Remote Sensing, it's applications; Types of sensors; Resolution of dataset.
Remote sensing is gathering information about an object or phenomenon without being in contact with it. Remote sensing is particularly used for collecting information about the earth surface through reflected or emitted electromagnetic radiation. This reflected/emitted radiation is collected by a sensor which converts it into a signal and transmits it to a processing station where data is processed into useful information.
Remote sensing is used for weather forecast, natural resource management, forest fire mapping, flood forecast and for many other applications.
Sensors may be mounted on an aircraft or a satellite. Electromagnetic radiation incident on the earth surface is absorbed (and emitted in response to it), transmitted and reflected and thus goes through many changes. These changes are detected by sensor and interpreted.
Two types of sensor are used in remote sensing applications:
Passive Sensors: Passive sensors make use of external source of energy such as sun, so they can work only in day time.
Active Sensors: Active sensors use their own source of energy so they can work day and night. Example is Radar/LIDAR etc.
Satellites use multispectral scanners which can take images in different bands of electromagnetic radiation.
Resolution
Resolution determines the quality of the data and accordingly its application. It depends on design and orientation (satellite’s orbit) of the sensor. There are four types of resolution:
Spatial Resolution: Ability of a sensor to detect area of smallest size. What minimum size you can detect from a sensor depends on size of each pixel within a digital image. High spatial resolution (lower size of pixels) means finer details can be obtained from the image.
Spectral Resolution: Sensitivity of a sensor to respond to a specific frequency range. More number of narrower range a sensor can detect, better its spectral resolution will be.
Radiometric Resolution: Ability of sensor to measure signal strength or brightness of objects which is manifested by amount of information in each pixel.
Temporal Resolution: Frequency with which a satellite can revisit to take new images of area of interest. It depends on orbit of the satellite.
Remote sensing data is processed and analyzed by visual or digital image processing techniques.