Satellite Data Processing

Adapted from the article on

Levels of Data Processing & Spatial Resolution


Satellite data is available at different stages (or levels) of processing, going from raw data collected from the satellite to polished products that visualize information. NASA takes the data from satellites and processes it to make it more usable for a broad array of applications. There is a set of terminology that NASA uses to refer to the levels of processing it conducts: 

Level 0 & 1 is the raw instrument data that may be time-referenced. It is the most difficult to use. 

Level 2 is Level 1 data that has been converted into a geophysical quantity through a computer algorithm (known as retrieval). This data is geo-referenced and calibrated. 

Level 3 is Level 2 data that has been mapped on a uniform space-time grid and quality controlled. 

Level 4  is Level 3 data that has been combined with models or other instrument data.

Level 3 &  4 data is the easiest to use.


Level 1: Brightness Temperature at 36 km

This Level 1 product (L1C) contains calibrated, geolocated, time-ordered brightness temperatures expressed in Kelvin and acquired by the SMAP radiometer. This product is a gridded version of another Level 1 brightness temperature product.

Level 2: Soil Moisture

This Level 2 soil moisture product provides measurements of the soil moisture in the top 5 cm of the soil, expressed in volumetric terms as cm3/cm3. This was retrieved using SMAP’s passive microwave radiometer brightness temperature observations. This product is resampled to an Earth-fixed, global, cylindrical 36 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0)

Level 3: Soil Moisture

This Level 3 soil moisture product provides a composite of daily estimates of soil moisture derived from SMAP’s passive microwave radiometer. SMAP L-band soil moisture data are resampled to EASE-Grid 2.0.

Level 4: Root Zone Soil Moisture at 9 km

A land surface model is used to estimate soil moisture at the root zone level (1 meter down). Estimates are obtained by assimilating soil moisture into a land surface model. That is then gridded using an EASE-Grid 2.0 projection.

Posted on July 13, 2021 Tags: