Object-Based Image Analysis Technique for Gully Mapping Using Topographic Data at Very High Resolution (VHR)

6 pages•Published: September 20, 2018

Antonio Francipane, Francesca Mussomè, Giuseppe Cipolla and Leonardo Noto

Abstract

An accurate mapping of gullies is important since they are still major contributors of sediment to streams. Mapping gullies in many areas is difficult because of the presence of dense canopy, which precludes the identification through aerial photogrammetry and other traditional remote sensing methods. Moreover, the wide spatial extent of some gullies makes their identification and characterization through field surveys a very large and expensive proposition.
This work aims to develop an object-based image analysis (OBIA) to detect and map gullies based on a set of rules and morphological characteristics retrieved by very high resolution (VHR) imagery. A one-meter resolution LiDAR Digital Elevation Model (DEM) is used to derive different morphometric indexes, which are combined, by using different segmentation and classification rules, to identify gullies. The tool has been calibrated using, as reference, the perimeters of two relatively large gullies that have been measured during a field survey in the Calhoun Critical Zone Observatory (CCZO) area in the Southeastern United States.

Keyphrases: classification, ecognition, object based, segmentation, very high resolution

In: Goffredo La Loggia, Gabriele Freni, Valeria Puleo and Mauro De Marchis (editors). HIC 2018. 13th International Conference on Hydroinformatics, vol 3, pages 725-730.

Links:	https://easychair.org/publications/paper/Q5Lw
	https://doi.org/10.29007/shdh

BibTeX entry

@inproceedings{HIC2018:Object_Based_Image_Analysis,
  author    = {Antonio Francipane and Francesca Mussomè and Giuseppe Cipolla and Leonardo Noto},
  title     = {Object-Based Image Analysis Technique for Gully Mapping Using Topographic Data at Very High Resolution (VHR)},
  booktitle = {HIC 2018. 13th International Conference on Hydroinformatics},
  editor    = {Goffredo La Loggia and Gabriele Freni and Valeria Puleo and Mauro De Marchis},
  series    = {EPiC Series in Engineering},
  volume    = {3},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2516-2330},
  url       = {/publications/paper/Q5Lw},
  doi       = {10.29007/shdh},
  pages     = {725-730},
  year      = {2018}}

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