Open-Source Framework for Creation of Canopy Height Models from UAS-Lidar Data

Sergio Arriola-Valverde, Renato Rimolo-Donadio, Eduardo Somarriba-Chavez, Eduardo Saenz-Vargas

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

1 Cita (Scopus)

Resumen

This work presents the integration of an open-source framework for the conformation of canopy height models. The LiDAR point cloud filtering techniques Cloth Simulation Filter and Simple Morphological Filter were evaluated, obtaining a maximum deviation or 5.77% in the generation of digital terrain models with respect to commercial tools. With the normalize digital surface model technique, a maximum difference of 7.75% was obtained from a LiDAR point cloud with a reduction factor K=10 and a GSD value of 5 cm/pix. In computational terms, a decimation process allowed to reduce the execution time, e.g., by 25% when using K=10.

Idioma originalInglés
Título de la publicación alojadaIGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Proceedings
EditorialInstitute of Electrical and Electronics Engineers Inc.
Páginas4254-4257
Número de páginas4
ISBN (versión digital)9798350320107
DOI
EstadoPublicada - 2023
Evento2023 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023 - Pasadena, Estados Unidos
Duración: 16 jul 202321 jul 2023

Serie de la publicación

NombreInternational Geoscience and Remote Sensing Symposium (IGARSS)
Volumen2023-July

Conferencia

Conferencia2023 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023
País/TerritorioEstados Unidos
CiudadPasadena
Período16/07/2321/07/23

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