Desertification assessment using Sentinel-2A images, spectral and TCT indices in the Admer-Ezem watershed, upper Oum-Rbaa basin, Morocco

Abstract

This paper focuses on a quantitative assessment of desertification in the Admer-Ezem basin, using Sentinel-2A satellite images and indices to map the degree of basin-wide desertification in 2023. The methodology is based on the extraction of several spectral indices, such as the normalized difference vegetation index (NDVI), albedo, topsoil grain size index (TGSI) and the modified soil adjusted vegetation index (MSAVI), as well as the tasseled cap transformation (TCT) indices: brightness (TCB), greenness (TCG) and wetness (TCW). Different combinations of these indices were then created and analyzed using linear regression to identify low correlation rates. Based on these results, three characteristic zones were selected: TGSI-Albedo (r = -0.95), TGSI-TCW (r = -0.74) and TCW-TCB (r = -0.73). The resulting map subdivides the region into five categories of desertification: extreme, severe, moderate, low and non-desertified. The results show that the forest is undergoing progressive desertification. In general, and according to the different models used, more than 50% of the area studied is subject to severe to extreme desertification, while less than 30% of the area is classified as no-desertified, or slightly affected. Thanks to the high accuracy of the models used (Area Under the Curve (AUC) from 79 to 83%), this approach proves to be almost optimal for the quantitative analysis and monitoring of desertification in the Moroccan Middle Atlas. Finally, this work can help planners identify the most suitable sites for future forest development.

Keywords

• Sentinel 2A
• Spectral Index
• TCT
• Morocco
• Desertification

References

1. REFERENCE LIST :
2. Imeson, AC. (1996). Desertification research—Thematic issues and spatial and temporal scaling. In: Hill J, Peter D (eds) The use of remote sensing for land degradation and desertification monitoring in the Mediterranean basin. European Commission, Brussels. https://hdl.handle.net/11245/1.125472
3. Rubio, J.L., & Recatala, L. (2006).The relevance and consequences of Mediterranean desertification including security aspects. In: Kepner WG, Rubio JL, Mouat DA, Pedrazzini F (eds) Desertification in the Mediterranean Region: a security issue. Springer, Netherlands, pp. 133–165. https://doi :10.1007/1-4020-3760-0_05
4. Duanyang, X., Xiangwu ,K., Dongsheng, Q., Dafang, Z., & Jianjun, P.(2009). Quantitative Assessment of Desertification Using Landsat Data on a Regional Scale – A Case Study in the Ordos Plateau, China. Remote Sensors (Basel). 2009, 9(3),pp. 1738-1753. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3345839/#.
5. Guo, Q., Fu, B., Shi, P., Cudahy, T., Zhang, J., & Xu, H. (2017). Satellite Monitoring the Spatial-Temporal Dynamics of Desertification in Response to Climate Change and Human Activities across the Ordos Plateau, China. Remote Sens., 9, 525. [CrossRef].
6. Reem Tuama, Y., & AL-khakani, E.T. (2021). Assessing Degree of Desertification Using Tasselled Cap Transformation and Spectral Indicators Techniques: Iraq. The Scientific Journal of King Faisal University, Volume (2).Issue (1). https://doi.org/10.37575/b/sci/0019
7. UNCCD (1994). United Nations Convention to Combat Desertification in those Countries Experiencing Serious Drought and/or Desertification, particularly in Africa; United Nations Convention to Combat Desertification: United Nations Paris, France., Treaty Series, vol. 1954, p. 3. [Google Scholar]
8. Bouabid, R., Rouchdi, M., Badraoui, M., & Louafi, S. (2010). Assessment of land desertification based on the MEDALUS approach and elaboration of an action plan: the case study of the Souss River Basin, Morocco. Land degradation and desertification: assessment, mitigation and remediation. Springer, pp 131–145. https://www.researchgate.net/publication/251100743

9. Ekundayo, A., Oluibukun, A., Joseph, O., & Abel, I. (2024). Assessing the risk of soil loss using geographical information system (GIS) and the revised universal soil loss equation (RUSLE). Advanced GIS. 4(2),pp. 42-53. http://publish.mersin.edu.tr/index.php/agis/indexe-ISSN:2822-7026.
10. Thomas, D. S. G. (1995). Desertification: Causes and processes, In: Encyclopedia of Environmental Biololgy, Vol. 1, ed. W. A. Nierenberg, San Diego, Academic Press,pp. 463-473. [Google Scholar]
11. Array, A. (1989). Current Issues and Trends in Irrigation with Special Reference to Developing Countries, In: “Resource Conservation and Desertification Control in the Near East, Report of the International Training Course, DSE, FAO, GTZ, UNESCWA, Germany and Kingdom of Jordan.
12. Verbist, K., Santibañez, F., Gabriels, D., & Soto, G. (2010). Atlas de zonas áridas de América Latina y El Caribe. : dentro del marco del proyecto elaboración del Mapa de Zonas áridas, Semiáridas y Subhúmedas de América Latina y el Caribe. http://www.cazalac.org/mapa_za.php
13. Hu, Y., Han, Y., & Zhang, Y. (2020). Land desertification and its influencing factors in Kazakhstan. J Arid Environ 18+0:104203. http://dx.doi.org/10.1016/j.jaridenv.2020.104203
14. Khorrami, B., Gunduz, O., Patel, N., & Ghouzlane, S. (2019). Land surface temperature anomalies in response to changes in forest cover. International Journal of Engineering and Geosciences, 4(3), pp. 149-156. https://doi.org/10.26833/ijeg.549944
15. Herrmann, S., Diouf. A. A., & Sall, I. (2020). Beyond bioproductivity: engaging local perspectives in land degradation monitoring and assessment. J Arid Environ 173:104002, http://dx.doi.org/10.1016/j.jaridenv.2019.104002
16. Lamaamri, M., Lghabi, N., Ghazi, A., El Harchaoui, N., Adnan, MSG., & Shakiul Islam, M. (2022). Evaluation of desertification in the Middle Moulouya Basin (North-East Morocco) using sentinel-2 images and spectral index techniques. Earth Syst Environ pp.1– 20. https://doi.org/10.1007/S41748-022-00327-9
17. Reynolds, J., Maestre, F., Huber-Sannwald, E., Herrick, J., & Kemp, P. (2006). Aspectos socioeconómicos y biofísicos de la desertificación: . Ecosistemas, 14(3). http://www.revistaecosistemas.net/articulo.asp?Id=131
18. L’organisation arabe pour le développement agricole (OADA) .(2002). Etude des Indicateurs de Suivi de la Désertification dans le Pays Arabes. United Nations, Treaty Series , vol. 1954, p. 3. [Google Scholar]
19. El- Bouhali, A., Amyay, M., & El Ouazani Ech- Chahdi, K. (2024). Changes in water surface area of the Middle Atlas-Morocco lakes: A response to climate and human effects. International Journal of Engineering and Geosciences, 9(2), pp. 221-232. https:// doi:10.26833/ijeg.1391957
20. Boutallaka, M., Miloud, T., El Mazi, M., Hmamouchi, M., & EL Hairchi, K. (2025). Assessment of current and future land sensitivity to degradation under climate change in the upstream Ouergha watershed (Morocco) using GIS and AHP method. International Journal of Engineering and Geosciences, 10(1), 46-58. https://doi.org/10.26833/ijeg.1521350
21. Mokhtari ,N .(2016). Etude de la dynamique de la désertification dans le bassin versant de la Moulouya en intégrant les données issues de la télédétection et les données socio-économiques, Maroc (Thèse de doctorat). Université de Liège, pp.326. https://www.academia.edu/79606011
22. MADREF (Ministère de l’Agriculture du Développement Rural et des Eaux et Forêts). (2020). Programme national de lutte contre la désertification: Rapport principal.p.135. http://www.unccd.int/actionprogrammes/africa/national/2002/morocco-fre.pdf. Cited 15 Apr 2009
23. Bengrich, M. (1988). La désertification dans le bassin de Guercif (Maroc oriental): étude de géographie physique. Thèse de doctorat université Avignon, France, pp 265. http://www.secheresse.info/spip.php?article7744
24. Lahlaoi, H., Rhinane, H., Hilali, A., Lahssini,S., & Moukrim, S. (2017). Desertification assessment using MEDALUS model in watershed Oued El Maleh, Morocco. Geosciences pp. 7- 50. https://doi.org/10.3390/GEOSCIENCES7030050
25. Lamqadem, A.A., Saber, H., & Pradhan, B. (2018). Quantitative assessment of desertification in an arid oasis using remote sensing data and spectral index techniques. Remote Sens 10(12):1862. https://doi.org/10.3390/RS10121862
26. Ech-Chahdi-Ouazani, K., Elbouhali. A., & Amyay, M. (2022). La cartographie et caracterisation de la sensibilité à la désetification dans le bassin versant du haut Ouergha(Rif central-Maroc) par l’approche MEDALUS. Geomaghreb. No. 16 (20). https://revues.imist.ma/index.php/Geomaghreb/article/view/30776
27. Boutallaka, M., El Mazi, M., Ben-Brahim, Y., & Houari, A. (2023). Mapping the sensitivity of land degradation in the Ouergha catchment (Morocco) using the MEDALUS approach. Eurasian Journal of Soil Science. https://doi.org/10.18393/ejss.1276119
28. El Hairchi, K., Benbrahim, Y., Ouiaboub, L., Limame, A., & Saadi, O., Nouayti, A. (2023). Desertification modeling in the Moroccan Middle Atlas using Sentinel 2A images and TCT indexes (case of the Ain Nokra Forest). Modeling Earth Systems and Environment. https://doi.org/10.1007/s40808-023-01752-z
29. Benabderrahmane. M.C., & Chenchouni, H.(2010). Assessing Environmental Sensitivity Areas to Desertification in Eastern Algeria using Mediterranean Desertification and Land Use “MEDALUS” Model. Int. J. of Sustainable Water & Environmental Systems Volume 1, No. 1. 5-10. https://d1wqtxts1xzle7.cloudfront.net/31932973/swes201001005010-libre
30. Huang, S., & Siegert, F. (2006). Land cover classification optimized to detect areas at risk of desertification in North China based on SPOT VEGETATION imagery. J. Arid Environ. 67, 308–327. [CrossRef]
31. Guang, Y., Dong, C., Xinlin, H., Aihua, L., Mingjie, Y., & Xiaolong, L. (2017). Land use change characteristics affected by water saving practices in Manas River Basin, China using Landsat satellite images. Int. J. Agric. Biol. Eng. 2017, 10, pp. 123–133. [CrossRef]
32. Wang, X., Hua, T., Lang, L., & Ma, W. (2017). Spatial differences of aeolian desertification responses to climate in arid Asia. Glob. Planet. Chang., 148, pp.22–28. [CrossRef]
33. Hostert, P., Roder, A., & Jarmer, T., & Udelhoven, T. (2001). The potential of remote sensing and GIS for desertification monitoring and assessment.,Ann Arid Zone 40:103–140. https://d1wqtxts1xzle7.cloudfront.net
34. Wang, T., Yan, CZ., Song, X., & Xie, JL. (2012). Monitoring recent trendsin the area of aeolian desertified land using Landsat images inChina’s Xinjiang region. ISPRS J Photogramm Remote Sens 68:184–190. https://doi.org/10.1016/j.isprsjprs.2012.01.001
35. Sayl, K.N., Sulaiman, SO., Kamel, A.H., Muhammad, NS., Abdullah, J., & AlAnsari, N. (2021). Minimizing the impacts of desertification in an arid region: a case study of the West Desert of Iraq. Adv Civ Eng. https://doi.org/10.1155/2021/5580286
36. Becerril-Piña, R., Díaz-Delgado, C., Mastachi-Loza, CA., & González-Sosa, E. (2016) . Integration of remote sensing techniques for monitor-ing desertification in Mexico. Hum Ecol Risk Assess an Int J 22:1323–1340. https://www.researchgate.net/publication/299653857
37. Zeng, Y., Feng, Z., & Xiang, N. (2006). Albedo-NDVI space and remote sensing synthesis index models for desertification monitoring. Sci Geogr Sin 26:75, https://doi: 10.13249/j.cnki.sgs.2006.01.75
38. Guo, B., & Wang, F. (2020). Dynamic monitoring of desertification in Naiman Banner based on feature space models with typical surface parameters derived from LANDSAT images. Land degradation & développement Volume31, Issue12 pp 1573-1592. https://doi:10.1002/ldr.3533
39. Wei, H., Wang, J., Cheng, K., Li, G., Ochir A., Davaasuren, D., & Chonokhuu, S. (2018). Desertification information extraction based on feature space combinations on the Mongolian plateau. Remote Sensing, 10(10), 1614. https://doi: 10.3390/rs10101614.
40. Limame, A., Hanchane, M., Zhar, M., El hairchi, K., & Lamaamri, M. (2022). Variabilité climatique et ses impacts sur le régime hydrologique de l’oued Améngous-Fellat, Haut basin de l’Oum-Rbia (Maroc). Acte de colloque Les risques hydroclimatiques et géomorphologiques : typologie, cartographie et gestion. Oujda. Pp 41-46. http://lettres.ump.ma/fr/actes-du-colloque-international-les-risques-hydroclimatiques-et-geomorphologiques-typologie-cartographie-et-gestion ).
41. Yilmaz H.M., Yakar M., Yildiz F., Karabork H., Kavurmaci M.M., Mutluoglu O., & Goktepe A. (2010). Determining rates of erosion of an earth pillar by terrestrial laser scanning. Arab. J. Sci. Eng. 35(2A), 163–172 (2010)
42. Lecompte, M. (1969). La végétation du Moyen Atlas central : esquisse phyto-écologique et carte des séries de végétation au 1/200000. R.G.M., pp. 3 - 34. Rabat.
43. Lecompte, M., & Lepoutre, B. (1975). Bilan de l’eau et conditions d’existence de la Cédraie dans le Moyen Atlas Basaltique. An. Recher. Forest. Au Maroc. T15. pp : 92 - 269.
44. Termier, H. (1936). Etude géologique sur le Maroc central et la Moyen Atlas septentrional. Notes et mém. Serv. Géol. Maroc, N°33, 1566p.
45. Martin, J. (1981). Le Moyen Atlas Central : étude géomorphologique. Thèse d’état, paris 7, Ed. Serv. Géol. Maroc, n° 258. https://www.persee.fr/doc/rga_0035
46. Demirel, Y., & Türk, N. (2024). Automatic detection of active fires and burnt areas in forest areas using optical satellite imagery and deep learning methods. Mersin Photogrammetry Journal, 6 (2), 66-78. https://doi.org/10.53093/mephoj.1575877
47. Zanchetta, A., Bitelli, G., & Karnieli, A. (2016). Monitoring desertification by remote sensing using the Tasselled Cap transform for long-term change detection. Nat Hazards 83:223–237. https://link.springer.com/article/10.1007/s11069-016-2342-9
48. Rouse, J. W., Haas R. H., Schell J. A., & Deering D. W. (1973). Monitoring Vegetation Systems in the Great Plains with ERTS. In Paper presented at the Third ERTS Symposium, NASA SP-351, Vol.I, December 10-14, Washington, DC: NASA: 309-317. https://www.scirp.org/journal/home?journalid=114
49. Tucker, C. J. (1979). Red and photographic infrared linear combinations for monitoring vegetation. Remote sensing of Environment, 8(2), 127-150. http://dx.doi.org/10.1016/0034-4257(79)90013-0
50. Zhao, H.L., Li, J., Liu, R.T,. Zhou, R.L., Qu, H., & Pan, C.C. (2014). Effects of desertification on temporal and spatial distribution of soil macro-arthropods in Horqin sandy grassland, Inner Mongolia. Geoderma 223: pp.62–67. https://doi.org/10.1016/J.GEODERMA.2014.01.026
51. Ma, Z., Xie, Y., Jiao, J., Wang, X. (2011). The construction and application of an Aledo-NDVI based desertification monitoring model. Procedia Environ Sci 10:2029–2035. https://doi.org/10.1016/j.proenv.2011.09.318
52. Liang, S., Shuey, C.J., Russ, A.L., & Fang. H. (2003). Narrowband to broadband conversions of land surface albedo: II Validation. Remote Sensing of Environment 84 1:25-41 https://doi:10.1016/S0034-4257(02)00068-8
53. 53. Yakar, M. (2011). Using close range photogrammetry to measure the position of inaccessible geological features. Experimental Techniques, 35(1), 54-59.
54. Wang, S., Grant, RF., Verseghy, D.L., & Black, TA. (2002). Modelling carbon dynamics of boreal forest ecosystems using the Canadian Land Surface Scheme. Clim Change 55:pp.451–477. http://doi:10.1023/A:1020780211008
55. Xiao, J., Shen, Y., Tateishi, R., & Bayaer, W. (2006). Development of topsoil grain size index for monitoring desertification in arid land using remote sensing. Int J Remote Sens 27:pp. 2411–2422. http://dx.doi.org/10.1080/01431160600554363
56. Yakar, M., Yilmaz, H. M., & Yurt, K. (2010). The effect of grid resolution in defining terrain surface. Experimental Techniques, 34(6), 23-29
57. Kauth, R., & Thomas, G. (1976). The tasselled cap a graphic description of the spectral-temporal development of agricultural crops as seen by LANDSAT. LARS symposia. June 29 - July 1, pp. 38-51. https://docs.lib.purdue.edu/lars_.
58. Jenks, G.F. (1963). Generalization in statistical mapping. Ann Assoc Am Geogr 53:15–26. . [CrossRef]
59. Pan, J., & Li, T. (2013). Extracting desertification from Landsat TM imagery based on spectral mixture analysis and Albedo-Vegetation feature space. Nat Hazards 68:915–9 https://link.springer.com/article/10.1007/s11069-013-0665-3
60. Gheshlaghi,A,G., Feizizadeh, B., Blaschke, T., Lakes, T ., & Tajbar, S. (2020). Forest fire susceptibility modeling using hybrid approaches.transaction in Gis, 25(1). https://doi.org/10.1111/tgis.12688.
61. Yakar, M., Yıldız, F., Uray, F., & Metin, A. (2010, June). Photogrammetric Measurement of The Meke Lake and Its Environment with Kite Photographs to Monitoring of Water Level to Climate Change. In ISPRS Commission V Mid-Term Symposium (pp. 613-616).
62. Da, Silva, T.G.F.d., Cruz Neto,J.F.d., Jardim, A.M.d.R.F., Souza, C.A.A.d., Araújo Júnior, G.d.N., Silva, M.V.d., Silva, J.L.B.d., Carvalho, A.A.d., Montenegro, A.A.d.A., & de Souza, L.S.B. (2024). RisDes_Index: An Index for Analysing the Advance of Areas Undergoing Desertification Using Satellite. Data. Agri Engineering, 6, pp.1150–1174. https://doi.org/10.3390/agriengineering6020066
63. Wang, G.J., & Zhang, J.C. (2006). Analysis of grassland desertification due to coal mining based on remote sensing - An example from huolinheopen-cast coalmine. Journal of China University of Mining and Technology, 10(6), 917–25. https://dx.doi.org/10.11834/jrs.200606134
64. Djeddaoui, F., Chadli, M., & Gloaguen, R. (2017). Desertification Susceptibility Mapping Using Logistic Regression Analysis in the Djelfa Area, Algeria, Remote Sensing. 2017, 9(10), 1031. https://doi.org/10.3390/rs9101031
65. Benslimane, M., Hamimed, A., Elzerey, W., Khaldi, A., & Mederbal, K. (2021). Analyse et suivi du phénomène de la désertification en Algérie du nord, VertigO 8(3):Ppp.1-97. https://doi.org/10.4000/vertigo.6782
66. Mihi, A., Ghazela, R., & Wissal, D. (2022). Mapping potential desertifcation prone areas in North Eastern Algeria using logistic regression model, GIS, and remote sensing techniques. Environmental Earth Sciences. https://www.researchgate.net/publication/362193731
67. Elkhabaz, M., Boumaaza,T., & Aoughar, M. (2024). Modélisation spatiale du phénomène de désertification par l'approche MEDALUS dans le Bassin Central de la Moulouya, Questions, théories et méthodologies en sciences humaines et sociales Publications du Faculté des lettres et des Sciences Humaines, Mohammadia.pp. 68-88.
68. Crist, E.P. Laurin, R., & Cicone, R.C. (1986). Vegetation and Soils Information Contained in Transformed Thematic Mapper Data. Proceedings of International Geoscience and Remote Sensing 86 Symposium, Zurich, Switzerland. https://www.scirp.org/reference/referencespapers?referenceid=2089836
69. Lamchin, M., Lee, J.Y., Lee, W.K., Lee, E.J., Moonil, K., Lim, C.H.A., Choi, H.A.b., & Kim, S.R. (2016). Assessment of land cover change and desertification using remote sensing technology in a local region of Mongolia. Adv Sp Res 57:64. https://www.researchgate.net/deref/http%3A%2F%2Fdx.doi.org%2F10.1016%2Fj.asr.2015.10.006?_tp=eyJjb250ZXh0Ijp7ImZpcnN0UGFnZSI6InB1YmxpY2F0aW9uIiwicGFnZSI6InB1YmxpY2F0aW9uIiwicHJldmlvdXNQYWdlIjoiX2RpcmVj
70. Yaman, Ş., & Tunç Görmüş, E. (2025). Sentinel-2 ve Landsat-8 ile Bulut Tabanlı Orman Yangın Analizi. Geomatik, 10(3), 316-330. https://doi.org/10.29128/geomatik.1603707
71. Baytar, İ. (2025). Arazi Kullanımının Coğrafi Bilgi Sistemleri (CBS) ile Haritalanması ve Analizi: Van Şehri Örneği. Geomatik, 11(1), 1-16. https://doi.org/10.29128/geomatik.1673220
72. Baytar, İ. (2025). Arazi Kullanımının Coğrafi Bilgi Sistemleri (CBS) ile Haritalanması ve Analizi: Van Şehri Örneği. Geomatik, 11(1), 1-16. https://doi.org/10.29128/geomatik.1673220
73. Eyi, G., & Buğdaycı, İ. (2024). Uzaktan algılama yöntemleri ile yangın şiddetinin tespiti: Yunanistan Rodos Adası orman yangını örneği. Geomatik, 9(3), 348-360. https://doi.org/10.29128/geomatik.1481708
74. Eyi, G., & Buğdaycı, İ. (2024). Uzaktan algılama yöntemleri ile yangın şiddetinin tespiti: Yunanistan Rodos Adası orman yangını örneği. Geomatik, 9(3), 348-360. https://doi.org/10.29128/geomatik.1481708
75. Yakar M, Yılmaz H M & Mutluoǧlu Ö (2010). Comparative evaluation of excavation volume by TLS and total topographic station based methods. Lasers in Eng,19, 331-345.
76. Ünel, F. B., Kuşak, L., Yakar, M., & Doğan, H. (2023). Coğrafi bilgi sistemleri ve analitik hiyerarşi prosesi kullanarak Mersin ilinde otomatik meteoroloji gözlem istasyonu yer seçimi. Geomatik, 8(2), 107-123. https://doi.org/10.29128/geomatik.1136951