EventsThe 1st International Electronic Conference on Forests — Forests for a Better Future: Sustainability, Innovation, Interdisciplinarity
Published
This submission belongs to the session S6. Forest Operations and Engineering of the event The 1st International Electronic Conference on Forests — Forests for a Better Future: Sustainability, Innovation, Interdisciplinarity
Published date
12 Nov, 2020
Citation
Francesco Latterini, Rachele Venanzi, Damiano Tocci, Federico Moschetti, Rodolfo Picchio, Comparing accuracy of three remote sensing methods to evaluate soil impact related to forest operations, in Proceedings of The 1st International Electronic Conference on Forests — Forests for a Better Future: Sustainability, Innovation, Interdisciplinarity, 15 November–30 November 2020, MDPI: Basel, Switzerland, doi: 10.3390/IECF2020-07954
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Comparing accuracy of three remote sensing methods to evaluate soil impact related to forest operations

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Damiano Tocci 2
Federico Moschetti 2
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1. Centro per la Ricerca in Agricoltura e l'Analisi dell'Economia Agraria, Italy
2. Tuscia University, DAFNE Department
Abstract

The aim of the present work was the evaluation of the reliability of three different remote sensing tools to assess soil impact related to forest operations. Study area consisted in an oak coppice located in the Municipality of Castel Giorgio (Terni District, Central Italy). The different tested technologies were Sentinel-2, Google Earth and Unmanned Aerial vehicle equipped with RGB sensor. After the forest utilization, images of the study area were obtained from the mentioned above systems, and a photo-interpretation process allowed to identify the skid trails pattern opened by the operators to extract the wooden material. The three theoretical skid trails patterns were compared to the real one, obtained with field relief with GNSS technology. Obtained results showed that all these systems still need some improvements for a practical application in Italian forest sector, for what concerning soil impacts evaluation after forest operations.

Keywords
remote sensing
Google Earth
Unmanned Aerial Vehicle
GNSS
GIS
Manuscript
Poster
Latterini et al. presentation.pdf
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