Table 1.

Description of the types of satellite remote sensing introduced in this article. Specific sensor names are given, followed by the satellite platform on which it is carried in brackets.

Type of remote sensing	Sensors & platforms	Application	Limitation
Very High Resolution (VHR) Optical Imagery	Worldview constellation, PlanetScope constellation	Data products are optical images with red, green, blue, and occasionally near-infrared spectral bands, at a ground resolution below 1 m per pixel (as low as 30 cm). Used for precise mapping of ground features and monitoring ground activities over time, as satellites often also have quick revisit times to the same location.	The low number of spectral bands captured reduce the range of science applications. Data from this type of RS is often provided as commercial products, which increases the barrier to use.	Sagan et al., 2021
High resolution Optical Imagery	OLI (Landsat 8), MSI (Sentinel 2), WVI (GaoFen-1)	Multispectral sensors capture images in between 4 and 10 spectral bands in the visible and infrared parts of the electromagnetic spectrum. Data usually have a ground resolution of between 10 m and 30 m per pixel. This data is used for various applications in urban studies, agriculture, and environment, including mapping land-use, and its changes over time. These datasets are often available to the public freely, and available for multiple years, which has led to widespread adoption by the scientific community.	Slow revisit times to the same location (order of one or two weeks). Images are often obstructed by clouds, which together with slow revisit times cause extended periods without no data. The spatial resolution is insufficient for applications that require distinguishing individual objects like houses or cars.	Xu et al., 2021; E. D. Chaves et al., 2020
Moderate Resolution Spectrometers & Radiometers	MODIS (Terrra & Aqua), OLCI (Sentinel 3), VIIRS (Suomi-NPP)	Data characterised by narrow spectral bands in the UV, visible and infrared spectrum, with more bands captured than in multispectral imagery (e.g., 36 bands for MODIS, 21 bands for OLCI). Data captured by these sensors generally have a ground resolution of between 250 m and 1 km per pixel, and is thus mainly suitable for studies over large spatial scales. The high spectral resolution allows the data to be used for a range of science applications, including studies on the atmosphere, ocean and land colour and surface temperature.	The lower spatial resolution is insufficient for certain applications.	Milne and Cohen, 1999; Hillger et al., 2014
Coarse resolution Spectrometers	TROPOMI (Sentinel 5P), OMI (Aura)	Spectrometers allow for the capture of narrow spectral bands between the UV and IR parts of the spectrum. Data is captured daily, but at low ground spatial resolution (7 km per pixel, or lower) The high spectral resolution allows for distinguishing gas types and aerosols in the atmosphere. This imagery is thus used to study the atmosphere, including ozone, air-quality, and atmospheric chemistry.	Due to the coarse spatial resolution, the data is suitable primarily for atmospheric studies, and localised air-quality and sources of pollution are difficult to measure.	Wang et al., 2020
Weather Satellites	GOES, Meteosat, Fengyun	These satellites capture wind, cloud, temperature, and other atmospheric variables, to supply data for weather monitoring. Geostationary weather satellites capture data over specific regions at high temporal frequency (e.g., every 15 min). The ground spatial resolution for weather satellite data is usually lower than 1 km per pixel.	Weather satellites are primarily limited to weather monitoring applications. The spatial resolution, and band-composition are not well suited for studies such as land cover mapping.	Perez et al., 2013