Land use land cover change detection by using remote sensing in Meknes province, Morocco with an indicator based (DPSIR) approach

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Print ISSN : 0970-4078.
Online ISSN : 2229-4473.
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Doi: 10.1007/s42535-024-01110-z
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Keywords: Land use land cover (LULC), Diachronic analysis, Remote sensing, Supervised classification, Kappa index


Abstract


Land use and land cover changes (LULCC) are key drivers of ecosystem transformations at a global scale. This study explores the spatio-temporal transformations of LULC in various ecosystems within the Meknes prefecture, Morocco, with two main objectives: first, to analyze the dynamics of LULC changes over a 22-year period (from 2000 to 2021) and second, to identify the driving factors behind these transformations using the DPSIR (Driving Forces-Pressures-States-Impacts-Responses) conceptual framework. The study relies on remote sensing techniques and the analysis of satellite images from Landsat 7 ETM+ (2000, 2010) and Landsat 8 OLI/TIRS (2021). A supervised image classification was conducted using the Maximum Likelihood Classifier (MLC), with accuracy assessed by the Kappa index, which increased from 0.7529 in 2000 to 0.8057 in 2021. The overall accuracy of this classification also improved, rising from 82.92 to 86.53% over the same period. The analysis reveals significant changes in ecosystem composition, with a decrease in Dense Forest (DF) by -0.24%, Bushland/Sparse (BS) by -0.74%, Plantations (PL) by -0.53%, Barren/Rocky Land (BR) by -1.59%, and Barren Land (BL) by -1.60%. Conversely, there has been an increase in Agricultural Land (AG) by 0.36%, Moderately Dense Forest (MDF) by 0.39%, and Urbanized areas (UR) by 0.91%. These spatio-temporal changes result from multiple influences exerting pressure on the various ecosystems in the region, thus highlighting the need to strengthen conservation policies and adopt sustainable management strategies to reduce degradation and promote sustainable development in this study area.


Land use land cover (LULC), Diachronic analysis, Remote sensing, Supervised classification, Kappa index


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References


 

 


Ahmad A, Quegan S (2013) Comparative analysis of supervised and unsupervised classification on multispectral data. Appl Math Sci 7(73–76):3681–3694. https://doi.org/10.12988/ams.2013.34214


Amoussou E, Totin Vodounon SH, Hougni A et al (2017) Changements Environnementaux et vulnérabilité des écosystèmes dans le bassin-versant béninois du fleuve Niger. Int J Biol Chem Sci 10(5):2183. https://doi.org/10.4314/ijbcs.v10i5.20


Atwah W (2021) Land Use and Land Cover Change Impact on sustainability in the United Arab Emirates: a Big-Data Approach using Google Earth Engine. ProQuest Diss Theses, p 243


Avila-Flores G, Hinojosa-Arango G, Juárez-Mancilla J, Arizpe-Covarrubias O (2017) The use of the dspir framework to estimate impacts of urbanization on mangroves: a case study from La Paz, Baja California Sur, Mexico. WIT Trans Ecol Environ 223:459–469. https://doi.org/10.2495/SC170401


Ayad NA, Ayad AA, El Khalidi K, Habib A, Charif A (2023) Remote sensing and Meteorological indexes of Drought using Open Short Time-Series Data in Doukkala Region, Morocco. Ecol Eng Environ Technol 24(2):1–10. https://doi.org/10.12912/27197050/156962


Barbache A, Beghami Y, Benmessaoud H (2018) Study and diachronic analysis of forest cover changes of Belezma-Algeria. Geogr Pannonica 22(4):253–263. https://doi.org/10.5937/gp22-18806


Barnagaud Jyves (2011) L ’avifaune commune face aux changements anthropiques: comprendre les facteurs de vulnérabilité à travers la structure et les variations de la niche écologique


Bergeri I, Michel R, Boutin JP (2002) Everything (or almost everything) about the Kappa coefficient. Med Trop (Mars) 62(6):634–636


Bodart C, Eva H, Beuchle R et al (2011) Pre-processing of a sample of multi-scene and multi-date landsat imagery used to monitor forest cover changes over the tropics. ISPRS J Photogramm Remote Sens 66(5):555–563. https://doi.org/10.1016/j.isprsjprs.2011.03.003


Boubekraoui H, Maouni Y, Ghallab A, Draoui M, Maouni A (2023) Spatio-temporal analysis and identification of deforestation hotspots in the Moroccan western Rif. Trees Forests People 12:100388


Bradley P, Yee S (2015) Using the DPSIR Framework to develop a conceptual model. Technical Support Document Office, p 82


Buchet R (2012) Directive Cadre sur l ’ Eau: les pressions anthropiques et leur impact sur les indicateurs de l ’ état écologique des masses d ’ eau littorales de la façade Synthèse bibliographique. Synthèse Bibliogr Hocer/Ifremer


Debolini M, Valette E, François M, Chéry JP (2015) Mapping land use competition in the rural–urban fringe and future perspectives on land policies: a case study of Meknès (Morocco). Land Use Policy 47:373–381


Deng Y, Wang S, Bai X, Tian Y, Wu L, Xiao J, Chen F, Qian Q (2018) Relationship among land surface temperature and LUCC, NDVI in typical karst area. Sci Rep 8(1):1–12. https://doi.org/10.1038/s41598-017-19088-x


Directorate General of Local Authorities (2015) Monographie générale, Région de Fès-Meknès. https://www.region-fes-meknes.ma/fr/publications/monographie-de-la-region-fes-meknes/


Dupont P (2020) Observatoire GE-EN-VIE: Système D’ indicateurs DPSIR et o utils de communication sur la biodiversité du canton de Genève. (405):111. https://projets.ge-en-vie.ch/uploads/1600871452Dupont_Pauline_Memoire_masterfinal.pdf


El Fallah K, Adiba A, Charafi J, Ouhakki H, El Kharrim K, Belghyti D (2024a) Modeling current and future pomegranate distribution under climate change scenarios in the Fes-Meknes region, Morocco. Euro-Mediterranean J Environ Integr 1–15


El Fallah K, Ouhakki H, Adiba A, El Kharrim K, Belghyti D (2024b) Links between land use change, land surface temperature, and partridge distribution–an analysis of environmental factors. Ecol Eng Environ Technol 25


El Hafyani M, Essahlaoui A, Van Rompaey A, Mohajane M, El Hmaidi A, El Ouali A et al (2020) Assessing regional scale water balances through remote sensing techniques: a case study of Boufakrane River Watershed, Meknes Region, Morocco. Water 12(2):320


Elias E, Seifu W, Tesfaye B, Girmay W (2019) Impact of land use/cover changes on lake ecosystem of Ethiopia central rift valley. Cogent Food Agric 5(1). https://doi.org/10.1080/23311932.2019.1595876


Foley JA, DeFries R, Asner GP et al (2005) Global consequences of land use. Science 309(5734):570–574


Hamadou O, Oumani AA, Yahou H, Morou B, Mahamane A (2022) Modélisation de la distribution spatiale de la girafe (Giraffa camelopardalis peralta, Linnaeus 1758) de l’Afrique de l’Ouest pour sa conservation Au Niger. Int J Biol Chem Sci 15(6):2486–2499. https://doi.org/10.4314/ijbcs.v15i6.19


Hammada S (2007) Etudes sur la vegetation des zones humides du Maroc. Catalogue et Analyse de la Biodiversité Floristique et Identification des principaux Groupements Végétaux. Thèse Dr dans l’écologie végétale Univ Mohamed 5 – Rabat N° 2328


hcp (2017) Monographie de la Préfecture de Meknès. https://www.hcp.ma/region-meknes/Monographie-de-la-Prefecture-de-Meknes_a135.html





Hili A, Bissour R, Jaa F, Reddad H, El Jouhary Y (2022) Etude De La Dynamique spatio-temporelle de la forêt des Ait Daoud Ou Ali (Haut Atlas central, Maroc) en utilisant les techniques géospatiales. Rev Estud Andaluces 43:208–225


Jaskuła J, Sojka M (2019) Assessing spectral indices for detecting vegetative overgrowth of reservoirs. Pol J Environ Stud 28(6):4199–4211. https://doi.org/10.15244/pjoes/98994


Kong F, Li X, Wang H, Xie D, Li X, Bai Y (2016) Land cover classification based on fused data from GF-1 and MODIS NDVI time series. Remote Sens 8(9). https://doi.org/10.3390/rs8090741


Lambin EF, Geist HJ, Lepers E (2003) Dynamics of land-use and land-cover change in tropical regions. Annu Rev Environ Resour 28(1):205–241


Lu M, Wang S, Wang X et al (2022) An Assessment of Temporal and Spatial Dynamics of Regional Water Resources Security in the DPSIR Framework in Jiangxi Province, China. Int J Environ Res Public Health 19(6). https://doi.org/10.3390/ijerph19063650


Lyu X, Wang Y, Niu S, Peng W (2022) Spatio-temporal pattern and influence mechanism of cultivated land system resilience: case from China. Land 11(1). https://doi.org/10.3390/land11010011


MAPMDREF M (2018) Bilan et impacts 2008–2018


Maxim L, Spangenberg JH, O’Connor M (2009) An analysis of risks for biodiversity under the DPSIR framework. Ecol Econ 69(1):12–23. https://doi.org/10.1016/j.ecolecon.2009.03.017


Mohd Hasmadi I, Pakhriazad HZ, Shahrin MF (2009) Evaluating supervised and unsupervised techniques for land cover mapping using remote sensing data. Malaysian J Soc Sp 5(1):1–10


Moshinsky M (1959) Enjeux et Modes d’intégration de La Dimension Socio-Économique Dans La Surveillance Environnementale. Vol 13


Moumni A, Belghazi T, Maksoudi B, Lahrouni A (2021) Argan Tree (Argania Spinosa (L.) Skeels) Mapping based on Multisensor Fusion of Satellite Imagery in Essaouira Province, Morocco. J Sens 2021. https://doi.org/10.1155/2021/6679914


Nasiri V, Deljouei A, Moradi F, Sadeghi SMM, Borz SA (2022) Land use and land cover mapping using Sentinel-2, Landsat-8 satellite images, and Google Earth Engine: a comparison of two composition methods. Remote Sens 14(9):1977. https://doi.org/10.3390/rs14091977


Nguyen HTT, Doan TM, Tomppo E, McRoberts RE (2020) Land use/land cover mapping using multitemporal sentinel-2 imagery and four classification methods-A case study from Dak Nong, Vietnam. Remote Sens 12(9):1–28. https://doi.org/10.3390/RS12091367


Nowak MM, Dziób K, Ludwisiak L, Chmiel J (2020) Mobile GIS applications for environmental field surveys: a state of the art. Glob Ecol Conserv 23. https://doi.org/10.1016/j.gecco.2020.e01089


Ping W, Fu J, Qiao W, Yasir M, Hui S, Hossain MS, Nazir S (2021) Decision support system for hyperspectral remote-sensing data of Yellow River Estuary, China. Sci Prog 2021. https://doi.org/10.1155/2021/1376167


Rasool R, Fayaz A, Shafiq M, ul, Singh H, Ahmed P (2021) Land use land cover change in Kashmir Himalaya: linking remote sensing with an indicator based DPSIR approach. Ecol Indic 125. https://doi.org/10.1016/j.ecolind.2021.107447


Rwanga SS, Ndambuki JM (2017a) Accuracy Assessment of Land Use/Land Cover classification using remote sensing and GIS. Int J Geosci 08(04):611–622. https://doi.org/10.4236/ijg.2017.84033


Rwanga SS, Ndambuki JM (2017b) Accuracy assessment of land use/land cover classification using remote sensing and GIS. Int J Geosci 8(4):611–622. https://doi.org/10.4236/ijg.2017.84033


SADDIK M (2017) Application of the DPSIR approach to a Moroccan coastal zone: case of the Nador lagoon. Environ Water Sci Public Heal Territ Intell J 1(3):1–6


Scopélitis J, Andréfouët S, Phinn S et al (2009) Changes of coral communities over 35 years: integrating in situ and remote-sensing data on Saint-Leu reef (la Réunion, Indian Ocean). Estuar Coast Shelf Sci 84(3):342–352. https://doi.org/10.1016/j.ecss.2009.04.030


Seto KC, Güneralp B, Hutyra LR (2012) Global forecasts of urban expansion to 2030 and direct impacts on biodiversity and carbon pools. Proc Natl Acad Sci 109(40):16083–16088





Toumi S, Meddi M, Mahé G, Brou YT (2013) Cartographie De l’érosion dans le bassin versant de l’Oued mina en Algérie par télédétection et SIG. Hydrol Sci J 58(7):1542–1558. https://doi.org/10.1080/02626667.2013.824088


Verburg PH, Neumann K, Nol L (2011) Challenges in using land use and land cover data for global change studies. Global Change Biol 17(2):974–989


Vivekananda GN, Swathi R, Sujith AVLN (2021) Multi-temporal image analysis for LULC classification and change detection. Eur J Remote Sens 54(sup2):189–199. https://doi.org/10.1080/22797254.2020.1771215


Wang B, Yu F, Teng Y, Cao G, Zhao D, Zhao M (2022) A SEEC Model based on the DPSIR Framework Approach for Watershed Ecological Security Risk Assessment: a Case Study in Northwest China. Water (Switzerland) 14(1). https://doi.org/10.3390/w14010106


Wynd CA, Schmidt B, Schaefer MA (2003) Two quantitative approaches for estimating content validity. West J Nurs Res 25(5):508–518. https://doi.org/10.1177/0193945903252998


Xiang H, Xi Y, Mao D, Mahdianpari M, Zhang J, Wang M, Jia M, Yu F, Wang Z (2023) Prediction of potentially suitable distribution areas for Prunus tomentosa in China based on an optimized MaxEnt model Yangtze River Basin. Global Ecol Conserv 42(October 2022):e02397. https://doi.org/10.1016/j.gecco.2023.e02397

 

 

 


Acknowledgements



Author Information


El fallah Kamal
Department of Biology, Faculty of Science, University Ibn Toufail BP, Kenitra, Morocco
kamal-meknassi@outlook.com
El kharrim Khadija
Department of Biology, Faculty of Science, University Ibn Toufail BP, Kenitra, Morocco


Belghyti Driss
Department of Biology, Faculty of Science, University Ibn Toufail BP, Kenitra, Morocco