This table contains 2394 series, with data for years 1991 - 1991 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...), Population group (19 items: Entire cohort; Income adequacy quintile 1 (lowest);Income adequacy quintile 2;Income adequacy quintile 3 ...), Age (14 items: At 25 years; At 30 years; At 40 years; At 35 years ...), Sex (3 items: Both sexes; Females; Males ...), Characteristics (3 items: Life expectancy; High 95% confidence interval; life expectancy; Low 95% confidence interval; life expectancy ...).

Global human exposure to wildland fires dataset: 2002-2021

Seyd Teymoor Seydi¹, John T. Abatzoglou², Matthew W. Jones³, Mojtaba Sadegh^1,4

¹Department of Civil Engineering, Boise State University, Boise, ID, USA

²Management of Complex Systems Department, University of California, Merced, Merced, CA, USA

³Tyndall Centre for Climate Change Research, School of Environmental Sciences, University of East Anglia (UEA), Norwich, UK

⁴United Nations University Institute for Water, Environment and Health, Richmond Hills, ON, Canada

1. Dataset Overview

This dataset contains comprehensive information on global fire events from 2002 to 2021, including fire characteristics, environmental variables, land cover properties, and detailed population exposure estimates separated by age group and gender. The data is organized into two separate dataset series:

1. Fire Events Series (df_Fire_Events_2002 to df_Fire_Events_2021): Contains fire characteristics, environmental variables, land cover properties, and summary exposure information for each fire event. Each file includes global fire events for one year, as indicated in the file name.

2. Age Groups Series (df_Fire_Age_Groups_2002 to df_Fire_Age_Groups_2021): Contains detailed demographic breakdowns of populations exposed to individual fire events by age group and gender. Each file includes global fire events for one year, as indicated in the file name.

2. Data Structure

Each annual dataset contains the following information:

• Temporal Coverage: Individual years from 2002 to 2021 (20 datasets total x 2 [environmental variables and summary exposure + exposures broken down by age and gender structures])
• Spatial Coverage: Global
• Unit of Analysis: Individual fire events identified by unique fire_ID
• Fire Metrics: Location, size, duration, spread characteristics, active fire days, and fire radiative power
• Environmental Variables: Vegetation indices (EVI, NDVI) and land cover fractions
• Population Metrics: Total exposure and detailed breakdowns by 5-year age groups and gender
• Geographic Context: Country and continent information

Column Definitions

Fire Characteristics

• fire_ID: Unique identifier for each fire event
• Latitude: Latitude coordinate of fire ignition point (decimal degrees)
• Longitude: Longitude coordinate of fire ignition point (decimal degrees)
• size: Fire area
• perimeter: Fire perimeter length
• start_date: Fire start date
• duration: Fire duration (days)
• spread: Fire spread rate
• speed: Fire speed rate
• Active_Fire_Days: Number of active fire days in each pixel within fire polygon, averaged for each fire polygon (Source: MOD14A1)
• total_frp: Total fire radiative power summed from start to end date of fire, aggregated by sum for each fire polygon (Source: MOD14A1)

3. Geographic Information

• Country: Name of country where fire occurred
• Continent: Name of continent where fire occurred

4. Land Cover Characteristics (Source: MCD12Q1)

• Agriculture-Fraction: Fraction of agricultural land cover within fire polygon
• Urban-Fraction: Fraction of urban areas within fire polygon

5. Vegetation Indices (Source: MOD13A1)

• EVI: Enhanced Vegetation Index - maximum annual value for each pixel averaged across fire polygon
• NDVI: Normalized Difference Vegetation Index - maximum annual value for each pixel averaged across fire polygon

6. Population Exposure (Source: WorldPop)

• Exposure: Total population exposure to fire, aggregated by sum for each individual fire event using contemporary population data for each year
• Scenario-Exposure: Total population exposure to fire using constant 2002 population data across all years, with dynamic fire data for each year, aggregated by sum for each individual fire event. This is also referred to as counterfactual exposure.

6.1. Female Population Exposure (SUM_f_*)

• SUM_f_0: Number of females aged <1 year exposed to fire
• SUM_f_1: Number of females aged ≥1 to <5 years exposed to fire
• SUM_f_5: Number of females aged ≥5 to <10 years exposed to fire
• SUM_f_10: Number of females aged ≥10 to <15 years exposed to fire
• SUM_f_15: Number of females aged ≥15 to <20 years exposed to fire
• SUM_f_20: Number of females aged ≥20 to <25 years exposed to fire
• SUM_f_25: Number of females aged ≥25 to <30 years exposed to fire
• SUM_f_30: Number of females aged ≥30 to <35 years exposed to fire
• SUM_f_35: Number of females aged ≥35 to <40 years exposed to fire
• SUM_f_40: Number of females aged ≥40 to <45 years exposed to fire
• SUM_f_45: Number of females aged ≥45 to <50 years exposed to fire
• SUM_f_50: Number of females aged ≥50 to <55 years exposed to fire
• SUM_f_55: Number of females aged ≥55 to <60 years exposed to fire
• SUM_f_60: Number of females aged ≥60 to <65 years exposed to fire
• SUM_f_65: Number of females aged ≥65 to <70 years exposed to fire
• SUM_f_70: Number of females aged ≥70 to <75 years exposed to fire
• SUM_f_75: Number of females aged ≥75 to <80 years exposed to fire
• SUM_f_80: Number of females aged ≥80 years exposed to fire

6.2. Male Population Exposure (SUM_m_*)

• SUM_m_0: Number of males aged <1 year exposed to fire
• SUM_m_1: Number of males aged ≥1 to <5 years exposed to fire
• SUM_m_5: Number of males aged ≥5 to <10 years exposed to fire
• SUM_m_10: Number of males aged ≥10 to <15 years exposed to fire
• SUM_m_15: Number of males aged ≥15 to <20 years exposed to fire
• SUM_m_20: Number of males aged ≥20 to <25 years exposed to fire
• SUM_m_25: Number of males aged ≥25 to <30 years exposed to fire
• SUM_m_30: Number of males aged ≥30 to <35 years exposed to fire
• SUM_m_35: Number of males aged ≥35 to <40 years exposed to fire
• SUM_m_40: Number of males aged ≥40 to <45 years exposed to fire
• SUM_m_45: Number of males aged ≥45 to <50 years exposed to fire
• SUM_m_50: Number of males aged ≥50 to <55 years exposed to fire
• SUM_m_55: Number of males aged ≥55 to <60 years exposed to fire
• SUM_m_60: Number of males aged ≥60 to <65 years exposed to fire
• SUM_m_65: Number of males aged ≥65 to <70 years exposed to fire
• SUM_m_70: Number of males aged ≥70 to <75 years exposed to fire
• SUM_m_75: Number of males aged ≥75 to <80 years exposed to fire
• SUM_m_80: Number of males aged ≥80 years exposed to fire

7. Data Sources

• Population Data: WorldPop Project demographic datasets

o Source URL: https://hub.worldpop.org/project/categories?id=8

o Population estimates are provided in 5-year age groups by gender at high spatial resolution

• Land Cover Data: MODIS MCD12Q1 Land Cover Type product

o Used to calculate agricultural and urban land cover fractions within fire polygons

• Vegetation Indices: MODIS MOD13A1 Vegetation Indices product

o Used to derive maximum annual EVI and NDVI values, averaged across fire polygons

• Fire Activity Data: MODIS MOD14A1 Thermal Anomalies and Fire Daily product

o Used to calculate active fire days and total fire radiative power within fire polygons

• Fire Data: Global fire atlas is available at: https://doi.org/10.5281/zenodo.11400062" href="https://doi.org/10.5281/zenodo.11400062" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.11400062

8. Usage Notes

1. Exposure Definition: Exposure is defined as population within fire polygon boundaries
2. Exposure Scenarios:

o Exposure: Uses contemporary population data for each year, allowing analysis of changing demographics over time

o Scenario-Exposure: Uses constant 2002 population data across all years to isolate the effect of changing fire patterns while holding population constant

1. Age Group Structure: Age groups follow standard demographic categories with the first year of life separate (0)

Introduction

Welcome to the Native American Child Faces Dataset, meticulously curated to enhance face recognition models and support the development of advanced biometric identification systems, child identification models, and other facial recognition technologies.

Facial Image Data

This dataset comprises over 3,000 child image sets, divided into participant-wise sets with each set including:

Diversity and Representation

The dataset includes contributions from a diverse network of children across Native American countries:

Quality and Conditions

To ensure high utility and robustness, all images are captured under varying conditions:

Metadata

Each facial image set is accompanied by detailed metadata for each participant, including:

This metadata is essential for training models that can accurately recognize and identify children's faces across different demographics and conditions.

Usage and Applications

This facial image dataset is ideal for various applications in the field of computer vision, including but not limited to:

Secure and Ethical Collection

Updates and