Quantitative Assessment of Desertification in an Arid Oasis Using Remote Sensing Data and Spectral Index Techniques
Desertification is an environmental problem worldwide. Remote sensing data and technique offer substantial information for mapping and assessment of desertification. Desertification is one of the most serious forms of environmental threat in Morocco, especially in the oases in the south-eastern part...
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doaj-8ad0751e2db34c2b92ccd6f9e5f041c82020-11-24T21:34:04ZengMDPI AGRemote Sensing2072-42922018-11-011012186210.3390/rs10121862rs10121862Quantitative Assessment of Desertification in an Arid Oasis Using Remote Sensing Data and Spectral Index TechniquesAtman Ait Lamqadem0Hafid Saber1Biswajeet Pradhan2Laboratory of Geodynamic and Geomatic, Department of Geology, Faculty of Sciences, Chouaïb Doukkali University, Ben Maachou Street, El Jadida 24000, MoroccoLaboratory of Geodynamic and Geomatic, Department of Geology, Faculty of Sciences, Chouaïb Doukkali University, Ben Maachou Street, El Jadida 24000, MoroccoThe Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS), Faculty of Engineering and Information Technology, University of Technology Sydney, Ultimo, New South Wales 2007, AustraliaDesertification is an environmental problem worldwide. Remote sensing data and technique offer substantial information for mapping and assessment of desertification. Desertification is one of the most serious forms of environmental threat in Morocco, especially in the oases in the south-eastern part of the country. This study aims to map the degree of desertification in middle Draa Valley in 2017 using a Sentinel-2 MSI (multispectral instrument) image. Firstly, three indices, namely, tasselled cap brightness (TCB), greenness (TCG) and wetness (TCW) were extracted using the tasselled cap transformation method. Secondly, other indices, such as normalized difference vegetation index (NDVI) and albedo, were retrieved. Thirdly, a linear regression analysis was performed on NDVI⁻albedo, TCG⁻TCB and TCW⁻TCB combinations. Results showed a higher correlation between TCW and TCB (r = −0.812) than with that of the NDVI⁻albedo (r = −0.50). On the basis of this analysis, a desertification degree index was developed using the TCW⁻TCB feature space classification. A map of desertification grades was elaborated and divided into five classes, namely, nondesertification, low, moderate, severe and extreme levels. Results indicated that only 6.20% of the study area falls under the nondesertification grade, whereas 26.92% and 32.85% fall under the severe and extreme grades, respectively. The employed method was useful for the quantitative assessment of desertification with an overall accuracy of 93.07%. This method is simple, robust, powerful, and easy to use for the management and protection of the fragile arid and semiarid lands.https://www.mdpi.com/2072-4292/10/12/1862Sentinel-2GIStasselled cap transformationNDVIalbedoremote sensingmiddle Draa valley |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Atman Ait Lamqadem Hafid Saber Biswajeet Pradhan |
spellingShingle |
Atman Ait Lamqadem Hafid Saber Biswajeet Pradhan Quantitative Assessment of Desertification in an Arid Oasis Using Remote Sensing Data and Spectral Index Techniques Remote Sensing Sentinel-2 GIS tasselled cap transformation NDVI albedo remote sensing middle Draa valley |
author_facet |
Atman Ait Lamqadem Hafid Saber Biswajeet Pradhan |
author_sort |
Atman Ait Lamqadem |
title |
Quantitative Assessment of Desertification in an Arid Oasis Using Remote Sensing Data and Spectral Index Techniques |
title_short |
Quantitative Assessment of Desertification in an Arid Oasis Using Remote Sensing Data and Spectral Index Techniques |
title_full |
Quantitative Assessment of Desertification in an Arid Oasis Using Remote Sensing Data and Spectral Index Techniques |
title_fullStr |
Quantitative Assessment of Desertification in an Arid Oasis Using Remote Sensing Data and Spectral Index Techniques |
title_full_unstemmed |
Quantitative Assessment of Desertification in an Arid Oasis Using Remote Sensing Data and Spectral Index Techniques |
title_sort |
quantitative assessment of desertification in an arid oasis using remote sensing data and spectral index techniques |
publisher |
MDPI AG |
series |
Remote Sensing |
issn |
2072-4292 |
publishDate |
2018-11-01 |
description |
Desertification is an environmental problem worldwide. Remote sensing data and technique offer substantial information for mapping and assessment of desertification. Desertification is one of the most serious forms of environmental threat in Morocco, especially in the oases in the south-eastern part of the country. This study aims to map the degree of desertification in middle Draa Valley in 2017 using a Sentinel-2 MSI (multispectral instrument) image. Firstly, three indices, namely, tasselled cap brightness (TCB), greenness (TCG) and wetness (TCW) were extracted using the tasselled cap transformation method. Secondly, other indices, such as normalized difference vegetation index (NDVI) and albedo, were retrieved. Thirdly, a linear regression analysis was performed on NDVI⁻albedo, TCG⁻TCB and TCW⁻TCB combinations. Results showed a higher correlation between TCW and TCB (r = −0.812) than with that of the NDVI⁻albedo (r = −0.50). On the basis of this analysis, a desertification degree index was developed using the TCW⁻TCB feature space classification. A map of desertification grades was elaborated and divided into five classes, namely, nondesertification, low, moderate, severe and extreme levels. Results indicated that only 6.20% of the study area falls under the nondesertification grade, whereas 26.92% and 32.85% fall under the severe and extreme grades, respectively. The employed method was useful for the quantitative assessment of desertification with an overall accuracy of 93.07%. This method is simple, robust, powerful, and easy to use for the management and protection of the fragile arid and semiarid lands. |
topic |
Sentinel-2 GIS tasselled cap transformation NDVI albedo remote sensing middle Draa valley |
url |
https://www.mdpi.com/2072-4292/10/12/1862 |
work_keys_str_mv |
AT atmanaitlamqadem quantitativeassessmentofdesertificationinanaridoasisusingremotesensingdataandspectralindextechniques AT hafidsaber quantitativeassessmentofdesertificationinanaridoasisusingremotesensingdataandspectralindextechniques AT biswajeetpradhan quantitativeassessmentofdesertificationinanaridoasisusingremotesensingdataandspectralindextechniques |
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