Gully erosion is a form of accelerated erosion that may affect soil productivity, restrict land use, and lead to an increase of risk to infrastructure. Accurate mapping of these landforms can be difficult because of the presence of dense canopy and/or the wide spatial extent of some gullies. Even where possible, mapping of gullies through conventional field surveying can be an intensive and expensive activity. The recent widespread availability of very high resolution (VHR) imagery has led to remarkable growth in the availability of terrain information, thus providing a basis for the development of new methodologies for analyzing Earth’s surfaces. This work aims to develop a geographic object-based image analysis to detect and map gullies based on VHR imagery. A 1-meter resolution LIDAR DEM is used to identify gullies. The tool has been calibrated for two relatively large gullies surveyed in the Calhoun Critical Zone Observatory (CCZO) area in the southeastern United States. The developed procedure has been applied and tested on a greater area, corresponding to the Holcombe’s Branch watershed within the CCZO. Results have been compared to previous works conducted over the same area, demonstrating the consistency of the developed procedure.

Francipane, A., Cipolla, G., Maltese, A., La Loggia, G., Noto, L. (2020). Using very high resolution (VHR) imagery within a GEOBIA framework for gully mapping: An application to the Calhoun Critical Zone Observatory. JOURNAL OF HYDROINFORMATICS, 22, 219-234 [10.2166/hydro.2019.083].

Using very high resolution (VHR) imagery within a GEOBIA framework for gully mapping: An application to the Calhoun Critical Zone Observatory

Francipane, A.
;
Cipolla, G.;Maltese, A.;La Loggia, G.;Noto, Leonardo
2020-01-01

Abstract

Gully erosion is a form of accelerated erosion that may affect soil productivity, restrict land use, and lead to an increase of risk to infrastructure. Accurate mapping of these landforms can be difficult because of the presence of dense canopy and/or the wide spatial extent of some gullies. Even where possible, mapping of gullies through conventional field surveying can be an intensive and expensive activity. The recent widespread availability of very high resolution (VHR) imagery has led to remarkable growth in the availability of terrain information, thus providing a basis for the development of new methodologies for analyzing Earth’s surfaces. This work aims to develop a geographic object-based image analysis to detect and map gullies based on VHR imagery. A 1-meter resolution LIDAR DEM is used to identify gullies. The tool has been calibrated for two relatively large gullies surveyed in the Calhoun Critical Zone Observatory (CCZO) area in the southeastern United States. The developed procedure has been applied and tested on a greater area, corresponding to the Holcombe’s Branch watershed within the CCZO. Results have been compared to previous works conducted over the same area, demonstrating the consistency of the developed procedure.
2020
Settore ICAR/02 - Costruzioni Idrauliche E Marittime E Idrologia
Settore ICAR/06 - Topografia E Cartografia
Francipane, A., Cipolla, G., Maltese, A., La Loggia, G., Noto, L. (2020). Using very high resolution (VHR) imagery within a GEOBIA framework for gully mapping: An application to the Calhoun Critical Zone Observatory. JOURNAL OF HYDROINFORMATICS, 22, 219-234 [10.2166/hydro.2019.083].
File in questo prodotto:
File Dimensione Formato  
Francipane et al., 2019 - Ecognition.pdf

accesso aperto

Descrizione: Articolo principale
Tipologia: Pre-print
Dimensione 2.23 MB
Formato Adobe PDF
2.23 MB Adobe PDF Visualizza/Apri
jh0220219 (1).pdf

accesso aperto

Descrizione: Articolo completo
Tipologia: Versione Editoriale
Dimensione 930.58 kB
Formato Adobe PDF
930.58 kB 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: https://hdl.handle.net/10447/420279
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 6
  • ???jsp.display-item.citation.isi??? 6
social impact