@article{fdi:010058871,
  title = {{M}apping linear erosion features using high and very high resolution satellite imagery},
  author = {{D}esprats, {J}. {F}. and {R}aclot, {D}amien and {R}ousseau, {M}. and {C}erdan, {O}. and {G}arcin, {M}. and {L}e {B}issonnais, {Y}. and {B}en {S}limane, {A}. and {F}ouche, {J}. and {M}onfort-{C}liment, {D}.},
  editor = {},
  language = {{ENG}},
  abstract = {{M}apping and monitoring linear erosion features ({LEF}s) over large areas is fundamental for a better understanding of the main erosion processes and for planning suitable protection measures. {T}he advent of very high-resolution satellite imagery has expanded the range of satellite {LEF} identification to moderate-size elements. {A}fter determining the relationship between satellite imagery resolution and the ability to detect {LEF}s, we discuss a highly automated method for extracting such {LEF}s from a very high spatial resolution image (0.61?m resolution). {T}he method is based on a two-stage strategy: (1) extraction of all linear features visible on the satellite image using filters and photo-interpretation; (2) filtering these linear features according to geometric criteria (e.g. orientation relative to slope, sinuosity, position in landscape, etc.) so as to retain only those relative to linear erosion. {A} series of three images with increasing spatial resolution (10.5 and 0.61?m) was prepared for an area on the {C}ap {B}on peninsula ({T}unisia). {T}his predominantly agricultural area has a high density of {LEF}s with very varied geometric characteristics. {T}he area's problems are both onsite for the agriculture itself, and offsite with the silting up of hillside reservoirs. {R}espectively 22 per cent, 37 per cent and 73 per cent of the site's {LEF}s, with respective average widths of 2.8, 3.0 and 2.2?m, are visible on the 10, 5 and 0.61?m resolution images. {G}ully identification should help to identify the most threatened areas to help land use planning and management or to validate erosion models whether at regional or local (drainage basin) scale.},
  keywords = {remote sensing ; {Q}uick{B}ird ; linear erosion features ; very high ; resolution ; {T}unisia ; {TUNISIE}},
  booktitle = {},
  journal = {{L}and {D}egradation and {D}evelopment},
  volume = {24},
  numero = {1},
  pages = {22--32},
  ISSN = {1085-3278},
  year = {2013},
  DOI = {10.1002/ldr.1094},
  URL = {https://www.documentation.ird.fr/hor/fdi:010058871},
}