How do you deal with the trade-off between microwave and radar data quality and cost?

1 Microwave basics

Microwave remote sensing uses waves with wavelengths ranging from 1 mm to 1 m, which can penetrate clouds, rain, and vegetation. This makes it suitable for monitoring land surface processes, such as soil moisture, snow cover, biomass, and natural hazards. Microwave sensors can be passive or active, depending on whether they emit or receive the microwave signals. Passive sensors measure the natural thermal emission of the Earth, while active sensors transmit a pulse and measure the backscattered signal.

2 Radar basics

Radar remote sensing uses waves with wavelengths from 1 mm to 1 m, but with much higher frequency and energy than microwave sensors. Radar sensors are always active, and they can operate in different modes, such as imaging radar, scatterometer, or altimeter. Radar sensors can provide high-resolution images of the land surface, with geometric and radiometric distortions. They can also measure the distance, speed, and direction of the target, using the Doppler effect and interferometry.

3 Data quality

The quality of microwave and radar data depends on several factors, such as the spatial resolution, the temporal frequency, the signal-to-noise ratio, the calibration, and the correction of errors and artifacts. Generally, higher resolution and frequency data require more bandwidth and storage, and are more prone to noise and interference. Microwave and radar data also need to be calibrated and corrected for atmospheric effects, geometric distortions, speckle noise, and other sources of error.

4 Data cost

The cost of microwave and radar data depends on the availability, accessibility, and licensing of the data sources. Some microwave and radar data are freely available from public platforms, such as NASA, ESA, or USGS. However, some data are restricted or proprietary, and require a subscription or a fee to access. The cost of data also depends on the processing and analysis tools and software that are needed to handle and interpret the data.

5 Data applications

Microwave and radar data have numerous applications for land cover mapping, including detecting changes in land use and land cover, estimating biophysical parameters, monitoring natural hazards, and assessing environmental impacts. For instance, this data can be used to detect deforestation, urbanization, or agriculture; estimate biomass, soil moisture, vegetation structure, or snow depth; monitor floods, landslides, volcanoes, or earthquakes; and evaluate erosion, drought, or carbon emissions.

6 Data optimization

When dealing with the trade-off between microwave and radar data quality and cost, you should consider your research objectives, data requirements, and resources. To optimize your data acquisition and analysis, select the appropriate sensor type, mode, wavelength, and polarization for your application. Furthermore, you can compare and combine different data sources to increase the coverage, accuracy, and reliability of your results. Utilizing pre-processed or standardized data products can reduce the processing time and complexity. Additionally, quality control and validation methods can be used to assess and improve the data quality. Lastly, open-source or free software and tools can help reduce the data cost.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?