The five resolutions have different importance in the field of remote sensing, and they are:
Spatial Resolution:
Definition: Refers to the size of a cell in an image that represents a point on the ground, and is the ability to measure the details of the earth's surface.
Application: In satellite maps, spatial resolution determines the clarity and level of detail of the image.
Spectral resolution
Definition: Refers to the ability of a remote sensing sensor to resolve the range of the radiant energy spectrum, i.e., in how many bands the data is collected.
Application: Spectral resolution determines the spectral information that can be captured by remote sensing data, which plays an important role in the spectral characteristics of different ground objects.
Temporal resolution
Definition: Refers to the time interval between data collected by the remote sensing system, that is, the frequency at which the same area is observed.
Applications: Temporal resolution is used to monitor land surface changes, such as seasonal changes, rapid response to natural disasters, etc.
Radiometric resolution:
Definition: Refers to the accuracy of the radiation intensity that a sensor is able to sense and record.
Application: Radiometric resolution is very important for accurately measuring the brightness and hue of surface features, affecting the quality of images and the accuracy of information extraction.
Geometric Resolution:
Definition: Refers to the spatial relationship between adjacent cells in an image, that is, the ratio of the actual distance on the ground to the distance in the image.
Application: Geometric resolution directly affects the location accuracy of specific features on the map, which is of great significance for geographic information system (GIS) applications.
Therefore, when selecting satellite data for a specific application, these five resolutions need to be considered together to ensure that the data meets the needs of research or monitoring.