Method to classify vegetation cover using satellite images and artificial intelligence
- Lucas Herrera,
- Wilver Auccahuasi(corresponding author),
- Karin Rojas,
- ,
- Abilio Cuzcano,
- Jorge Del Carpio
- Universidad Continental, Huancayo,
- Universidad Privada del Norte,
- Universidad Nacional Federico Villarreal,
- Universidad Tecnológica del Perú,
- Universidad Nacional Mayor de San Marcos,
- Universidad Privada Norbert Wiener
Publication Information
Output type
Original language
EnglishArticle number
050005Publication milestones
- Published - 04/04/2023
Publication status
Publisher
American Institute of Physics Inc.Publication series
- Publication series name: AIP Conference Proceedings
ISSN (Print): 0094-243X
ISSN (Electronic): 1551-7616
Volume: 2725
ISBN (Electronic)
9780735444072Publication IDs
- Scopus: 85152798713
Host publication title
2nd International Conference on Circuits, Signals, Systems and Securities, ICCSSS 2022Host publication editors
- R. Harikumar
- C. Ganesh Babu
- C. Poongodi
Abstract
Space technology is being used with greater emphasis in monitoring land cover, where the use of satellite images is used to analyze large areas of land, we can find optical satellite images that cover large areas of land, we present a methodology to be able to classify areas of vegetation cover present in the cadastre by means of satellite images, the classification is carried out by analyzing the chromatic characteristics that are extracted from the images. For which, two groups of images are created, corresponding to areas with the presence of vegetation and no vegetation. For the classification, the Matlab tool was used, from where a neural network was implemented to perform the classification, as well as a user interface for the use, manipulation and classification of the image, the results allow evaluating through the user interface of such that the neural network will be able to classify it.
