English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

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. An 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 a 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. doi: 10.2166/hydro.2019.083 s://iwaponline.com/jh/article-pdf/doi/10.2166/hydro.2019.083/610494/jh2019083.pdf A. Francipane (corresponding author) G. Cipolla A. Maltese G. La Loggia L. V. Noto Dipartimento di Ingegneria (DI), Università di Palermo, Viale delle Scienze, 90142 Palermo, Italy E-mail: antonio.francipane@unipa.it

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