The capability of a sensor or EO product to resolve anything is a function of its (spatial, temporal, spectral and radiometric) resolution and of the detail at which a geographic phenomenon of interest manifests itself in time and space. A geographic phenomenon can be named or described, georeferenced and provided with a time interval at which it exists. The geographic phenomenon of interest is the one of which a user needs information to help him make a decision. Therefore, the geographic phenomenon needs to be resolved with a low enough uncertainty and a high enough quality that allows the user to make a decision with confidence.
For example, let’s consider a helicopter pilot that wants to know whether a specific site is suitable for an emergency landing. The decision to perform an emergency landing may be supported with an EO-derived digital map of emergency landing sites that are flat enough (as well as large enough for the pilot’s helicopter and free of any obstacles on the surface and in the approach area). If we only focus on the flatness of the terrain, we need a digital elevation model (DEM) of high enough spatial resolution and accuracy in the Z dimension to calculate slope within acceptable levels of uncertainty. The pilot probably can tell us what degrees of slope are okay for his helicopter and tell us sites (e.g. football fields) where such a landing would succeed. However, this is only the input to an analysis of different DEMs to identify the minimum spatial resolution and accuracy in the Z dimension to model slope products and associated uncertainty to derive an emergency landing site product that fulfils the requirements. Thereby the capability of different DEMs to resolve emergency landing sites can be analysed.
Spatial resolution is a measure of the smallest angular or linear separation between two objects that can be resolved by the remote sensing system. A useful heuristic rule of thumb is that in order to detect a feature, the nominal spatial resolution of the sensor should be less than one-half the size of the feature measured in its smallest dimension.
Other types of resolution of an EO dataset are available that determine for various geographic phenomena under investigation whether it is possible to resolve them in the data. These are radiometric resolution, spectral resolution and temporal resolution. Radiometric resolution is defined as the sensitivity of a remote sensing detector to differences in signal strength as it records the radiant flux reflected, emitted, or back-scattered from the terrain. Spectral resolution is the number and dimension (size) of specific wavelength intervals (referred to as bands or channels) in the electromagnetic spectrum to which a remote sensing instrument is sensitive. The temporal resolution of a remote sensing system generally refers to how often the sensor records imagery of a particular area. For time-series analysis, the temporal resolution determines the time granularity for resolving processes that underlie the change that is observable between subsequent images.
The spectral resolution of an Earth Observation sensor refers to the number of spectral bands this sensor can capture. Spectral bands are wavelength intervals in the electromagnetic spectrum. Sometimes, spectral bands are also called spectral channels. Spectral resolution is related to a sensor’s ability to distinguish between different Earth’s surface features based on their spectral properties. A high number of spectral bands means high spectral resolution, with many bands meaning an increasingly smaller range of wavelengths covered by a single band. The spectral resolution of an Earth observation sensor can range from a single very broad band for panchromatic black and white images over a few bands in the case of multispectral sensors (e.g. Landsat family, SPOT, Sentinel-2) to 200 or even more channels for capturing hyperspectral images. Multispectral or hyperspectral sensor imagery has a higher degree of discriminating power than a single band sensor. Another definition of the spectral resolution can be given by the spectral sensitivity of a sensor, which can be specified by the definition of the full width, half maximum (FWHM) as being the spectral interval measured at the level at which the response of the instrument reaches one-half of its maximum values.
Spectral satellite sensors can only gather radiation which is able to pass the Earth’s atmosphere. The atmosphere contains gases, aerosols, ice crystals and water droplets, which absorb and scatter parts of the radiation passing through the atmosphere. Wavelength ranges which do not allow radiation to pass through on their way to the satellite sensors are called absorption bands and those getting through to the sensor are called atmospheric windows. This means that spectral sensors can only operate in these atmospheric windows and the spectral bands should be placed in the wavelength ranges of the atmospheric windows.