Microwave remote sensing, particularly using sensors like radar and radiometers, is commonly employed to measure soil moisture content due to its ability to penetrate vegetation and clouds and its sensitivity to changes in soil moisture.

Remote sensing allows for the collection of soil data without disturbing or damaging the soil, making it a non-destructive method of soil study.

Visible and near-infrared (VNIR) remote sensing data can be used to estimate soil organic matter content due to the strong absorption of VNIR radiation by organic matter.

Radar remote sensing, particularly synthetic aperture radar (SAR), is widely used to measure soil moisture content due to its ability to penetrate vegetation and clouds and its sensitivity to changes in soil moisture.

Atmospheric interference, such as clouds and aerosols, can affect the accuracy and reliability of remote sensing data for soil studies.

Geostationary satellites, which maintain a fixed position above a specific location on Earth, are commonly used for soil studies at regional and global scales due to their wide coverage and frequent data acquisition.

Remote sensing data can be used to map soil types by classifying soil spectral signatures, which are unique patterns of reflectance across different wavelengths.

Multispectral imagery, which captures data in multiple narrow wavelength bands, is commonly used for monitoring soil erosion due to its ability to distinguish between soil and vegetation and to detect changes in soil surface conditions.

Hyperspectral imagery offers the advantage of wide spectral coverage, allowing for the collection of detailed spectral information across a continuous range of wavelengths.

Remote sensing data can be used to estimate soil salinity by classifying soil spectral signatures, which are affected by the presence of salts in the soil.

Synthetic Aperture Radar (SAR) is commonly used to study soil compaction due to its ability to detect changes in soil surface roughness, which can be indicative of compaction.

Remote sensing data can be used to monitor soil contamination by detecting changes in soil spectral signatures, which can be caused by the presence of contaminants.

Unmanned Aerial Vehicles (UAVs), also known as drones, are suitable for soil studies at the field scale due to their ability to collect high-resolution data at low altitudes.

Field spectrometers have limited spatial coverage compared to remote sensing platforms, as they can only collect data at specific locations.

Remote sensing data can be used to estimate soil texture by classifying soil spectral signatures, which are affected by the size and shape of soil particles.