PROCESSING AND INTERPRETATION OF SATELLITE IMAGES USING "QGIS" SOFTWARE
Session
Civil Engineering, Infrastructure and Environment
Description
In the world we live in, a special importance is being given to the environment. We are its biggest polluters, but we are the ones who must protect it. Designing measures for the protection of the environment first requires the analysis of the current situation in which we find ourselves. This analysis can be done with different methods which have their own characteristics and accuracy. Recently, identification methods from the air have taken on a special importance. Remote Sensing or Hyperspectral Image, also known as Hyperspectral (or Spectroscopic) Image, is one of the most advanced technologies in the development of Satellite Imaging, with beginnings in the early 80s, currently continues to be studied and is developed, with the aim of enabling the discovery and identification of minerals, vegetation on the ground, environmental parameters as well as materials or objects derived, or even man-made. This technology provides spatial-spectral data, based on technological developments in the production of hyperspectral sensorial systems, which collect and record reflective and emissive data in a very wide range of the electromagnetic spectrum, including its visible part. . In my paper I dealt with the classification of satellite images by creating a thematic map that defines each natural and human activity by means of colors. This allows researchers to make relevant interpretations on the state of the environment and not only on the surface of the lands and/or water. Digital image classification uses spectral information represented by numbers for one or more spectral bands, and on this basis attempts to classify each individual pixel of this information. This type of classification is known as Spectral Component Recognition or multispectral classification. The objective of this process as a whole is to define all the pixels in the image according to classes or special layers (eg water bodies, degraded forests, cereals, planted greens, etc.). At the end of this process, the resulting classified image is a "compromise" of pixel mosaics, each of which belongs to a separate theme and is essentially a thematic "map" of the original image.
Proceedings Editor
Edmond Hajrizi
ISBN
978-9951-550-50-5
Location
UBT Kampus, Lipjan
Start Date
29-10-2022 12:00 AM
End Date
30-10-2022 12:00 AM
DOI
10.33107/ubt-ic.2022.212
Recommended Citation
Hasa, Xhesika, "PROCESSING AND INTERPRETATION OF SATELLITE IMAGES USING "QGIS" SOFTWARE" (2022). UBT International Conference. 216.
https://knowledgecenter.ubt-uni.net/conference/2022/all-events/216
PROCESSING AND INTERPRETATION OF SATELLITE IMAGES USING "QGIS" SOFTWARE
UBT Kampus, Lipjan
In the world we live in, a special importance is being given to the environment. We are its biggest polluters, but we are the ones who must protect it. Designing measures for the protection of the environment first requires the analysis of the current situation in which we find ourselves. This analysis can be done with different methods which have their own characteristics and accuracy. Recently, identification methods from the air have taken on a special importance. Remote Sensing or Hyperspectral Image, also known as Hyperspectral (or Spectroscopic) Image, is one of the most advanced technologies in the development of Satellite Imaging, with beginnings in the early 80s, currently continues to be studied and is developed, with the aim of enabling the discovery and identification of minerals, vegetation on the ground, environmental parameters as well as materials or objects derived, or even man-made. This technology provides spatial-spectral data, based on technological developments in the production of hyperspectral sensorial systems, which collect and record reflective and emissive data in a very wide range of the electromagnetic spectrum, including its visible part. . In my paper I dealt with the classification of satellite images by creating a thematic map that defines each natural and human activity by means of colors. This allows researchers to make relevant interpretations on the state of the environment and not only on the surface of the lands and/or water. Digital image classification uses spectral information represented by numbers for one or more spectral bands, and on this basis attempts to classify each individual pixel of this information. This type of classification is known as Spectral Component Recognition or multispectral classification. The objective of this process as a whole is to define all the pixels in the image according to classes or special layers (eg water bodies, degraded forests, cereals, planted greens, etc.). At the end of this process, the resulting classified image is a "compromise" of pixel mosaics, each of which belongs to a separate theme and is essentially a thematic "map" of the original image.