr.2024.104488. This dataset includes information on people impacted by Drought, tropical cyclones, flash flood, riverine flood, forest fire, land fire, heat wave, landslide and mudslide. Data on coastal flood was not included because the database only had recordings until 2013. Data on disaster sub-types “landslides” and “mudslides” as presented in the EM-DAT were further combined as one single climate-related disaster (“land and mudslides”) for the analyses. Likewise, data on disaster sub-types “forest fire” and “land fire” were further combined as one climate-related disaster (“wildfire”). The data was accessed directly from the EM-DAT database and then summarized as show in the dataset. We used this database, downloaded on June 2nd 2021, to access data on “total affected” people and the “total deaths” per disaster event impacting a country (i.e., an entry in the EM-DAT), which were combined in this study to create the variable “total people impacted”. In the EM-DAT database, “total affected” represents the sum of people “injured,” “affected,” and “homeless” resulting from a particular event. “Injured” were considered those that have suffered from physical injuries, trauma, or an illness requiring immediate medical assistance, including people hospitalized, as a direct result of a disaster, “affected” were considered people requiring immediate assistance during an emergency and “homeless” were considered those whose homes were destroyed or heavily damaged and therefore needed shelter after an event. “Total deaths” include people that have died or were considered missing, those whose whereabouts since the disaster were unknown and presumed dead based on official figures. More details can be found under “documentation, data structure and content description” at emdat.be. In the dataset, "ADM-CODE" refers to the code used to identify each administrative area, which refers to the code of FAO's Global Administrative Unit Layer, GAUL.

Disasters deeply impact the health of the affected population and the economy of a country. The health burden of disasters in Brazil is underestimated and more studies are needed to underpin policies and actions for disaster risk reduction. This study analyzes and describes disasters that occurred in Brazil from 2013 to 2021. The Integrated Disaster Information System (S2iD) was accessed to obtain demographic data, disaster data according to Brazilian Classification and Codification of Disasters (COBRADE), and health outcome data (number of dead, injured, sick, unsheltered, displaced, and missing individuals and other outcomes). Database preparation and analysis were performed in Tableau. In total, 98.62% (50,481) of the disasters registered in Brazil from 2013 to 2021 are natural, with a significant increase in 2020 and 2021 due to the COVID-19 pandemic, a biological disaster. This disaster group also caused the highest number of deaths (321,111), as well as injured (208,720) and sick (7,041,099) people. By analyzing data for each geographic region, we observed differences regarding disasters frequency and their health outcomes. In Brazil, climatological disasters are the most frequent (23,452 events) and occur mainly in the Northeast region. Geological disasters have the highest lethality, which are more common in the Southeast; however, the most common disasters in the South and Southeast are those of the meteorological and hydrological groups. Therefore, since the greatest health outcomes are associated with disasters predicted in time and space, public policies for the prevention and management of disasters can reduce the impacts of these events.

Data published by Our World in Data based on EM-DAT, CRED / UCLouvain, Brussels, Belgium – www.emdat.be (D. Guha-Sapir)

Variable time span 1900 – 2010

This dataset has been calculated and compiled by Our World in Data based on raw disaster data published by EM-DAT, CRED / UCLouvain, Brussels, Belgium – www.emdat.be (D. Guha-Sapir). EM-DAT publishes comprehensive, global data on each individual disaster event – estimating the number of deaths; people affected; and economic damages, from UN reports; government records; expert opinion; and additional sources. Our World in Data has calculated annual aggregates, and decadal averages, for each country based on this raw event-by-event dataset. Decadal figures are measured as the annual average over the subsequent ten-year period. This means figures for ‘1900’ represent the average from 1900 to 1909; ‘1910’ is the average from 1910 to 1919 etc. We have calculated per capita rates using population figures from Gapminder (gapminder.org) and the UN World Population Prospects (https://population.un.org/wpp/). Economic damages data is provided by EM-DAT in concurrent US$. We have calculated this as a share of gross domestic product (GDP) using the World Bank’s GDP figures (also in current US$) (https://data.worldbank.org/indicator). Definitions of specific metrics are as follows: – ‘All disasters’ includes all geophysical, meteorological, and climate events including earthquakes, volcanic activity, landslides, drought, wildfires, storms, and flooding. – People affected are those requiring immediate assistance during an emergency situation. – The total number of people affected is the sum of injured, affected, and homeless.Link www.emdat.be

The data set analyzes the spatial and temporal distribution, impact and loss of typical global flood disasters from 2018 to 2019. In 2018, there were 109 flood disasters in the world, with a death toll of 1995. The total number of people affected was 12.62 million. The direct economic loss was about 4.5 billion US dollars, which was at a low level in the past 30 years. The number of global flood incidents in 2018 was higher in the first half of the year than in the second half of the year, and the frequency of occurrence was higher from May to July. Therefore, based on three typical disaster events such as the hurricane flood in Florence in the United States in 2018, the flooding of the Niger River in Nigeria in 2018, and the Shouguang flood in Shandong Province in 2018, the disaster background, hazard factors, and disaster situation were analyzed. .

"The Canadian Disaster Database (CDD) contains detailed disaster information on more than 1000 natural, technological and conflict events (excluding war) that have happened since 1900 at home or abroad and that have directly affected Canadians. The CDD tracks ""significant disaster events"" which conform to the Emergency Management Framework for Canada definition of a ""disaster"" and meet one or more of the following criteria: •10 or more people killed •100 or more people affected/injured/infected/evacuated or homeless •an appeal for national/international assistance •historical significance •significant damage/interruption of normal processes such that the community affected cannot recover on its own The database describes where and when a disaster occurred, the number of injuries, evacuations, and fatalities, as well as a rough estimate of the costs. As much as possible, the CDD contains primary data that is valid, current and supported by reliable and traceable sources, including federal institutions, provincial/territorial governments, non-governmental organizations and media sources. Data is updated and reviewed on a semi-annual basis"

Romania, an eastern European country, is severely affected by a variety of natural hazards. These include frequent earthquakes, floods, landslides, soil erosion, and drought all of which have major social and economic impacts. Thus, there is a long tradition of study of these hazards by scientific researchers in Romania. This set of slides includes examples of landslides, rockfalls,sheet erosion, and mudflows. Romania has an area of 237,500 km2 and a great variety of geologic regions. Two-thirds of the country consists of hills, tablelands, and mountains of the Carpathian arch. The climate is dominantly temperate-continental and vegetation and soils vary widely with altitude. Altitude ranges from sea level to 2,544 meters above sea level at the highest point of the Romanian Carpathians. Romania's population in 1992 was 22.76 million inhabitants, or an average density of 95.8 people per square kilometer. The Vrancea Seismic Region of the southeastern part of the Carpathian Mountains is the most active subcrustal earthquake province of Europe. The region is characterized by high seismicity, with about three major earthquakes greater than magnitude (M) 7.0 occurring every century. The best studied earthquake of recent times occurred March 4, 1977, and had a magnitude of 7.2. This earthquake caused the death of 1,570 people, and destroyed 33,000 buildings. In addition to earthquakes, torrential rains are responsible for catastrophic floods, massive landslides, and major soil erosion. Mass movements are a significant hazard in the hilly and mountainous regions, particularly those underlain by flysch deposits. These deposits are complexes of folded and faulted sedimentary rocks containing marls, clays, shales, sandstones, and conglomerates. The distribution of mass movements in these deposits is controlled by various climatic, tectonic, and lithologic factors influenced by different land-management practices. There are significant regional differences among types of mass movements, the quantities of materials delivered from the slopes into adjacent stream channels, and risks to various human activities. In the Subcarpathians, formed predominantly of folded and faulted molasse deposits, slopes may be highly unstable. The instability is most frequently manifested by shallow (sheet) slides, landslides of medium depth, and mudflows typically 300-700 meters in length. The areas most affected by these features lie within the Curvature Subcarpathians in the Vrancea Seismic Region. In the Eastern Carpathians, formed predominantly of Cretaceous and Paleocene flysch deposits, periglacial or immediate postglacial colluvial materials are major sources of mass movements. These deposits generally range from 10 to 30 meters in depth, and landslides within them arecommonly activated or reactivated by regional deepening of the valley network in the long term, or deforestation practices by people. Because oftheir association with stream valleys, these landslides often affect towns, communication lines, and roads, and may partially or totally block valleys when they move. In the Moldlavian Plateau, the areas most affected by landslides occur on slopes built up of alternations of marls and clays, with intercalations of conglomerates and sandstones. In the Transylvanian Plateau deep landslides called "glimee" are commonly triggered by heavy rains. In the alpine belt of the Carpathian mountains, the most common mass movements are rockfalls and rock avalanches. These processes are mostcommon in the crystalline rocks on the steep slopes of glacial cirques and valleys. Sheet and gully erosion affect most of the hilly and mountainous regions of Romania. Agricultural lands on slopes steeper than 5% represent 42% ofthese regions and contribute to the bulk of sheet and gully erosion. About 20% of the agricultural lands are affected by high to very high erosionrates of 8-16 T/HA/year; 19% are subject to more moderate rates of 2-8 T/HA/Year; and about 3% are classified as slightly eroded. Highest erosion risks occur in the Curvature Subcarpathians, the Getic Subcarpathians, the north of the Getic Plateau, the central part of the Moldavian Plateau, and the west of the Translvanian Plateau. In these regions, large areas are affected by gully erosion which contributes to making about 5,000 ha/year unfit for the cultivation of crops. There is a corresponding loss of 30 million tons of soil per year. Factors related to gully erosion include poorly consolidated rocks, intense rainfall, and poor land-use practices. Mud volcanoes occur along active fault lines in the Curvature Subcarpathians, and are related to groundwater circulation under pressure.Mud volcanoes commonly are activated and reactivated during strong earthquakes. The largest mud volcanoes are located in the Berca Anticline Depression, a region rich in oil deposits. Upward movement of ground waterand oil there formed large, circular mud volcano plateaus 60-70 meters high with diameters of 200-300 meters. Within these plateaus, there are active and extinct mud volcano cones about one to three meters high. Because of the unusual formations, the region is protected from development and is a preserve for some of Romania's spectacular natural features.

Whilst the number of people globally being killed from both disasters and conflicts has generally been falling over the past twenty years, the number of people actually affected by disasters has steadily been rising1. Available electronically Call Number: [EL] Physical Description: 3 Pages

📖 Description

This dataset contains detailed records of natural disasters in Indonesia from 2018 to 2024, based on official reports from BNPB (Badan Nasional Penanggulangan Bencana / Indonesia’s National Disaster Management Authority).

Indonesia is one of the most disaster-prone countries in the world due to its geographic location on the Pacific “Ring of Fire” and its tropical climate. Events such as floods, landslides, volcanic eruptions, earthquakes, and strong winds occur regularly, affecting communities across all provinces.

Each record in this dataset represents a single disaster event reported at the city (kabupaten/kota) level on a specific date, along with its human and infrastructure impacts. This dataset can be used for time-series analysis, geospatial mapping, disaster risk modeling, and policy research.

📊 Dataset Content

The dataset includes the following fields: - city_id → Official administrative code for the city/kabupaten. - date → Date of the disaster event (YYYY-MM-DD). - disaster_type → Type of disaster. - city → Name of the city/kabupaten affected. - province → Province of the affected city/kabupaten. - cause → Reported cause or trigger. - death → Number of fatalities. - missing_person → Number of people reported missing. - injured_person → Number of injured people. - damaged_house → Number of houses damaged. - damaged_facility → Number of damaged public facilities. - flooded_house → Number of houses flooded (specific to flood events).