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Articles

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  1. Blaschke, T., Lang, S., Lorup, E., Strobl, J. and Zeil, P. (2000) Object-oriented image processing in an integrated GIS/remote sensing environment and perspectives for environmental applications. In: Environmental Information for Planning, Politics and the Public (EnviroInfo 2000), Vol. 2, pp. 555–570. Available at: https://enviroinfo.eu/sites/default/files/pdfs/vol102/0555.pdf ( Accessed 24 June 2026)

  2. Gilberto Câmara, Souza, R.C.M., Freitas, U.M. and Garrido, J. (1996) SPRING: Integrating remote sensing and GIS by object-oriented data modelling. Computers & Graphics, 20(3), pp. 395–403. Available at: https://www.sciencedirect.com/science/article/abs/pii/0097849396000088.( Accessed 24 June 2026)

  3. Warren B. Cohen and Samuel N. Goward (2004) Landsat’s role in ecological applications of remote sensing. BioScience, 54(6), pp. 535–545.   ( Accessed 24 June 2026)

  4. Frederick W. Davis, Dale A. Quattrochi, Ridd, M., Lam, N., Walsh, S.J., Michaelsen, J.C., Franklin, J., Stow, D.A., Johannsen, C.J. and Johnston, C.A. (1991) Environmental analysis using integrated GIS and remotely sensed data: some research needs and priorities. Photogrammetric Engineering and Remote Sensing, 57(6), pp. 689–697.( Accessed 24 June 2026)

  5. John C. Hinton (1996) GIS and remote sensing integration for environmental applications. International Journal of Geographical Information Systems, 10(7), pp. 877–890. Available at: https://www.tandfonline.com/doi/abs/10.1080/02693799608902114.( Accessed 24 June 2026)

  6.  Brian G. Lees and Kim Ritman (1991) Decision-tree and rule-induction approach to integration of remotely sensed and GIS data in mapping vegetation in disturbed or hilly environments. Environmental Management, 15, pp. 823–831. Available at: https://link.springer.com/article/10.1007/BF02394820 ( Accessed 24 June 2026)

  7.  An Li (2006) Eco-environmental vulnerability evaluation in mountainous regions using remote sensing and GIS. Ecological Engineering, 27(4), pp. 301–310. Available at: https://www.sciencedirect.com/science/article/pii/S0304380005003388 ( Accessed 24 June 2026)

  8. Xiaobin Jin, Zhenqi Hu and Xiaoping Liu (2008) Integration of remote sensing and GIS for ecological vulnerability assessment. Ecological Modelling, 212(3), pp. 180–199. Available at: https://econpapers.repec.org/article/eeeecomod/v_3a212_3ay_3a2008_3ai_3a3_3ap_3a180-199.htm ( Accessed 24 June 2026)

  9. Assefa M. Melesse, Weng, Q., Thenkabail, P.S. and Senay, G.B. (2007) Remote sensing sensors and applications in environmental resources mapping and modelling. Sensors, 7(12), pp. 3209–3241. Available at: https://www.mdpi.com/1424-8220/7/12/3209 ( Accessed 24 June 2026)

  10. Rebelo, L.M., Finlayson, C.M. & Nagabhatla, N., 2009. 'Remote sensing and GIS for wetland inventory, mapping and change analysis', Journal of environmental management, 90(7), pp.2144-2153.( Accessed 24 June 2026)

  11. Kenneth F. Noltimier, Kenneth C. Jezek, Sohn, H.G., Li, B., Liu, H., Baumgartner, F., Kaupp, V., Curlander, J.C., Wilson, B. and Onstott, R. (1999) RADARSAT Antarctic mapping project: mosaic construction. In: Proceedings of the IEEE 1999 International Geoscience and Remote Sensing Symposium (IGARSS’99). Piscataway, NJ: IEEE, Vol. 5, pp. 2349–2351.( Accessed 24 June 2026)

  12. Georges Ducher (1980) Cartographic possibilities of the SPOT and Spacelab projects. The Photogrammetric Record, 10(56), pp. 167–180. Available at: https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1477-9730.1980.tb00019.x.( Accessed 24 June 2026)

  13. Jozef Feranec, Soukup, T., Hazeu, G. and Jaffrain, G. (2007) Cartographic aspects of land cover change detection: over- and underestimation in the I&CORINE Land Cover 2000 project. The Cartographic Journal, 44(1), pp. 5–15. Available at: https://www.tandfonline.com/doi/abs/10.1179/000870407X173869                         ( Accessed 24 June 2026)

  14. ​Gao, J. & Liu, Y. 2001, 'Applications of Remote Sensing, GIS and GPS in glaciology: a review', Progress in Physical Geography: Earth And  Environment, 25(4), pp.520-540.( Accessed 24 June 2026)

  15. Giorgio Gualtieri and Marco Tartaglia (1998) Predicting urban traffic air pollution: a GIS framework. Transportation Research Part D: Transport and Environment, 3(5), pp. 329–336. Available at: https://www.sciencedirect.com/science/article/abs/pii/S136192099800011X( Accessed 24 June 2026)

  16. ​Fatih Sunar and Cem Özkan (2001) Forest fire analysis with remote sensing data. International Journal of Remote Sensing, 22(12), pp. 2265–2277. Available at: https://www.tandfonline.com/doi/abs/10.1080/01431160118510.( Accessed 24 June 2026)

  17. ​Kerr, J. and Ostrovsky, M., 2003, ‘From space to species: ecological applications for remote sensing’. Trends in Ecology & Evolution, 18(6), pp.299-305.( Accessed 24 June 2026)

  18. Labrière, N. et al. (2023) Toward a forest biomass reference measurement system for remote sensing applications, Willey Online Library.( Accessed 24 June 2026)

  19. Jawak S D, Pohjola V, Kääb A, Andersen B N, Błaszczyk M, Salzano R, Luks B, Enomoto H, Høgda K A, Moholdt G, Dinessen F and Fjæraa A M 2023 Status of Earth Observation and Remote Sensing Applications in Svalbard Remote Sensing 15 513 ( Accessed 24 June 2026)

  20. ​ Chung-Ru Ho and Antony K. Liu (2023) Preface: remote sensing applications in ocean observation. Remote Sensing, 15(2), 415. Available at: https://www.mdpi.com/2072-4292/15/2/415 ( Accessed 24 June 2026)

  21.  Thulani Dube (2023) Remote sensing for water resources and environmental management. Remote Sensing, 15(1), 18. Available at: https://www.mdpi.com/2072-4292/15/1/18. ( Accessed 24 June 2026)

  22. Nicolas Labrière, Davies, S.J., Disney, M.I., Duncanson, L.I., Herold, M., Lewis, S.L., Phillips, O.L., Quegan, S., Saatchi, S.S., Schepaschenko, D.G. et al. (2023) Toward a forest biomass reference measurement system for remote sensing applications. Global Change Biology, 29(3), pp. 827–840. Available at: https://onlinelibrary.wiley.com/doi/10.1111/gcb.16497. ( Accessed 24 June 2026)

  23. ​​Zhang, Y., Li, X., Wang, S. et al. (2023) Remote sensing applications in environmental monitoring and analysis. Remote Sensing, 15(5), 1378. Available at: https://www.mdpi.com/2072-4292/15/5/1378 ( Accessed 24 June 2026)

  24. Y. Ma et al. (2024) Transfer learning in environmental remote sensing. Remote Sensing of Environment, 301, 113924. Available at: https://www.sciencedirect.com/science/article/pii/S0034425723004765 ( Accessed 24 June 2026)

  25. ​Florian E. Fassnacht, Næsset, E. et al. (2024) Remote sensing in forestry: current challenges, considerations and directions. Forestry: An International Journal of Forest Research, 97(1), pp. 11–37. Available at: https://academic.oup.com/forestry/article/97/1/11/7159227                      ( Accessed 24 June 2026)

  26.  R.W. Aslam et al. (2024) Wetland identification through remote sensing: insights into wetness, greenness, turbidity, temperature, and changing landscapes. Big Data Research, 35, 100416. Available at: https://www.sciencedirect.com/science/article/pii/S2214579623000862( Accessed 24 June 2026)

  27.  Messaoudi, D., Settou, N. and Allouhi, A. (2024) ‘Geographical, technical, economic, and environmental potential for wind to hydrogen production in Algeria: GIS-based approach’, International Journal of Hydrogen Energy, 50, pp. 142–160. doi:10.1016/j.ijhydene.2023.07.263. ( Accessed 24 June 2026)

  28. Weslati, O. and Serbaji, M.-M. (2023) Spatial assessment of soil erosion using RUSLE model, remote sensing and GIS: A case study of mellegue watershed, algeria- Tunisia [Preprint]. doi:10.21203/rs.3.rs-2696076/v1.                       ( Accessed 24 June 2026)

  29. Pablo Benalcazar, Aleksandra Komorowska and Jacek Kamiński (2024) A GIS-based method for assessing the economics of utility-scale photovoltaic systems. Applied Energy, 360, 122044. Available at: https://www.sciencedirect.com/science/article/pii/S0306261923014083              ( Accessed 24 June 2026) 

  30. R. Guria et al. (2023) Remote sensing, GIS, and analytic hierarchy process-based delineation and sustainable management of potential groundwater zones: a case study of Jhargram district, West Bengal, India. Environmental Monitoring and Assessment, 196(1), 51. Available at: https://link.springer.com/article/10.1007/s10661-023-12205-6(Accessed 24 June 2026)

  31. M.S. Hossain et al. (2024) Hydro-chemical characteristics and groundwater quality evaluation in south-western region of Bangladesh: a GIS-based approach and multivariate analyses. Heliyon, 10(1), e24011. Available at: https://www.sciencedirect.com/science/article/pii/S2405844024001234 ( Accessed 24 June 2026)

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