**2. Remote sensing methods**

Generally, remote sensing refers to the activities of recording, observing, and perceiving (sensing) objects or events at far away (remote) places. Remote sensing is defined as a science and technology by which the characteristics of objects or events of interest can be identified, measured or analyzed without direct contact with the sensors. The spectral information relies on the properties of the light after multiple interactions, i.e., reflections, transmissions, and absorptions with the object. The information needs a physical carrier to travel from the objects/events to the sensors through an intervening medium. The electromagnetic radiation which is reflected or emitted from an object is the usual source of remote sensing data. However any media such as gravity or magnetic fields can be utilized. Remote sensing is a technology to identify and understand the object or the environmental condition through the uniqueness of their spectral responses. This technology offers advantages such as viewing parts of the Earth at different scales (synoptic view), monitoring of regions that are very remote or with restricted access, ability to obtain imagery of an area of the Earth at regular intervals over many years and to evaluate changes in the landscape as well as capability to distinguish anthropogenic effects.

A basic assumption made in remote sensing is that specific targets (soils of differed types, water with varying degrees of impurities, rocks of differing lithologies, or vegetation of various species) have an individual and characteristic manner of interacting with incident radiation that is described by the spectral response of that target. Different materials reflect and absorb visible (VIS) and infrared light differently at different wavelengths. They have different colours and brightness when seen under the sun. Thus, the targets can be differentiated by their 'spectral reflectance signatures', a term used to describe the spectral response of a target. The variety of earth's surface materials is enormous, and therefore the recording of their spectral signatures (also known as spectral library) requires substantial financial and time investments. With the development of hyperspectral technology, the spectral resolution of hyperspectral sensors have reached less than 10 nm, which is sufficient for creating a continuous spectral curve from 350-2500 nm to detect subtle changes in the spectral behaviour of the earth objects. For years, efforts have been made to establish such datasets and pool them for general use through spectral libraries. Such spectral libraries are maintained by many organizations including the Johns Hopkins University (JHU), the Jet Propulsion Laboratory (JPL), and the United States Geological Survey (USGS). Many of these datasets are made available with commercial remote sensing image processing software packages.
