Method to classify vegetation cover using satellite images and artificial intelligence
Fecha
2023-04-04Autor(es)
Herrera, Lucas
Auccahuasi, Wilver
Rojas, Karin
Urbano, Kitty
Cuzcano, Abilio
Del Carpio, Jorge
Flores, Edward
Flores, Pedro
Benites, Nicanor
Zamalloa, Leonidas
Sernaque, Fernando
Metadatos
Mostrar el registro completo del ítemResumen
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.
Mostrar más
Cita bibliográfica
Herrera, L., Auccahuasi, W., Rojas, K., Urbano, K., Cuzcano, A., Del Carpio, J., Flores, E., Flores, P., Benites, N., Zamalloa, L., & Sernaque, F. (2023). Method to classify vegetation cover using satellite images and artificial intelligence. AIP Conference Proceedings, 2725(1), 050005. https://doi.org/10.1063/5.0125500
Nota
El texto completo de este trabajo no está disponible en el Repositorio Académico UPN por restricciones de la casa editorial donde ha sido publicado.
Materia
Colecciones
Ítems relacionados
Mostrando ítems relacionados por Título, autor o materia.
-
Classification of land cover in optical satellite images, using characteristics and color indices
Auccahuasi, Wilver; Herrera, Lucas; Rojas, Karin; Urbano, Kitty; Romero, Luis; Lovera, Denny; Cueva, Juanita; Perez, Ivan; Santos, César; Leva, Antenor; Fuentes, Alfonso; Sernaque, Fernando (American Institute of Physics, 2023-04-04)Acceso cerradoSatellite images are being used more and more frequently in the analysis of land coverage, due to their ability to record large areas of land, managing to analyze their type of coverage and the uses that it is providing, ... -
Análisis espacio temporal de la cobertura vegetal mediante el NDVI, y su relación con el crecimiento poblacional de la provincia de Lima, Perú (2000-2019)
Guerra Cardenas, María de los Ángeles Lisbeth (Universidad Privada del Norte, 2021-11-19)Acceso abiertoLos cambios de cobertura vegetal son provocados por factores naturales, climáticos y antrópicos, siendo este último el más predominante en territorios urbanos; en donde, se encuentra el crecimiento poblacional; el cual, ... -
Methodology for classifying objects in high resolution optical images, using deep learning techniques
Herrera, Lucas; Auccahuasi, Wilver; Leva, Antenor; Urbano, Kitty; Flores, Edward; Flores, Michael; Flores, Javier; Santos, César; Arroyo, Sergio; Rojas, Karin; Bejarano, Patricia; Sernaque, Fernando (American Institute of Physics, 2023-04-04)Acceso cerradoThe classification of objects that are present in the images or in the videos, is being developed progressively obtaining good results thanks to the use of Convolutional Networks, in this work we also use the convolutional ...