Detecção de Mudanças no Uso e na Cobertura da Terra Utilizando Séries Temporais Landsat na Bacia do Wadi Rdat, Marrocos

Autores

  • LAMIAE BELHAK Hassan II University, Department of Geography, Faculty of Arts and Humanities Mohammedia, Casablanca, Morocco https://orcid.org/0009-0004-2665-8617
  • Taj-din Rahmani Ibn Tofail University, Department of Geography, Faculty of Humanities and Social Sciences, Kenitra, Morocco https://orcid.org/0009-0003-5763-7766
  • M’hamed Nmiss Hassan II University, Department of Geography, Faculty of Arts and Humanities Mohammedia, Casablanca, Morocco
  • Abdelmajid Essami Hassan II University, Department of Geography, Faculty of Arts and Humanities Mohammedia, Casablanca, Morocco

DOI:

https://doi.org/10.22456/1807-9806.153402

Palavras-chave:

Uso e cobertura da terra, Análise espaço-temporal, SIG, Bacia do Wadi Rdat

Resumo

As mudanças no uso e na cobertura da terra (LULC) constituem um importante indicador da dinâmica ambiental, particularmente em regiões semiáridas, onde os recursos naturais são altamente sensíveis à pressão antrópica. A compreensão da evolução espaço-temporal da LULC é essencial para a gestão sustentável da terra e dos recursos hídricos. Este estudo analisa as mudanças de longo prazo da LULC na Bacia do Wadi Rdat, no centro do Marrocos, utilizando imagens multitemporais do satélite Landsat e técnicas baseadas em Sistemas de Informação Geográfica (SIG). Foi realizada uma análise diacrônica ao longo de 30 anos, entre 1990 e 2020, com base em dados de Landsat TM e OLI. A classificação supervisionada, baseada no algoritmo de máxima verossimilhança, foi aplicada para gerar mapas representativos de LULC de quatro anos. Foram identificadas seis principais classes de LULC: floresta, terras agrícolas, terras em pousio e pastagens, áreas construídas, terras nuas e corpos d’água. Os resultados indicam transformações significativas, caracterizadas por um declínio contínuo da cobertura florestal, mudanças dinâmicas nas terras agrícolas, uma expansão acentuada das terras nuas e um crescimento urbano gradual. Esses resultados evidenciam processos contínuos de degradação da terra e fornecem subsídios relevantes para o planejamento do uso da terra e para a gestão ambiental futura da bacia.

Downloads

Não há dados estatísticos.

Referências

Afenzar, M.; Achiban, H.; Abahrour , M.; Hmamouchi, M.; Senhaji, M.; Ennaji, N.; Halouan, S. 2025. Using Simulated Rainfall to Assess Water Erosion in the Aghrouz Watershed (Southern Rif, Morocco). Pesquisas em Geociências, 52(1): e146225. https://doi.org/10.22456/1807-9806.146225

Alvarez, C.I. & Govind, A. 2025. Assessing climate and land use changes in Morocco (2001–2023): from a geospatial and farmers’ perspective. Theoretical and Applied Climatology, 156: 420. https://doi.org/10.1007/s00704-025-05656-z

Arari, K.; Amhani, Z.; Tribak, A.; El-Ommal, M.; Laaraj, M.; Azagouagh, K. 2025. Analysis of land use changes and soil erosion in the Wadi Larbâa Basin (Eastern Pre-Rif, Morocco): a spatial assessment from 1984 to 2024. Mediterranean Geoscience Reviews, 7: 1007-1025. https://doi.org/10.1007/s42990-025-00200-7

Assede, E.S.P.; Orou, H., Biaou, S.S.H.; Geldenhuys, C.J.; Ahononga, F.C.; Chirwa, P.W. 2023. Understanding Drivers of Land Use and Land Cover Change in Africa: A Review. Current Landscape Ecology Reports, 8: 62-72. https://doi.org/10.1007/s40823-023-00087-w

Benbih, M.; Ouammou, A.; Nmiss, M.; Boukdoun, A.; Nait-Si, H. 2025. Impact of human activities on soil degradation and sustainability of oasis ecosystems in the Middle Draa (Morocco). Revista de Estudios Andaluces, 50: 266-285. https://doi.org/10.12795/rea.2025.i50.12

Ben-Said, M.; Chemchaoui, A.; Etebaai, I.; Taher, M. 2025. Land use and land cover changes in Morocco: Trends, research gaps, and perspectives. GeoJournal, 90: 44. https://doi.org/10.1007/s10708-024-11214-3

Chrif El Idrissi, M.C.; Er‑Riyahi Saber, E.; Al Mashoudi, A. 2024. Land use and land cover change analysis using geospatial techniques: A case study of the Dayet Aoua Watershed, Middle Atlas, Morocco. Environmental & Socio‑economic Studies, 12(4): 45-56. https://doi.org/10.2478/environ-2024-0024

Chrif El Idrissi, M.; El Attar, M.; Saber, E.R.; El Ghalbi, K. 2026. Four decades of land use and land cover change in the Ouiouane forest area (Middle Atlas, Morocco): A remote sensing and GIS-based assessment (1984–2024). Euro-Mediterranean Journal for Environmental Integration, 11: 87. https://doi.org/10.1007/s41207-025-01051-2

Cohen, J. 1960. A coefficient of agreement for nominal scales. Educational and Psychological Measurement, 20(1): 37-46. https://doi.org/10.1177/001316446002000104

Congalton, R.G. 1991. A review of assessing the accuracy of classifications of remotely sensed data. Remote Sensing of Environment, 37(1): 35-46. https://doi.org/10.1016/0034-4257(91)90048-B

Coppin, P.; Jonckheere, I.; Nackaerts, K.; Muys, B.; Lambin, E.F. 2004. Digital change detection methods in ecosystem monitoring: a review. International Journal of Remote Sensing, 25(9): 1565-1596. https://doi.org/10.1080/0143116031000101675.

Debolini, M.; Marraccini, E.; Dubeuf, J.-P.; Geijzendorffer, I.R.; Guerra, C.; Simon, M.; Targetti, S.; Napoléone, C. 2018. Land and farming system dynamics and their drivers in the Mediterranean Basin. Land Use Policy, 74: 71-85. https://doi.org/10.1016/j.landusepol.2018.03.035

Dregne, H.E. 2002. Land degradation in the drylands. Arid Land Research and Management, 16(2): 99-132. https://doi.org/10.1080/153249802317304422

El Mazi, M.; Saber, E.R.; El-Bouhali, A.; Hmamouchi, M.; Bade, M.; Dhaouadi, L. 2026. Long-term Response of Vegetation to Global Change in the High Rif (Morocco): an Analysis Based on Remote Sensing Data. Earth Systems and Environment, (2026). https://doi.org/10.1007/s41748-025-01018-x

Ellis, E.C.; Goldewijk, K.K.; Siebert, S.; Lightman, D.; Ramankutty, N. 2010. Anthropogenic transformation of the biomes, 1700–2000. Global Ecology and Biogeography, 19(5): 589-606. https://doi.org/10.1111/j.1466-8238.2010.00540.x

FAO. 2018. The state of the world’s forests 2018: Forest pathways to sustainable development. FAO. https://openknowledge.fao.org/items/28896bfc-567c-4e4e-a1b2-d28e78867028

Ferreira, R.H.S. & Angelo, N.P. 2018. Change detection in remote sensing multitemporal image data by applying support vector machines using polynomial kernel and radial basis function (RBF) kernel. Pesquisas em Geociências, 45(2): e0674. https://doi.org/10.22456/1807-9806.88649

Foley, J.A.; DeFries, R.; Asner, G.P.; Barford, C.; Bonan, G.; Carpenter, S.R.; Chapin, F.S.; Coe, M.T.; Daily, G.C.; Gibbs, H.K.; Helkowski, J.H.; Holloway, T.; Howard, E.A.; Kucharik, C.J.; Monfreda, C.; Patz, J.A.; Prentice, I.C.; Ramankutty, N.; Snyder, P.K. 2005. Global consequences of land use. Science, 309(5734): 570-574. https://doi.org/10.1126/science.1111772

Foody, G.M. 2002. Status of land cover classification accuracy assessment. Remote Sensing of Environment, 80(1): 185-201. https://doi.org/10.1016/S0034-4257(01)00295-4

García-Ruiz, J.M.; López-Moreno, J.I.; Vicente-Serrano, S.M.; Lasanta-Martínez, T.; Beguería, S. 2013. Mediterranean water resources in a global change scenario. Earth-Science Reviews, 105(3–4): 121-139. https://doi.org/10.1016/j.earscirev.2011.01.006

Geist, H.J. & Lambin, E.F. 2002. Proximate causes and underlying driving forces of tropical deforestation: Tropical forests are disappearing as the result of many pressures, both local and regional, acting in various combinations in different geographical locations. BioScience, 52(2): 143-150. https://doi.org/10.1641/0006-3568(2002)052[0143:PCAUDF]2.0.CO;2

Gouveia, R.G.L.; Galvanin, E.A.S.; Neves, S.M.A.S.; Neves, R.J. 2015. Environmental fragility analysis in the Queima-Pé river basin, Tangará da Serra, MT. Pesquisas em Geociências, 42(2): 131-140. https://doi.org/10.22456/1807-9806.78115

Hansen, M.C. & Loveland, T.R. 2012. A review of large area monitoring of land cover change using Landsat data. Remote Sensing of Environment, 122: 66-74. https://doi.org/10.1016/j.rse.2011.08.024

Irifi, H.; Sebbab, M.M.; Ousbih, M.; Ziyadi, M.; El Ouahidi, A. 2025. Landscape characterization and dynamics of oases in arid environments: A study of the Timoulay Oumaloukt and Timoulay n’Tozomte oases in Ait Herbil (Guelmim-Oued Noun, Morocco). Cuadernos de Investigación Geográfica, 51(2): 233-262. https://doi.org/10.18172/cig.6475

Kennedy, R.E.; Yang, Z.; Cohen, W.B. 2010. Detecting trends in forest disturbance and recovery using yearly Landsat time series: 1. LandTrendr — Temporal segmentation algorithms. Remote Sensing of Environment, 114(12): 2897-2910. https://doi.org/10.1016/j.rse.2010.07.008

Kennedy, R.E.; Andréfouët, S.; Cohen, W.B.; Gómez, C.; Griffiths, P.; Hais, M.; Healey, S.P.; Helmer, E.H.; Hostert, P.; Lyons, M.B.; Meigs, G.W.; Pflugmacher, D.; Phinn, S.R.; Powell, S.L.; Scarth, P.; Sen, S.; Schroeder, T.A.; Schneider, A.; Sonnenschein, R.; Vogelmann, J.E.; Wulder, M.A.; Zhu, Z. 2014. Bringing an ecological view of change to Landsat-based remote sensing. Frontiers in Ecology and the Environment, 12(6): 339-346. https://doi.org/10.1890/130066.

Lambin, E.F.; Turner, B.L.; Geist, H.J.; Agbola, S.B.; Angelsen, A.; Bruce, J.W.; Coomes, O.T.; Dirzo, R.; Fischer, G.; Folke, C.; George, P.S.; Homewood, K.; Imbernon, J.; Leemans, R.; Li, X.; Moran, E.F.; Mortimore, M.; Ramakrishnan, P.S.; Richards, J.F.; … Xu, J. 2001) The causes of land‑use and land‑cover change: Moving beyond the myths. Global Environmental Change, 11(4): 261-269. https://doi.org/10.1016/S0959-3780(01)00007-3

Lambin, E.F.; Geist, H.J.; Lepers, E. 2003. Dynamics of land-use and land-cover change in tropical regions. Annual Review of Environment and Resources, 28: 205-241. https://doi.org/10.1146/annurev.energy.28.050302.105459

Leghrib, F.; Mazouz, S.; Martellozzo, F. 2025. From palm groves to urban zones: Patterns and past trends of urban sprawl and land use efficiency in semi-arid context, case of Biskra, Algeria. International Journal of Sustainable Development and Planning, 20(12): 5043-5057. https://doi.org/10.18280/ijsdp.201202

Loulad, S.; Nguyen, T.T.; Simou, M.R.; Rhinane, H.; Buerkert, A. 2023. Monitoring rural-urban transformation in the coastal region of Rabat-Sale-Kenitra, Morocco. PLOS ONE, 18(8): e0290829. https://doi.org/10.1371/journal.pone.0290829

Lu, D. & Weng, Q. 2007. A survey of image classification methods and techniques for improving classification performance. International Journal of Remote Sensing, 28(5): 823-870. https://doi.org/10.1080/01431160600746456

Lu, D.; Mausel, P.; Brondízio, E.; Moran, E. 2004. Change detection techniques. International Journal of Remote Sensing, 25(12): 2365-2401. https://doi.org/10.1080/0143116031000139863

Meyfroidt, P.; Roy Chowdhury, R.; de Bremond, A.; Ellis, E.C.; Erb, K.-H.; Filatova, T.; Garrett, R.D.; Grove, J.M.; Heinimann, A.; Kuemmerle, T.; Kull, C.A.; Lambin, E.F.; Landon, Y.; le Polain de Waroux, Y.; Messerli, P.; Müller, D.; Nielsen, J.Ø.; Peterson, G.D.; Rodriguez García, V.; Schlüter, M.; Verburg, P.H. 2018. Middle-range theories of land system change. Global Environmental Change, 53: 52-67. https://doi.org/10.1016/j.gloenvcha.2018.08.006

Nmiss, M.; Amyay, M.; Atiki, N.; Benbih, M.; Nait-Si, H.; Naji, M.E. 2025. Multidecadal evolution of the shoreline change at Agadir beach (Morocco): A GIS and high-resolution satellite imagery analysis. Pesquisas em Geociências, 52(1): e145533. https://doi.org/10.22456/1807-9806.145533.

Olofsson, P.; Foody, G.M.; Stehman, S.V.; Woodcock, C.E. 2013. Making better use of accuracy data in land change studies: Estimating accuracy and area and quantifying uncertainty using stratified estimation. Remote Sensing of Environment, 129: 122-131. https://doi.org/10.1016/j.rse.2012.10.031

Olofsson, P.; Foody, G.M.; Herold, M.; Stehman, S.V.; Woodcock, C.E.; Wulder, M.A. 2014. Good practices for estimating area and assessing accuracy of land change. Remote Sensing of Environment, 148, 42-57. https://doi.org/10.1016/j.rse.2014.02.015

Richards, J.A. & Jia, X.P. 2006. Remote sensing digital image analysis: An introduction (4th ed.). Springer. https://doi.org/10.1007/3-540-29711-1

Roy, D.P.; Wulder, M.A.; Loveland, T.R.; Woodcock, C.E.; Allen, R.G.; Anderson, M.C.; Helder, D.; Irons, J. R.; Johnson, D.M.; Kennedy, R.; Scambos, T.A.; Schaaf, C.B.; Schott, J.R.; Sheng, Y.; Vermote, E.F.; Belward, A.S.; Bindschadler, R.; Cohen, W.B.; Gao, F.; Zhu, Z. 2014. Landsat-8: Science and product vision for terrestrial global change research. Remote Sensing of Environment, 145: 154-172. https://doi.org/10.1016/j.rse.2014.02.001

Salvati, L.; Munafò, M.; Morelli, V.G.; Sabbi, A. 2012. Low-density settlements and land use changes in a Mediterranean urban region. Landscape and Urban Planning, 105(1–2): 43-52. https://doi.org/10.1016/j.landurbplan.2011.11.020

Scaramuzza, P.L.; Bouchard, M.A.; Dwyer, J.L. 2012. Development of the Landsat Data Continuity Mission cloud-cover assessment algorithms. IEEE Transactions on Geoscience and Remote Sensing, 50(4): 1140-1154. https://doi.org/10.1109/TGRS.2011.2164087

Shiferaw, N.; Habte, L.; Waleed, M. 2025. Land use dynamics and their impact on hydrology and water quality of a river catchment: a comprehensive analysis and future scenario. Environmental Science and Pollution Research, 32: 4124-4136. https://doi.org/10.1007/s11356-025-35946-y

Singh, A. 1989. Digital change detection techniques using remotely sensed data. International Journal of Remote Sensing, 10(6): 989-1003. https://doi.org/10.1080/01431168908903939

UNCCD. 2017. Global land outlook: First edition. United Nations Convention to Combat Desertification. https://www.unccd.int/sites/default/files/documents/2017-09/GLO_Full_Report_low_res.pdf

Veldkamp, A. & Lambin, E.F. 2001. Predicting land-use change. Agriculture, Ecosystems & Environment, 85(1–3): 1-6. https://doi.org/10.1016/S0167-8809(01)00199-2.

Wulder, M.A.; Loveland, T.R.; Roy, D.P.; Crawford, C.J.; Masek, J.G.; Woodcock, C.E.; Allen, R.G.; Anderson, M.C.; Belward, A.S.; Cohen, W.B.; Dwyer, J.; Erb, A.; Gao, F.; Griffiths, P.; Helder, D.; Hermosilla, T.; Hipple, J.D.; Hughes, M.J.; Huntington, J.; Zhu, Z. 2019. Current status of Landsat program, science, and applications. Remote Sensing of Environment, 225: 127-147. https://doi.org/10.1016/j.rse.2019.02.015

Yahaya, I.; Xu, R.; Zhou, J.; Jiang, S.; Su, B.; Huang, J.; Cheng, J.; Dong, Z.; Jiang, T. 2024. Projected patterns of land use in Africa under a warming climate. Scientific Reports, 14: 12315. https://doi.org/10.1038/s41598-024-61035-0

Zhu, Z. 2017. Change detection using Landsat time series: A review of frequencies, preprocessing, algorithms, and applications. ISPRS Journal of Photogrammetry and Remote Sensing, 130: 370-384. https://doi.org/10.1016/j.isprsjprs.2017.06.013

Zhu, Z. & Woodcock, C.E. 2014. Continuous change detection and classification of land cover using all available Landsat data. Remote Sensing of Environment, 144: 152-171. https://doi.org/10.1016/j.rse.2014.01.011

Zhu, Z.; Zhang, J.; Yang, Z.; Aljaddani, A.H.; Cohen, W.B.; Qiu, S.; Zhou, C. 2020. Continuous monitoring of land disturbance based on Landsat time series. Remote Sensing of Environment, 238: 111116. https://doi.org/10.1016/j.rse.2019.03.009

Downloads

Publicado

2026-06-01

Como Citar

BELHAK, L., Rahmani, T.- din, Nmiss, M., & Essami, A. (2026). Detecção de Mudanças no Uso e na Cobertura da Terra Utilizando Séries Temporais Landsat na Bacia do Wadi Rdat, Marrocos. Pesquisas Em Geociências, 53(1), e153402. https://doi.org/10.22456/1807-9806.153402