THE USE OF REMOTE SENSING IMAGES IN LAND MONITORING PUBLISHEDRoxana SELARIU, Andreea STULEANEC, Radu BERTICI, Mihai HERBEI None email@example.com
Remote sensing is defined as the technical field that deals with the detection, measurement, recording and visualization in the form of images, of electromagnetic radiation, which are emitted by objects, but also phenomena, from the surface of the Earth or from the Universe, from certain distances, without the existence of real or direct contact with them. As its name implies, remote sensing involves "the acquisition of information from a distance, without having direct contact with the detected object", through a "set of means that allow the recording of information on the earth's surface". This paper presents the spectral behaviour of some components of the environment, such as: spectral reflectance and spectral signature. Next, are presented a series of satellites, the most important of which is Landsat 8, which is the eighth satellite in the Landsat program and the seventh that successfully reaches orbit. The satellite has two instruments: OLI (Operational Land Imager) and TIRS (Thermal InfraRed Sensor), which provides global coverage at resolutions of 30m (visible spectrum, NIR, SWIR), 100m (thermal bands) and 15m (panchromatic band). We will conduct a study on the most important vegetation indices. The formulas for the calculation of the indices start from the hypothesis that the spectral variation of the soils without vegetation is linear. The function which described this variation is called the straight of the soils. This line can be most easily determined in a two-dimensional histogram of radiometric values, having as x-axis red band and z-axis, near infrared band. The radiometric values corresponding to the lack of vegetation are identified in the histogram. The straight for best approximating is the straight of the soils. Vegetation indices are very useful in monitoring of large areas, as they represent a very effective means of monitoring and evaluating drought phenomena at the scale of images, due to the possibilities of precise discrimination of vegetation, as well as correlations with biophysical parameters that determine the vegetation status and turgidity such as: plant height, leaf index, biomass, etc.
Remote Sensing, Vegetation indices, NDVI, NDWI, Landsat