Data & Architecture
Analysis-Ready Data
The concept that satellite imagery should arrive ready for science, not ready for more preprocessing
Analysis-Ready Data (ARD) is satellite imagery that has been processed to a standard where it can be used directly for analysis without additional preprocessing. This means the image has been geometrically corrected (pixels are in the right geographic locations), radiometrically calibrated (pixel values represent meaningful physical quantities like surface reflectance rather than arbitrary digital numbers), atmospherically corrected (the atmosphere's distortion has been removed), and often cloud-masked (unusable pixels are flagged). ARD is the difference between receiving raw ingredients and receiving a prepared, measured, recipe-ready mise en place.
Why It Matters
The vast majority of time spent working with satellite data is not spent doing analysis. It is spent getting the data ready for analysis.
A remote sensing analyst who wants to study vegetation health across a region over five years using Sentinel-2 imagery faces this sequence before any actual science begins: download the scenes, check cloud cover, apply atmospheric correction to convert top-of-atmosphere reflectance to surface reflectance, apply geometric correction to align pixels to a coordinate reference system, resample to a common grid, apply cloud and shadow masks, verify radiometric consistency across scenes, and handle any data gaps. For a single scene, this takes minutes to hours depending on tooling. For a time series across a large area, it can take days to weeks.
This preprocessing burden is the single largest barrier to wider use of earth observation data. Not the cost of the data — much of it is free through programs like Copernicus. Not the complexity of the analysis — vegetation indices are straightforward arithmetic on spectral bands. The barrier is the gap between what the data provider delivers and what the analyst needs.
ARD closes this gap. When data is delivered as ARD, the analyst receives surface reflectance values in a known projection with quality flags already applied. They can start computing NDVI immediately. They can compare scenes from different dates because the radiometry is consistent. They can composite across sensors because the data has been harmonized to a common standard.
The Committee on Earth Observation Satellites (CEOS) formalized ARD requirements in their ARD for Land (CARD4L) framework, defining minimum specifications for what constitutes analysis-ready optical and radar data. These specifications cover geometric accuracy, radiometric consistency, atmospheric correction quality, and metadata completeness.