Multidimensional Dataset Of Food Security And Nutrition In Cauca.
Description
A multidimensional dataset created for the department of Cauca based on public data sources is published. The dataset integrates the 4 FAO food security dimensions: physical availability of food, economic and physical access to food, food utilization, and the sustainability of the dimensions mentioned above. It also allows analysis of different variables such as nutritional, socioeconomic, climatic, sociodemographic, among others with statistical techniques or temporal analysis. The dataset can also be used for analysis and extraction of characteristics with computer vision techniques from satellite images, or multimodal machine learning with data of a different nature (images and tabular data). The dataset Contains the folders: - Multidimensional dataset of Cauca/: Here are the tabular data of the municipalities of the department of Cauca. The folder contains the files: 1. dictionary(English).xlsx: The dictionary of the static variables for each municipality of Cauca in english. 2. dictionary(Español): The dictionary of the static variables for each municipality of Cauca in spanish. 3. dictionary(English).xlsx: The dictionary of the static variables for each municipality of Cauca in english. 4. MultidimensionalDataset_AllMunicipalities.csv: Nutritional, climatic, sociodemographic, socioeconomic and agricultural data of the 42 municipalities of the department of Cauca, although with some null values due to the lack of data in nutrition surveys of some municipalities. - Satellite Images Popayán/: Here are the monthly Landsat 8 satellite images of the municipality of Popayán in Cauca. The folder contains the folders: 1. RGB/: Contains the RGB images of the municipality of Popayán in the department of Cauca. It contains RGB images of Popayán from April 2013 to December 2020 in a resolution of 15 m / px. The title of each image is image year_month.png. 1. 6 Band Images/: Contains images of Landsat 8 using bands 1 to 8 to generate images of the municipality of Popayán in the department of Cauca. It contains 6 band images in a tif format of Popayán from April 2013 to December 2020 in a resolution of 15 m / px. The title of each image is image year_month.tif.
Files
Steps to reproduce
1. Select the task to perform: - Nutrition time series (acute malnutrition in children under 5 years of age or death from malnutrition) - Climate analysis in time series (Temperature or Precipitation) - Agriculture, sociodemographic, socioeconomic or nutritional analysis. - Image tasks. 2. Download the dataset. - If you want to make an analysis of satellite images, you can download only the data of in 'Satellite Images Popayán/'. According to the bands you want to work with, you can download 3 band RGB images in 'RGB/' or 6 band images in '6 Band Images/'. - For other task you can Download: Multidimensional dataset of all municipalities in path: 'Multidimensional dataset of Cauca/MultidimensionalDataset_9Municipalities_clean.csv', or dataset for 9 municipalities in path: 'Multidimensional dataset of Cauca/MultidimensionalDataset_AllMunicipalities.csv'. 3. variable selection (for all except image analysis): - If you want to perform a Nutrition time series for the variable 'acute malnutrition in children under 5 years of age', you can select all variables with format cases_DesnutricionMenores5_YEAR_week_EPIWEEK. Where YEAR and EPIWEEK are an integer defining the date. - If you want to perform a Nutrition time series for the variable 'death from malnutrition', you can select all variables with format cases_MortalidadDesnutricion_YEAR_week_EPIWEEK. Where YEAR and EPIWEEK are an integer defining the date. - If you want to perform a Climate time series TASK for the variable 'temperature', you can select all variables with format TEMPERATURE_MONTH_YEAR. Where YEAR is an Integer between 12 and 18 indicating the yearn, and MONTH is a string indicating the month.-- If you want to perform a Climate time series TASK for the variable 'precipitation', you can select all variables with format PRECIPITATION_MONTH_YEAR. Where YEAR is an Integer between 12 and 18 indicating the yearn, and MONTH is a string indicating the month. - If you want to perform an agriculture, sociodemographic, socioeconomic or nutritional analysis, you should select the variables you want to use from the dictionary.