In the frame of project FoGLIE (Fruition of Goods and Landscape in Interactive Environment), UAS were used to survey a park area in its less accessible zones, for scenic and stereoscopic videos, 3D modeling and vegetation monitoring. For this last application, specifically, through the acquisition of very high resolution images taken with two UAS-borne compact cameras (RGB and NIR), a DSM of a small vegetated area and the corresponding orthoimages were produced and co-registered. Planimetric and height accuracies in block adjustments and orthophotos are in the range of 0.10 m horizontally and 0.15 m in height. Then, after the derivation of synthetic channels, both unsupervised classification and supervised one were performed in order to test the algorithms' ability to distinguish between different bushes and trees species: some of them were correctly classified by the latter method but misclassifications still remain. The overall accuracy for the unsupervised classification is about 50% while the supervised one yields an overall accuracy around 80%.

Use of Unmanned Aerial Systems for multispectral survey and tree classification: a test in a park area of northern Italy

GINI, ROSSANA;PASSONI, DANIELE;PINTO, LIVIO;SONA, GIOVANNA
2014

Abstract

In the frame of project FoGLIE (Fruition of Goods and Landscape in Interactive Environment), UAS were used to survey a park area in its less accessible zones, for scenic and stereoscopic videos, 3D modeling and vegetation monitoring. For this last application, specifically, through the acquisition of very high resolution images taken with two UAS-borne compact cameras (RGB and NIR), a DSM of a small vegetated area and the corresponding orthoimages were produced and co-registered. Planimetric and height accuracies in block adjustments and orthophotos are in the range of 0.10 m horizontally and 0.15 m in height. Then, after the derivation of synthetic channels, both unsupervised classification and supervised one were performed in order to test the algorithms' ability to distinguish between different bushes and trees species: some of them were correctly classified by the latter method but misclassifications still remain. The overall accuracy for the unsupervised classification is about 50% while the supervised one yields an overall accuracy around 80%.
Classification; DSM; UAS; Vegetation; Orthophoto; Block Adjustment
File in questo prodotto:
File Dimensione Formato  
2014_EuJRS_47_251_269_Gini.pdf

accesso aperto

: Post-Print (DRAFT o Author’s Accepted Manuscript-AAM)
Dimensione 3.79 MB
Formato Adobe PDF
3.79 MB Adobe PDF Visualizza/Apri
Use of Unmanned Aerial Systems for multispectral survey_11311-942168.pdf

accesso aperto

: Publisher’s version
Dimensione 4.07 MB
Formato Adobe PDF
4.07 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11311/942168
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 72
  • ???jsp.display-item.citation.isi??? 57
social impact