Spatiotemporal and spectral analysis of sand encroachment dynamics in southern Tunisia

Aeolian processes in drylands often transcend into sand encroachment, a common form of land degradation. Highly reflective desert features, hence sandy areas, often cause spectral confusion, and mapping through remote sensing techniques can be challenging. This work aims at designing an efficient cl...

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Main Authors: Gabriela Mihaela Afrasinei, Maria Teresa Melis, Claudio Arras, Marco Pistis, Cristina Buttau, Giorgio Ghiglieri
Format: Article
Language:English
Published: Taylor & Francis Group 2018-01-01
Series:European Journal of Remote Sensing
Subjects:
Online Access:http://dx.doi.org/10.1080/22797254.2018.1439343
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spelling doaj-b46d2501cfad4dfbb3e31c27db70951f2020-11-25T02:54:00ZengTaylor & Francis GroupEuropean Journal of Remote Sensing2279-72542018-01-0151135237410.1080/22797254.2018.14393431439343Spatiotemporal and spectral analysis of sand encroachment dynamics in southern TunisiaGabriela Mihaela Afrasinei0Maria Teresa Melis1Claudio Arras2Marco Pistis3Cristina Buttau4Giorgio Ghiglieri5University of CagliariUniversity of CagliariUniversity of CagliariUniversity of CagliariUniversity of CagliariUniversity of CagliariAeolian processes in drylands often transcend into sand encroachment, a common form of land degradation. Highly reflective desert features, hence sandy areas, often cause spectral confusion, and mapping through remote sensing techniques can be challenging. This work aims at designing an efficient classification method that minimises spectral confusion of desert features, hence two types of sandy areas. Moreover, we employ land cover (LC) change detection over the last 30 years. The extraction and spatiotemporal variations of LC and sand encroachment areas in the Dahar-Jeffara Medenine site (southeastern Tunisia) are assessed by employing Landsat imagery (1984 and 2014), a 30 m digital elevation model of Shuttle Radar Topography Mission (SRTMGL 1 arc second), field data and X-ray diffraction analyses of sand samples. Five new spectral indices were designed and employed in a Decision Tree (DT) classifier for the extraction of 11 LC classes, including two different types of sandy areas. The DT map yielded an overall accuracy of around 89%. Change detection results showed substantial change in several landscape components and an increase of sand units by 29% within the Jeffara-Medenine plain over the last three decades. Geomorphological observations and multi-temporal, spectral and mineral analyses indicate a main, possible in-situ source area of sand.http://dx.doi.org/10.1080/22797254.2018.1439343Landsat seriessand encroachmentpost-classification change detectionspectral indicesdecision tree classificationX-ray diffraction
collection DOAJ
language English
format Article
sources DOAJ
author Gabriela Mihaela Afrasinei
Maria Teresa Melis
Claudio Arras
Marco Pistis
Cristina Buttau
Giorgio Ghiglieri
spellingShingle Gabriela Mihaela Afrasinei
Maria Teresa Melis
Claudio Arras
Marco Pistis
Cristina Buttau
Giorgio Ghiglieri
Spatiotemporal and spectral analysis of sand encroachment dynamics in southern Tunisia
European Journal of Remote Sensing
Landsat series
sand encroachment
post-classification change detection
spectral indices
decision tree classification
X-ray diffraction
author_facet Gabriela Mihaela Afrasinei
Maria Teresa Melis
Claudio Arras
Marco Pistis
Cristina Buttau
Giorgio Ghiglieri
author_sort Gabriela Mihaela Afrasinei
title Spatiotemporal and spectral analysis of sand encroachment dynamics in southern Tunisia
title_short Spatiotemporal and spectral analysis of sand encroachment dynamics in southern Tunisia
title_full Spatiotemporal and spectral analysis of sand encroachment dynamics in southern Tunisia
title_fullStr Spatiotemporal and spectral analysis of sand encroachment dynamics in southern Tunisia
title_full_unstemmed Spatiotemporal and spectral analysis of sand encroachment dynamics in southern Tunisia
title_sort spatiotemporal and spectral analysis of sand encroachment dynamics in southern tunisia
publisher Taylor & Francis Group
series European Journal of Remote Sensing
issn 2279-7254
publishDate 2018-01-01
description Aeolian processes in drylands often transcend into sand encroachment, a common form of land degradation. Highly reflective desert features, hence sandy areas, often cause spectral confusion, and mapping through remote sensing techniques can be challenging. This work aims at designing an efficient classification method that minimises spectral confusion of desert features, hence two types of sandy areas. Moreover, we employ land cover (LC) change detection over the last 30 years. The extraction and spatiotemporal variations of LC and sand encroachment areas in the Dahar-Jeffara Medenine site (southeastern Tunisia) are assessed by employing Landsat imagery (1984 and 2014), a 30 m digital elevation model of Shuttle Radar Topography Mission (SRTMGL 1 arc second), field data and X-ray diffraction analyses of sand samples. Five new spectral indices were designed and employed in a Decision Tree (DT) classifier for the extraction of 11 LC classes, including two different types of sandy areas. The DT map yielded an overall accuracy of around 89%. Change detection results showed substantial change in several landscape components and an increase of sand units by 29% within the Jeffara-Medenine plain over the last three decades. Geomorphological observations and multi-temporal, spectral and mineral analyses indicate a main, possible in-situ source area of sand.
topic Landsat series
sand encroachment
post-classification change detection
spectral indices
decision tree classification
X-ray diffraction
url http://dx.doi.org/10.1080/22797254.2018.1439343
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