Map Documentation
We present here a concise overview of the data layers that have been added to the Your VCCA India map. For details on the respective sources and preprocessing steps please refer to https://doi.org/10.5281/zenodo.5839899.
GIS LAYERS
CROPLAND GFSAD 30m
This layer presents the cropland vs non-cropland and water extent as calculated in the Global Food Security-support Analysis Data (GFSAD) with data from 1990 to 2017, at 30m resolution. Map services and data are made available from U.S. Geological Survey, National Geospatial Program, and can be reproduced with no restrictions. Data has been downloaded from the NASA’s Land Processes Distributed Active Archive Center (https://lpdaac.usgs.gov/products/gfsad30saafgircev001/, last download: October 9th, 2021) and restricted to the region of interest. Data is color-coded to differentiate between cropland (green), non-cropland (gray), and water bodies (black).
License: https://www.usgs.gov/information-policies-and-instructions/acknowledging-or-crediting-usgs
ELEVATION ALOS DSM GLOBAL 30m
Elevation (in meters) was sourced from the Japan Aerospace Exploration Agency (JAXA) Earth Observation Research Center. The data was prepared by JAXA as part of the ALOS World 3D – 30m (AW3D30) dataset, a global digital surface model (DSM) dataset with 30 meters resolution, and imported directly into Google Earth Engine (https://developers.google.com/earth-engine/datasets/catalog/JAXA_ALOS_AW3D30_V3_2).
PREDICTED ELECTRICITY NETWORK LINES
This layer displays the predicted location of electricity network lines, as computed in Arderne et al., 2020 (https://doi.org/10.1038/s41597-019-0347-4) using satellite imagery of night-time lights and OpenStreetMap data. Data has been downloaded from https://zenodo.org/record/3628142 (last download: October 8th, 2021) and represents (vectorized) predicted distribution and transmission line network, together with existing OpenStreetMap lines. Please refer to the original paper for additional information on data collection and accuracy.
FRUITS & VEGETABLES PRODUCTION
District-wise statistics on crop production (in tonnes) for fruits and vegetables have been downloaded from the ICRISAT (International Crop Research Institute for the Semi-Arid Tropics) website: http://data.icrisat.org/dld/src/additional.html (last download: November 24th, 2021). Data is sourced from the State Horticultural Department. Displayed data shows perishable crops of interest and refers to the year 2016. For visualization purposes, the data has been merged with the administrative layer at the district level.
FRUITS & VEGETABLES COLD ROOMS
District-wise cold storage locations data has been downloaded from the ICRISAT (International Crop Research Institute for the Semi-Arid Tropics) website: http://data.icrisat.org/dld/src/additional.html (last download: October 7th, 2021). Data is sourced from the Central Warehousing Corporation. Displayed data represents the total number of cold storage for fruits and vegetables or for mixed-use for each district and refers to the year 2009. For visualization purposes, the data has been merged with the administrative layer at the district level.
MONTHLY TEMPERATURE
The monthly temperature of 2020 has been downloaded from the ERA5 database (https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=overview, last download: July 2nd, 2021). The spatial resolution is approximately 30 km (0.25 º latitude and 0.25 º longitude). The parameter’s name is “2m temperature,” and the name of the dataset is “ERA5 hourly data on single levels from 1979 to present”. The original dataset is in K and converted to °C.
License: See ‘License’ tab at https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=overview
MONTHLY SOLAR RADIANCE
The monthly solar radiance of 2020 (in W/m^2) represents the amount of both direct and diffused solar radiation at the surface. The data has been downloaded from the ERA5 database (https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=overview, last download: July 2nd, 2021). The spatial resolution is approximately 30 km (0.25 º latitude and 0.25 º longitude). The parameter’s name is “Total sky direct solar radiation at surface,” and the name of the dataset is “ERA5 hourly data on single levels from 1979 to present”.
License: See ‘License’ tab at https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=overview
SHELF LIFE GAIN
The predicted gain of shelf life (in days) is obtained by comparing active cooling at the optimal temperature of the corresponding crop to keeping the crop at ambient temperature. The shelf life at the ambient temperature was calculated using the kinetic rate model using temperature (please refer to https://doi.org/10.5281/zenodo.5839900 for more details). The optimal temperature for a corresponding crop was obtained from FAO (http://www.fao.org/3/y4893e/y4893e06.htm, last downloaded: December 14th, 2020).
ROADS
The layer represents the road network from OpenStreetMap. Data has been downloaded from http://download.geofabrik.de/asia/india.html (last download: June 30th, 2021).
License: Open Database 1.0 License
MARKET LOCATIONS
This layer presents the amenities identified as ‘marketplaces’ in OpenStreetMap. Data has been downloaded from https://overpass-turbo.eu/ (last download: December 6th, 2021). Marketplaces identified as ‘waypoints’ and ‘track points’ have been merged, and cropped to the region of interest.
License: Open Database 1.0 License
GSMA MOBILE BROADBAND COVERAGE 1km
This layer displays the World Mobile Broadband coverage, which is a 1km resolution raster representation of cellular mobile wireless Internet access. The data has been downloaded from the FAO Map Catalog (https://data.apps.fao.org/map/catalog/srv/eng/catalog.search#/metadata/7ee38f75-605f-4c88-9afc-64779e70e595, last download November 17th, 2021). The downloaded raster has been clipped to the region of interest. Please refer to the original source for additional information on data collection and accuracy.
License: See the ‘Legal constraints’ tab at https://data.apps.fao.org/map/catalog/srv/eng/catalog.search#/metadata/7ee38f75-605f-4c88-9afc-64779e70e595
AVAILABILITY OF MANDIS
These layers display the percentage of villages in each administrative level (district or block) where a Mandi is reported as available. The data is extracted from the Mission Antyodaya 2019 Report (https://missionantyodaya.nic.in/ma2019/, last download: June 3rd, 2021). The data has been web scraped from the report ‘Villagewise Report on Infrastructure’ (the column ‘Availability of markets: Mandis’ has been normalized to ‘No. of Villages Where Survey completed’) and merged with the administrative layers at the level of districts and blocks (for the states of Odisha and Bihar).
License: unknown
HOUSEHOLDS ENGAGED IN FARMING
These layers display the percentage of households in each administrative level (district or block) that are majorly involved in Farm activities. The data is extracted from the Mission Antyodaya 2019 Report (https://missionantyodaya.nic.in/ma2019/, last download: June 15th, 2021). The data has been web scraped from the report ‘Agriculture’ (the report column ‘Total No. OfHHs engaged majorly in Farm activities’ has been normalized to ‘Total Household’) and merged with the administrative layers at the level of districts and blocks (for the states of Odisha and Bihar).
License: unknown
VILLAGES WITH FARMERS PRODUCER ORGANIZATIONS (FPOs)
These layers display the percentage of villages in each administrative level (district or block) that are reported to have at least one FPO. The data is extracted from the Mission Antyodaya 2019 Report (https://missionantyodaya.nic.in/ma2019/, last download: June 15th, 2021). The data has been web scraped from the report ‘Agriculture’ (the report columns ‘Farmers Collective-FPOs(Count Of Villages)’ and ‘Farmers Collective-Both(Count Of Villages)’ have been added up and normalized to ‘No. of Villages Where Survey completed’) and merged with the administrative layers at the level of districts and blocks (for the states of Odisha and Bihar).
License: unknown
CULTIVABLE AREA
These layers display the percentage of area in each administrative level (district or block) which is reported as cultivable (in hectares). The data is extracted from the Mission Antyodaya 2019 Report (https://missionantyodaya.nic.in/ma2019/, last download: June 21st, 2021). The data has been web scraped from the report ‘Land Use and Irrigation’ (report column:’ Total cultivable Area(ha.)’), merged with the administrative layers at the level of districts and blocks (for the states of Odisha and Bihar), and normalized by the area of the polygons.
License: unknown
POPULATION DENSITY - NEW
These layers display the population density (in number of people per km squared) in each administrative level (district or block). The data is extracted from the Mission Antyodaya 2019 Report (https://missionantyodaya.nic.in/ma2019/, last download: June 3rd, 2021). The data has been web scraped from the report ‘Villagewise Report on Infrastructure’ (report column ‘Total Population’), merged with the administrative layers at the level of districts and blocks (for the states of Odisha and Bihar), and normalized by the area of the polygons.
License: unknown
HARVESTING SEASON - NEW
The harvesting season of apples, bananas, and potatoes was sourced from the Agricultural and Processed Food Products Export Development Authority (APEDA) of the Ministry of Commerce and Industry (for apple, banana, and potato; last download: May 3rd, 2021) for each state in India. The data is color-coded to differentiate between Not season (gray), Lean season (gold), Peak season (orange), Round the year (turquoise).
License: unknown
PREDICTED COLD ROOM LOCATIONS
This layer presents areas that could be suitable to install a cooling unit based on the available open-source data. This information is calculated based on the vicinity to a market, availability of close-by roads and stable network connection, amount of available Mandis and households dedicated to farming, and cultivable area in the region. Please refer to https://doi.org/10.5281/zenodo.5839899 for details on the computation. Note that this map is case-specific and depends on several assumptions on relevant layers and thresholds. In a future release of this application, we plan to make the map more interactive by allowing users to compute promising cold room locations by dynamically deciding which layers to include and their thresholds.
CROPLAND HIMACHAL PRADESH 10m - NEW
This layer presents the cropland predictions for 2020 made by Li et al. (2022) for three districts in Himachal Pradesh (Mandi, Kullu, and Shimla). The layer is colorized by altitude using the ALOS 30m elevation map. No data and non-croplands values are not visualized. The map was generated using a Random Forest classifier and feature engineering from a time series of Sentinel-2 satellite images. More information about the methodology and the code for generating the map can be found on the paper.