TY - GEN
T1 - Method to classify vegetation cover using satellite images and artificial intelligence
AU - Herrera, Lucas
AU - Auccahuasi, Wilver
AU - Rojas, Karin
AU - Urbano, Kitty
AU - Cuzcano, Abilio
AU - Carpio, Jorge Del
AU - Flores, Edward
AU - Flores, Pedro
AU - Benites, Nicanor
AU - Zamalloa, Leonidas
AU - Sernaque, Fernando
N1 - Publisher Copyright:
© 2023 Author(s).
PY - 2023/4/4
Y1 - 2023/4/4
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85152798713&partnerID=8YFLogxK
U2 - 10.1063/5.0125500
DO - 10.1063/5.0125500
M3 - Conference contribution
AN - SCOPUS:85152798713
T3 - AIP Conference Proceedings
BT - 2nd International Conference on Circuits, Signals, Systems and Securities, ICCSSS 2022
A2 - Harikumar, R.
A2 - Ganesh Babu, C.
A2 - Poongodi, C.
PB - American Institute of Physics Inc.
T2 - 2nd International Conference on Circuits, Signals, Systems and Securities, ICCSSS 2022
Y2 - 25 March 2022 through 26 March 2022
ER -