Remote sensing is formally defined as the acquisition of information related to an object, by means of instruments that are located far from the object to analyse. In our context, the instrument is a sensor beared in a satellite, while the object is the Earth's surface.

Sensors are characterized by different factors, that define the type of final application of the images taken by those sensors.

  Spatial resolution

This concept refers to the smallest object that can be distinguished in the image. It is fixed by the pixel size, measured in meters over the ground, although that depends on the position of the sensor above the Earth's surface, the vision angle, the scan velocity and the optical characteristics of the sensor.

  Temporal resolution

This is the pass frequency of the satellite above the same point of the earth's surface, and equivale to time period between two consecutive satellite passes above the same Earth's zone.

  Spectral resolution

It defines the spectral channels and its respective bandwidth in which the sensor is able to receive. Recently the hyperspectral sensors can have up to 256 channels with a very narrow bandwidth (just a few nanometers) in order to being able to distinguish in a precise way different objects by its spectral behaviour.

  Radiometric resolution

Also known as dynamic resolution, it represents the number of grey levels in which the detected radiation is classified. It depends on the analog-digital converter used: with a larger dynamic resolution we can better distinguish the small differences in radiation.

Sadly, there are several compromises among the first three properties, thus having to choose the most suitable resolution values for each application.

• The larger spatial resolution, the lower temporal and spectral resolution.
• The larger spatial resolution, the smaller surface coverage.

Low spatial resolution and high temporal resolution.

Those images are not suitable for vegetation or crops surveillance, given its lower spatial resolution. Anyway, they are the most suitable for the monitoring of atmosfere contaminants, storms, etc., due to the vast territory they cover, as well as their large temporal resolution.

Middle spatial and temporal resolution.

As we can see in the adjacent image, contours are much better distinguished, but at the cost of other properties like the temporal resolution. Those images would not be suitable for a storm surveillance.

These type of sensors are appropiate for vegetation condition reports, burned areas regeneration success assessments, drought monitoring and so on.

Environmental events control:

High spatial resolution, low temporal resolution.

The lower temporal resolution can be overcomed by increasing the number of high spatial resolution satellites in orbit, that is just the case of DEIMOS Imaging: our satellite is part of the DMC constellation, that will provide us with images within an hour period.

With those type of sensor suitable applications can be, e.g., crops conditions or watershed snow monitoring, reforestation sucess evaluation, etc.

Territory mapping:

Very high spatial resolution, low temporal resolution.

Other sensors, like Ikonos and Quickbird, have resolutions of about 1m, and among their main applications we can mention urban spatial planning, illegal constructions detection, or the assessment of the land use.