GADAS Input data
Description
The GADAS (Global Agricultural & Disaster Assessment System) geospatial data layers are a curated set of data products from various sources, encompassing critical aspects related to agriculture, disaster assessment, and the environment. These data are well organized in a table of contents as follows:
Weather Data: Meteorological information – such as temperature, precipitation, and snow depth – is utilized to understand and model the current, forecast, and historical weather conditions.
Vegetation Index: Satellite-derived vegetation indices like NDVI (Normalized Difference Vegetation Index) are employed to assess the health and vigor of vegetation, providing insights into crop health and land cover.
Crop Condition Data: Data on soil moisture, drought monitoring, heat damage days, days of rain, and precipitation rank are incorporated to assess agricultural productivity and identify areas at risk.
Agricultural Lands: Detailed data on agricultural lands are provided at five different scales to visualize croplands or mask out non-cropland areas with other data layers. These data layers cover types of crops, as well as irrigated/rainfed croplands, and are incorporated into relevant tools to help in evaluating the overall state of agriculture.
Disaster Data: Information on natural disasters such as earthquakes, tropical cyclones and storm impacts, floods, and volcanic activity are considered to evaluate the impact on the landscape and agricultural productivity. Data animations and risk and vulnerability layers provide additional disaster-related information.
Land Cover Data: Land use land cover datasets derived from satellite imagery provide a simple characterization of the land's surface in pre-defined categories or classes, facilitating a broader perspective on the environment.
Infrastructure Data: Details on transportation systems help to contextualize Earth observation data in terms of place, proximity, and trade flows.
Elevation Data: Elevation information aids in understanding the topography of the land, influencing factors like water drainage and soil characteristics.
Water Data: Hydrology and bathymetry data help to create finished map visualizations and to contextualize Earth observation data for the assessment of water resources for agriculture.
Political Data: Political and administrative boundaries, cities, and population information are considered to understand the governance framework that might influence agricultural practices and disaster response.
Overlays: Consistent grids define the spatial resolution of Earth observation data. GADAS predominantly provides weather and crop condition data using four gridcell arrays. Latitude and longitude data, station data locations, and drought monitoring cell gauges are also provided.
GADAS combines all these data to give a comprehensive view of global agriculture, potential disasters, and environmental conditions. This helps in making informed decisions about agriculture and disaster response.