Frequently Asked Questions about the Measurement

What type of satellites are used in your algorithms?

We use both passive microwave satellites and satellites that observe in the optical domain. The passive microwave satellites measure, which measure microwave signals that are naturally radiating from the Earth’s surface. This enables observations to be acquired during cloudy conditions, because of the physical properties of waves transmitted in this spectrum’s range. Examples of the satellites/sensors we use are:

When is the data observed?

Currently, Planet uses the nighttime observations during the descending orbits. Each satellite has its own time of observing an area, which is roughly the same time every day. For the satellites we use, these overpasses are either around 01:30 solar time or 06:00 solar time. The data acquired at that time can be regarded as a snapshot of the soil conditions at that time. Therefore, the measurements we provide are representative for the time of overpass.

What are the depths of the measurements?

The sensors we use measure the signal originating from the top layer of the soil. Typically, this is up to 10 cm deep, though the strongest contribution is received from the most upper layer. Commonly assumed is a depth of roughly 5 centimeter, but in reality the depth of this measurement varies slightly with water content. If the soil is drier, the sensing depth is deeper into the soil.

What does the unit \(m^3 m^{-3}\) represent?

The unit \(m^3 m^{-3}\) of the Planet data products is volumetric soil water content, which indicates the volume fraction of water in a volume of soil. A value of 0.4 is equivalent to 400 liters of water in one \(m^3\) of soil.

Where can I find how your soil water content retrieval works?

Planet’s retrieval algorithm is based on the Land Parameter Retrieval Model (LPRM), which has been extensively described in the scientific literature. The baseline algorithm is described in Owe et al., 2008. De Jeu et al., 2014 provides a review of LPRM and Van der Schalie et al, 2018 and 2021 describe the latest updates Planet has taken this well-tested method and uses its patented algorithm to go to a much higher spatial resolution. See also High resolution satellite soil water content.

What is your accuracy and precision?

The precision of the Planet soil water content data is about 0.001 \(m^3/m^3\). Accuracy is lower at approximately 0.04 \(m^3/m^3\). This is similar to properly installed in-situ sensors (see e.g. this paper ). This said, there are no independent measurements at the scale we are observing (e.g. no benchmark measurements at 100x100m) so the absolute accuracy remains largely unknown.

What is the difference between the 100 m and the 1 km resolution product?

Our one 1km resolution product is based on our patented disaggregation method where we make optimum use of the overlapping satellite footprints to refine the resolution from 36 km tot 1 km. The 100 m product also uses SWIR imagery of Sentinel 2. This imagery is used to add more spatial constraints to our disaggregation method.

Is it a modeled product or an observation?

The brightness temperatures are direct observations by the satellite. These observations are used in a physical based radiative transfer model to retrieve soil moisture. However, considering the strong physical description of the radiative transfer model, scientists often refer passive microwave soil moisture as satellite observed.

What do you measure in cities?

The soil water content values that we measure in urban areas are simply the measured dielectic constant values of the city’s surface converted into soil water content. Although we do show soil water content values over urban areas, these values don’t actually represent soil water content. You can use the built-up area data flag to mask out cities and other urban areas if required. See How to retrieve the data flags?.

Is vegetation on top of the soil an issue for your Soil Water Content retrievals?

In general this is not a problem. The LPRM model is able to seperate the influence on the microwave signal of the soil and vegetation components separately. Very dense vegetation (e.g. tropical rain forest) is one of the cases in which the soil water content estimate becomes impossible or less reliable. If that is the case we flag the affected pixels, see How to retrieve the data flags?.

How come your pixel size is so much smaller compared to the other Soil Water Content products?

This is due to the fact that Planet is using its patented disaggregation method ( that uses the individual overlapping footprints to retrieve the soil water content from the L1B data of the microwave satellites. Moreover, we use optical data to provide more constraints to our downscaling method.

Why do you have more than one Soil Water Content product?

Indeed we offer several products. The reason for this is that we want to give our clients the best possible product for their specific application. Based on your use of our data we will advise you which product to use, you are not alone.