Processed Data Assembly

Important

  • This section describes processed datasets that are used as inputs in Analysis and Results steps of the Argentina Transport Risk Analysis (ATRA)
  • The formats and attributes created in these datasets form the essential inputs for implementing the rest of the ATRA model
  • To implement the ATRA without any changes in existing codes, all data described here should be created and stored exactly as indicated below

Networks

  1. All finalised networks data are stored:
    • In the file path - /data/network/
    • As csv file with post-processed network nodes and edges
    • As Shapefiles with post-processed network nodes and edges
  2. All nodes have the following attributes:
    • node_id - String Node ID
    • geometry - Point geometry of node with projection ESPG:4326
    • Several other atttributes depending upon the specific transport sector
  3. Attributes only present in bridge nodes:
    • bridge_id - String Bridge ID
  4. All edges have the following attributes:
    • edge_id - String edge ID
    • from_node - String node ID that should be present in node_id column
    • to_node - String node ID that should be present in node_id column
    • geometry - LineString geometry of edge with projection ESPG:4326
    • length - Float estimated length in kilometers of edge
    • min_speed - Float estimated minimum speed in km/hr on edge
    • max_speed - Float estimated maximum speed in km/hr on edge
    • min_time - Float estimated minimum time of travel in hours on edge
    • max_time - Float estimated maximum time of travel in hours on edge
    • min_gcost - Float estimated minimum generalized cost in USD/ton on edge
    • max_gcost - Float estimated maximum generalized cost in USD/ton on edge
    • Several other atttributes depending upon the specific transport sector
  1. Attributes only present in province and national roads edges:
    • road_name - String name or number of road
    • surface - String value for surface
    • road_type - String value of either national, province or rural
    • road_cond - String value: paved or unpaved
    • width - Float width of edge in meters
    • min_time_cost - Float estimated minimum cost of time in USD on edge
    • max_time_cost - Float estimated maximum cost of time in USD on edge
    • min_tariff_cost - Float estimated minimum tariff cost in USD on edge
    • max_tariff_cost - Float estimated maximum tariff cost in USD on edge
    • tmda_count - Integer number of daily vehicle counts on edge

OD matrices

  1. All finalised OD matrices are stored:
    • In the path - /data/OD_data/
    • As csv file with names {mode}_nodes_daily_ods.csv
    • As csv file with names {mode}_province_annual_ods.csv
    • As Excel sheets with combined Province level annual OD matrices

The essential attributes in these OD matrices are listed below. See the data for all attributes

  1. All node-level daily OD matrices contain mode-wise and total OD flows and should have attributes:
    • origin_id - String node IDs of origin nodes
    • destination_id - String node IDs of destination nodes
    • origin_province - String names of origin Provinces
    • destination_province - String names of destination Provinces
    • min_total_tons - Float values of minimum daily tonnages between OD nodes
    • max_total_tons - Float values of maximum daily tonnages between OD nodes
    • commodity_names - Float values of daily min-max tonnages of commodities/industries between OD nodes: here based on OD data
    • If min-max values cannot be estimated then there is a total_tons column - for roads only
  2. All aggregated province-level OD matrices contain mode-wise and total OD flows and should have attributes:
    • origin_province - String names of origin Provinces
    • destination_province - String names of destination Provinces
    • min_total_tons - Float values of minimum daily tonnages between OD Provinces
    • max_total_tons - Float values of maximum daily tonnages between OD Provinces
    • commodity_names - Float values of daily min-max tonnages of commodities/industries between OD Provinces
    • If min-max values cannot be estimated then there is a total_tons column - for roads only

Hazards

  1. All hazard datasets are stored:
    • In sub-folders in the path - /data/flood_data/FATHOM
    • As GeoTiff files
    • See /data/flood_data/hazard_data_folder_data_info.xlsx for details of all hazard files
  2. Single-band GeoTiff hazard raster files should have attributes:
    • values - between 0 and 1000
    • raster grid geometry
    • projection systems: Default assumed = EPSG:4326

Administrative Areas with Statistics

  1. Argentina boundary datasets are stored:
    • In the path - /incoming_data/2/departamento
    • In the path - /incoming_data/2/provincia
    • As Shapefiles
  2. Global boundary dataset for map plotting are stored:
    • In the path - /data/boundaries/
    • As Shapefiles
  3. Census boundary data are stored:
    • In the path - /incoming_data/2/radios censales/
    • As Shapefiles

The essential attributes in the Argentina boundary datasets are listed below. See the data for all attributes

  1. All Argentina Department boundary datasets should have the attributes:
    • name - String names Spanish - attribute name changed to department_name
    • OBJECTID - Integer IDs - attribute name changed to department_id
    • geometry - Polygon geometries of boundary with projection ESPG:4326
  2. All Argentina Province boundary datasets should have attributes:
    • nombre - String names Spanish - attribute name changed to province_name
    • OBJECTID - Integer IDs - attribute name changed to province_id
    • geometry - Polygon geometries of boundary with projection ESPG:4326
  3. All global boundary datasets should have attributes:
    • name - String names of boundaries in English
    • geometry - Polygon geometry of boundary with projection ESPG:4326
  1. The census datasets should have attributes:
    • poblacion - Float value of population
    • geometry - Polygon geometry of boundary with projection ESPG:4326

Macroeconomic Data

  1. For the macroeconomic analysis we use the national IO table for Argentina:
    • In the file in path - data/economic_IO_tables/output/IO_ARGENTINA.xlsx
    • In the file in path - data/economic_IO_tables/output/MRIO_ARGENTINA_FULL.xlsx
  2. A set of look-up tables are created to match commdities in the OD matrices to IO industries
    • In the file in path - data/economic_IO_tables/input/commodity_classifications-hp.xlsx

Adaptation Options

  1. All adaptation options input datasets are stored:
    • In the file - /data/adaptation_options/ROCKS - Database - ARNG (Version 2.3) Feb2018.xlsx
    • We use the sheet Resultados Consolidados for our analysis