Long-Term Monitoring of Transformation from Pastoral to Agricultural Land Use Using Time-Series Landsat Data in the Feija Basin (Southeast Morocco)

  • Atman Ait Lamqadem
  • Hafid Saber
  • Biswajeet PradhanEmail author
Original Article


The expansion of agricultural land at the cost of pastoral land is the common cause of land degradation in the arid areas of developing countries, especially in Morocco. This study aims to assess and monitor the transformation of pastoral land to agricultural land in the arid environment of the Feija Basin (Southeast of Morocco) and to find the key drivers and the issues resulting from this transformation. Spectral mixture analysis was applied to multi-temporal (1975–2017) and multi-sensor (i.e. Multi-spectral Scanner, Thematic Mapper, and Operational Land Imager) Landsat satellite images, from which land use classifications were derived. The remote sensing data in combination with ground reference data (household level), groundwater and climate statistics were used to validate and explain the derived land use change maps. The results of the spatiotemporal changes in agricultural lands show two patterns of changes, a middle expansion from 1975 to 2007, and a rapid expansion from 2008 to 2017. In addition, the overall accuracy demonstrated a high accuracy of 94.4%. In 1975 and 1984, the agricultural lands in Feija covered 0.17 km2 and 1.32 km2, respectively, compared with 20.10 km2 in 2017. Since the adoption of the Green Morocco Plan in 2008, the number of watermelon farms and wells has increased rapidly in the study area, which induced a piezometric level drawdown. The results show that spectral mixture analysis yields high accuracies for agricultural lands extraction in arid dry lands and accounts for mixed pixels issues. Results of this study can be used by local administrators to prepare an effective environmental management plan of these fragile drylands. The proposed method can be replicated in other regions to analyse land transformation in similar arid conditions.


Land use monitoring Landsat images Linear-mixture analysis GIS Remote sensing Morocco 



We would like to thank the National Center of the Scientific and Technique Research for the scholarship of PhD student A.A.L. (Scholarship No. 1UCD2016). Our acknowledgments are also addressed to the Regional Office of the Agricultural Development for providing the statistical data and WorldClim for the climate data. We thank the Chouaïb Doukkali University for the logistical support during the field works of this study.


This research is supported by the Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS), University of Technology Sydney (UTS) under Grant number 321740.2232335 and 321740.2232357.


  1. ABHSM (1997) Etude d’approvidionnement en eau potable des populations rurales de la province de Zagora. Agence des bassines hydrauliques de Souss Mass, Direction de Ouarzazate, Ouarzazate, p 70Google Scholar
  2. ABHSM (2014) Etude hydrologique de la nappe de la Feija. Agence des bassines hydrauliques de Souss Mass, Direction de Ouarzazate, Ouarzazate, p 38Google Scholar
  3. Abu-Allaban M, El-Naqa A, Jaber M, Hammouri N (2015) Water scarcity impact of climate change in semi-arid regions: a case study in Mujib basin, Jordan. Arab J Geosci 8:951–959. CrossRefGoogle Scholar
  4. Abdullahi S, Pradhan B, Mansor S, Shariff ARM (2015) GIS-based modeling for the spatial measurement and evaluation of mixed land use development for a compact city. GISci Remote Sens 52(1):18–39CrossRefGoogle Scholar
  5. Adams JB, Smith MO, Johnson PE (1986) Spectral mixture modeling: a new analysis of rock and soil types at the Viking Lander 1 site. J Geophys Res 91:8098–8112. CrossRefGoogle Scholar
  6. Adams JB, Sabol DE, Kapos V, Almeida Filho R, Roberts DA, Smith MO, Gillespie AR (1995) Classification of multispectral images based on fractions of endmembers: application to land-cover change in the Brazilian Amazon. Remote Sens Environ 52:137–154. CrossRefGoogle Scholar
  7. Afrasinei GM, Melis MT, Arras C, Pistis M, Buttau C, Ghiglieri G (2018) Spatiotemporal and spectral analysis of sand encroachment dynamics in southern Tunisia. Eur J Remote Sens 51:352–374. CrossRefGoogle Scholar
  8. Aghdam IN, Varzandeh MHM, Pradhan B (2016) Landslide susceptibility mapping using an ensemble statistical index (Wi) and adaptive neuro-fuzzy inference system (ANFIS) model at Alborz Mountains (Iran). Environ Earth Sci 75(7):553. CrossRefGoogle Scholar
  9. Allbed A, Kumar L, Sinha P (2014) Mapping and modelling spatial variation in soil salinity in the Al Hassa Oasis based on remote sensing indicators and regression techniques. Remote Sens 6:1137–1157. CrossRefGoogle Scholar
  10. Badraoui M (2006) Connaissance et utilisation des ressources en sol au Maroc. Contribution in Rapport sur le Développement Humain (RDH50) Maroc (50 ans de Développement Humain et perspectives 2025, Rapport Général), report number: GT8-3. Royal Institute for Strategic Studies (IRES), pp 91–117. Accessed 10 Feb 2018
  11. Brahim YA, Saidi ME, Kouraiss K, Sifeddine A, Bouchaou L (2017) Analysis of observed climate trends and high resolution scenarios for the 21st century in Morocco. J Mater Environ Sci 8:1375–1384Google Scholar
  12. Dawelbait M, Dal Ferro N, Morari F (2017) Using Landsat images and spectral mixture analysis to assess drivers of 21-year LULC changes in Sudan. Land Degrad Dev 28:116–127. CrossRefGoogle Scholar
  13. Elmore AJ, Mustard JF, Manning SJ, Lobell DB (2000) Quantifying vegetation change in semiarid environments: precision and accuracy of spectral mixture analysis and the normalized difference vegetation index. Remote Sens Environ 73:87102. CrossRefGoogle Scholar
  14. FAO (1980) Réponse des rendements à l’eau. FAO, Rome, p 235Google Scholar
  15. FAO (2017) The future of food and agriculture—trends and challenges. Rome, p 180. Accessed 15 Jan 2018
  16. Faysse N (2015) The rationale of the Green Morocco Plan: missing links between goals and implementation. J N Afr Stud 20:622–634. CrossRefGoogle Scholar
  17. Fernández-Manso Ó (2015) Spectral mixture analysis and object-based image analysis for forestry applications. Doctoral thesis, University of LeónGoogle Scholar
  18. Foley JA, Ramankutty N, Brauman KA, Cassidy ES, Gerber JS, Johnston M, Mueller ND, O’Connell C, Ray DK, West PC, Balzer C, Bennett EM, Carpenter SR, Hill J, Monfreda C, Polasky S, Rockström J, Sheehan J, Siebert S, Tilman D, Zaks DPM (2011) Solutions for a cultivated planet. Nature 478:337–342. CrossRefGoogle Scholar
  19. 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. CrossRefGoogle Scholar
  20. Hamad R, Balzter H, Kolo K (2018) Predicting land use/land cover changes using a CA-Markov model under two different scenarios. Sustainability 10:3421. CrossRefGoogle Scholar
  21. Han X, Han L (2015) Estimating fractional vegetation cover of Oasis in Tarim Basin, China, using dimidiate fractional cover model. Proc SPIE 9808:1–8. Google Scholar
  22. HCP (2018) High Commission of the Plan of the Kingdom of Morocco. Accessed 04 Aug 2018
  23. Jia K, Li Y, Liang S, Wei X, Yao Y (2017) Combining estimation of green vegetation fraction in an arid region from Landsat 7 ETM+ data. Remote Sens 9:1–15. Google Scholar
  24. Kartya Y, Iwata S, IInamura T (2005) Geomorphology and pastoral-agricultural land use in Cotahuasi and Puica, Southern Peruvian Andes. Geogr Rev Jpn 78:842–852. CrossRefGoogle Scholar
  25. Klose A (2009) Soil characteristics and soil erosion by water in a semi-arid catchment (Wadi Drâa, South Morocco) under the pressure of global change. Université de Bonn, Bonn, p 378Google Scholar
  26. Klose S, Reichert B (2006) Groundwater management in the middle Drâa-River basin (South-Morocco). In: 14th International soil conservation organization conference. Marrakech, Morocco, pp 1–4Google Scholar
  27. Lamqadem AA, Saber H, Rahimi A (2017) Spatiotemporal changes of vegetation in the Middle Draa Valley Oasis: a study case of M’ hamid El Ghizlane Oasis (Morocco). Eur Sci J 13:115–132. Google Scholar
  28. Lamqadem AA, Pradhan B, Saber H, Rahimi A (2018a) Desertification sensitivity analysis using MEDALUS model and GIS: a case study of the Oases of Middle Draa Valley, Morocco. Sensors 18:2230. CrossRefGoogle Scholar
  29. Lamqadem A, Saber H, Pradhan B (2018b) Quantitative assessment of desertification in an arid oasis using remote sensing data and spectral index techniques. Remote Sens 10(12):1862CrossRefGoogle Scholar
  30. Li Y, Wang H, Li XB (2015) Fractional vegetation cover estimation based on an improved selective endmember spectral mixture model. PLoS One 10(4):e0124608. CrossRefGoogle Scholar
  31. Li S, Sun Z, Tan M, Guo L, Zhang X (2018) Changing patterns in farming–pastoral ecotones in China between 1990 and 2010. Ecol Indic 89:110–117. CrossRefGoogle Scholar
  32. Long JA, Nelson TA, Wulder MA (2010) Characterizing forest fragmentation: distinguishing change in composition from configuration. Appl Geogr 30:426–435. CrossRefGoogle Scholar
  33. Lu D (2006) Spectral mixture analysis of ASTER images for examining the relationship between urban thermal features and biophysical descriptors in Indianapolis, Indiana, USA. Remote Sens Environ 104:157–167. CrossRefGoogle Scholar
  34. MAPM (2013) Note de veille: Filière pastèque. Rabat, Morocco, p 19Google Scholar
  35. Masoud AA (2014) Predicting salt abundance in slightly saline soils from Landsat ETM+ imagery using spectral mixture analysis and soil spectrometry. Geoderma 217–218:45–56. CrossRefGoogle Scholar
  36. Matinfar HR, Roodposhti MS (2012) Decision tree land use/land cover change detection of Khoram Abad city using Landsat imagery and ancillary SRTM data. Middle East J Sci Res 13(8):40454053Google Scholar
  37. McPeak JG, Little PD (2018) Mobile peoples, contested borders: land use conflicts and resolution mechanisms among Borana and Guji Communities, Southern Ethiopia. World Dev 103:119–132. CrossRefGoogle Scholar
  38. Medjani F, Aissani B, Labar S, Djidel M, Ducrot D, Masse A, Hamilton CML (2017) Identifying saline wetlands in an arid desert climate using Landsat remote sensing imagery. Application on Ouargla Basin, southeastern Algeria. Arab J Geosci 10:9–10. CrossRefGoogle Scholar
  39. Meusburger K, Bänninger D, Alewell C (2010) Estimating vegetation parameter for soil erosion assessment in an alpine catchment by means of QuickBird imagery. Int J Appl Earth Obs Geoinf 12:201–207. CrossRefGoogle Scholar
  40. Mihi A, Tarai N, Chenchouni H (2017) Can palm date plantations and oasification be used as a proxy to fight sustainably against desertification and sand encroachment in hot drylands? Ecol Indic. Google Scholar
  41. Ouda S (2016) Major crops and water scarcity in Egypt: irrigation water management under changing climate. Springer International Publishing, Cham, p 126. CrossRefGoogle Scholar
  42. Pascual D, Pla E, Fons J, Abdul-Malak D (2017) Climate change impacts on water availability and human security in the intercontinental biosphere reserve of the Mediterranean (Morocco–Spain). Environmental change and human security in Africa and the Middle East. Springer International Publishing, Cham, pp 75–93. Google Scholar
  43. Peddle DR, Smith AM (2005) Spectral mixture analysis of agricultural crops: endmember validation and biophysical estimation in potato plots. Int J Remote Sens 26:4959–4979. CrossRefGoogle Scholar
  44. Pons X, Pesquer L, Cristóbal J, González-Guerrero O (2014) Automatic and improved radiometric correction of Landsat imagery using reference values from MODIS surface reflectance images. Int J Appl Earth Obs Geoinf 33:243–254CrossRefGoogle Scholar
  45. Pradhan B, Abokharima MH, Jebur MN, Tehrany MS (2014) Land subsidence susceptibility mapping at Kinta Valley (Malaysia) using the evidential belief function model in GIS. Nat Hazards 73(2):1019–1042CrossRefGoogle Scholar
  46. Proludra (1998) Feija d’Imssouffa: elements de comprehension. DEDRA/GTZ, Zagora, p 63Google Scholar
  47. Rahimon RM (2012) Evolution of land use in pastoral culture in Central Asia with special reference to Kyrgyzstan and Kazakhstan. Rangeland Stewardship in Central Asia. Springer, Dordrecht, pp 51–67. Google Scholar
  48. Roy DP, Wulder MA, Loveland TR, Allen RG, Anderson MC, Helder D, Irons JR, Johnson DM, Kennedy R, Scambos TA, Schaaf CB, Schott JR, Sheng Y, Vermote EF, Belward AS, Bindschadler R, Cohen WB, Gao F, Hipple JD, Hostert P, Huntington J, Justice CO, Kilic A, Kovalskyy V, Lee ZP, Lymburner L, Masek JG, McCorkel J, Shuai Y, Trezza R, Vogelmann J, Wynne RH, Zhu Z (2014) Landsat-8: science and product vision for terrestrial global change research. Remote Sens Environ 145:154–172. CrossRefGoogle Scholar
  49. Salih AAM, Ganawa E-T, Elmahl AA (2017) Spectral mixture analysis (SMA) and change vector analysis (CVA) methods for monitoring and mapping land degradation/desertification in arid and semiarid areas (Sudan), using Landsat imagery, Egypt. J Remote Sens Space Sci 20:S21–S29. Google Scholar
  50. Scarth PF, Röder A, Schmidt M (2010) Tracking grazing pressure and climate interaction—the role of Landsat fractional cover in time series analysis. In: Ben S et al. (eds) Proceedings of the 15th Australasian remote sensing and photogrammetry conference. Alice Springs, Australia, p 13.
  51. Schmidt M, Thamm HP, Menz G (2003) Long term vegetation change detection in an and environment using LANDSAT data. Geoinformation for European-wide integration. Millpress, Rotterdam, p 496Google Scholar
  52. Sedra MH (2015) Date palm status and perspective in Morocco. Date palm genetic resources and utilization. Springer, Dordrecht, pp 257–323. Google Scholar
  53. Smith MO, Johnson PE, Adams JB (1985) Quantitative determination of mineral types and abundances from reflectance spectra using principal components analysis. J Geophys Res 90:C797. CrossRefGoogle Scholar
  54. Smith MO, Ustin SL, Adams JB, Gillespie AR (1990) Vegetation in deserts: I. A regional measure of abundance from multispectral images. Remote Sens Environ 31:1–26. CrossRefGoogle Scholar
  55. Sraïri MT (2017) New challenges for the Moroccan agricultural sector to cope with local and global changes. Nova Science Publishers, Inc., New York, pp 165–188Google Scholar
  56. Sulieman HM (2018) Exploring the spatio-temporal processes of communal rangeland grabbing in Sudan. Pastoralism 8(1):14. CrossRefGoogle Scholar
  57. Tang Z, Ma J, Peng H, Wang S, Wei J (2017) Spatiotemporal changes of vegetation and their responses to temperature and precipitation in upper Shiyang river basin. Adv Space Res 6(5):969–979. CrossRefGoogle Scholar
  58. Teixido AL, Quintanilla LG, Carreño F, Gutiérrez D (2010) Impacts of changes in land use and fragmentation patterns on Atlantic coastal forests in northern Spain. J Environ Manag 91:879–886CrossRefGoogle Scholar
  59. Tilman D, Clark M (2015) Food, agriculture and the environment: can we feed the world and save the Earth? Daedalus 144:8–23. CrossRefGoogle Scholar
  60. Wang K, Franklin SE, Guo X, Cattet M (2010) Remote sensing of ecology, biodiversity and conservation: a review from the perspective of remote sensing specialists. Sensors 10:9647–9667. CrossRefGoogle Scholar
  61. Wang J, Huang Q, Huang J, Rozelle S, Wang J, Huang Q, Huang J, Rozelle S (2016) Water scarcity in Northern China. Managing water on China’s farms. Elsevier, Amsterdam, pp 3–19. CrossRefGoogle Scholar
  62. White MA, Asner GP, Nemani RR, Privette JL, Running SW (2000) Measuring fractional cover and leaf area index in arid ecosystems: digital camera, radiation transmittance, and laser altimetry methods. Remote Sens Environ 74:45–57. CrossRefGoogle Scholar
  63. Xie H, He Y, Zhang N, Lu H (2017) Spatiotemporal changes and fragmentation of forest land in Jiangxi Province, China. J For Econ 29(1):4–13. Google Scholar
  64. Xofis P, Poirazidis K (2018) Combining different spatio-temporal resolution images to depict landscape dynamics and guide wildlife management. Biol Conserv 218:10–17. CrossRefGoogle Scholar
  65. Yıldırım A, Öner MD (2015) Electrical conductivity, water absorption, leaching, and color change of Chickpea (Cicer arietinum L.) during soaking with ultrasound treatment. Int J Food Prop 18:1359–1372. CrossRefGoogle Scholar
  66. Zainabi AT (1989) Vers une disparition rapide du nomadisme au Sahara marocain: Le cas du Dra Moyen. Villes du monde arabe 20:49–62Google Scholar
  67. Zhang X, Liao C, Li J, Sun Q (2013) Fractional vegetation cover estimation in arid and semi-arid environments using HJ-1 satellite hyperspectral data. Int J Appl Earth Obs Geoinf 21:506–512. CrossRefGoogle Scholar
  68. Zhang X, Luo Y, Goh KS (2018) Modeling spray drift and runoff-related inputs of pesticides to receiving water. Environ Pollut 234:48–58. CrossRefGoogle Scholar
  69. Zhu Z (2017) Change detection using Landsat time series: a review of frequencies, preprocessing, algorithms, and applications. ISPRS J Photogramm Remote Sens 130:370–384. CrossRefGoogle Scholar
  70. Zohry AEH, Ouda SAH (2016) Crops intensification to face climate induced water scarcity in Nile Delta region. Management of climate induced drought and water scarcity in Egypt. Springer, Cham, pp 47–62. CrossRefGoogle Scholar

Copyright information

© King Abdulaziz University and Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Laboratory of Geodynamic and Geomatics, Department of Geology, Faculty of SciencesChouaïb DoukkaliEl JadidaMorocco
  2. 2.Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS), Faculty of Engineering and Information TechnologyUniversity of Technology SydneyUltimoAustralia

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