Elaboration of Vehicle Trafficability Maps Using Remote Sensing and GIS: a Systematic and Comprehensive Review

Main Article Content

Renan Fabres Dalmonech
https://orcid.org/0000-0002-4289-9873
Cláudia Maria de Almeida
https://orcid.org/0000-0002-6523-3169
Joel Borges dos Passos
Rodrigo de Campos Macedo

Abstract

Vehicle trafficability maps are cartographic products that allow users to check the forecast of trafficable land in areas that do not have roads available for travel to the destination or that have been damaged by natural events that may make it impossible to use roads built for vehicle trafficability. In these cases, off-road travel through poorly explored terrain can be a viable option, with the planning of the route to be followed aided by trafficability maps. These cartographic products can be produced using Digital Image Processing techniques, Remote Sensing (RS) and other auxiliary data. In this study, a wide-ranging search was carried out on the World Wide Web in order to verify published works whose object of study was trafficability maps, within a time frame of the last 20 years. A total of 45 studies were found and duly analyzed in order to extract the main information and results. The results indicate that the relief variable is the most frequently used (97.78%), followed by vegetation (95.55%), water bodies (91.11%), soil type (82.22%), anthropogenic features (80%), soil moisture (60%) and meteorological conditions (40%). Most of the studies operated on a topographic scale (71.11%). A small proportion of the studies carried out field work (31.11%), and most of them were aimed at the military (53.33%), with studies generally concentrated in countries such as Poland, the Czech Republic and India and using a variety of parametric and non-parametric methods.

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Article Details

Section

Remote Sensing

Author Biography

Renan Fabres Dalmonech, Federal University of Paraná (UFPR)

Renan Fabres Dalmonech, born in Vitória-ES, has a bachelor's degree in Cartographic Engineering from the Military Institute of Engineering (IME), with an exchange period at Texas Tech University (Lubbock, TX). He has experience in the area of Geosciences, with an emphasis on Cartography, RS and GIS (2019-2022). He is currently studying for a master's degree in Remote Sensing at the Federal University of Paraná (UFPR), with a line of research in developing methodologies for image segmentation and classification and applications in cartographic production lines.

How to Cite

DALMONECH, Renan Fabres; ALMEIDA, Cláudia Maria de; PASSOS, Joel Borges dos; MACEDO, Rodrigo de Campos. Elaboration of Vehicle Trafficability Maps Using Remote Sensing and GIS: a Systematic and Comprehensive Review. Brazilian Journal of Cartography, [S. l.], v. 77, n. 0a, 2025. DOI: 10.14393/rbcv77n0a-73481. Disponível em: https://seer.ufu.br/index.php/revistabrasileiracartografia/article/view/73481. Acesso em: 5 dec. 2025.

References

Flores, A. N., Entekhabi, D. & Bras, R. L. (2014). Application of a hillslope-scale soil moisture data assimilation system to military trafficability assessment. Journal of Terramechanics, v. 51, p. 53-66. https://doi.org/10.1016/j.jterra.2013.11.004.

Grandjean, G. & Angelliaume, S. (2009, 17 de agosto). The ECORS system: A mobility decision-making tool based on Earth observation data. In: IEEE International Geoscience and Remote Sensing Symposium. Cape Town, South Africa: p. 350-355. https://doi.org/10.1109/IGARSS.2009.5417657.

Grogan, A. (2009). Creating a spatial analysis model for generating composite cost surfaces to depict cross country mobility in natural terrain. In: ASPRS/MAPPS Fall Conference. San Antonio, Texas. https://www.semanticscholar.org/paper/CREATING-A-SPATIAL-ANALYSIS-MODEL-FOR-GENERATING-TO-Grogan/1f952330ce338719a050eba590d538e0dea03f2a.

Gumos, A. K. (2005). Modelling the Cross-Country Trafficability with Geographical Information Systems. [Independent thesis advanced level, Linköping University, Department of Computer and Information Science]. https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-313.

He, K., Dong, Y., Han, W. & Zhang, Z. (2023). An assessment on the off-road trafficability using a quantitative rule method with geographical and geological data. Computers & Geosciences, v. 177. https://doi.org/10.1016/j.cageo.2023.105355.

Hestera, H. & Pahernik, M. (2018). Physical-geographic factors of terrain trafficability of military vehicles according to Western World methodologies. Croatian Geographical Bulletin, v. 80, p. 5-31. https://doi.org/10.21861/HGG.2018.80.02.01.

Höfig, P. & Araujo-Junior, C. F. (2015). Classes de declividade do terreno e potencial para mecanização no estado do Paraná. Coffee Science, 10(2), p. 195-203. http://www.sbicafe.ufv.br/handle/123456789/8117.

Hofmann, A., Kovarik, V., Talhofer, V. & Hošková-Mayerová, S. (2014). Creation of models for calculation of coefficients of terrain passability. Quality and Quantity, v. 49, p. 1-13. https://doi.org/10.1007/s11135-014-0072-1.

Hua, C., Jiang, C., Niu, R., Fu, X., Chen, Z., Kuang, X. & Yu, B. (2024). Double Neural Networks Enhanced Global Mobility Prediction Model for Unmanned Ground Vehicles in Off-road Environments. IEEE Transactions on Vehicular Technology, 73(6), p. 7547-7560. https://doi.org/10.1109/TVT.2024.3351677.

Hua, C., Niu, R., Jiang, C., Yu, B., Zhu, H. & Li, B. (2023). Efficient and High-Fidelity Mobility Prediction for Unmanned Ground Vehicles Based on Gaussian Sampled Terrain and Enhanced Neural Network. IEEE Robot. Autom. Lett., 8(12), p. 8422-8429. https://doi.org/10.1109/lra.2023.3329349.

Hubacek, M., Kovarik, V., Talhofer, V., Rybansky, M., Hofmann, A., Břeňová, M. & Čeplová, L. (2016, 1º de janeiro). Modelling of geographic and meteorological effects on vehicle movement in the open terrain. In: 23rd Central European Conference. Brno, Czech Republic. https://www.researchgate.net/publication/307877346_MODELLING_OF_GEOGRAPHIC_AND_METEOROLOGICAL_EFFECTS_ON_VEHICLE_MOVEMENT_IN_THE_OPEN_TERRAIN.

Hubacek, M., Rybansky, M., Brenova, M. & Ceplova, L. (2014). The soil trafficability measurement in the Czech Republic for military and civil use. In: 18th International Conference of the ISTVS. Seoul, Korea: p. 22-25. https://www.researchgate.net/publication/268818255_The_soil_trafficability_measurement_in_ the_czech_republic_for_military_and_civil_use.

Kalugamuwa, K., Dinusha, K. A. & Sandamali, K. U. J. (2020, outubro). GIS Mechanism For Terrain Trafficability. In: 13th International Research Conference. Lavinia. Sri Lanka: General Sir John Kotelawala Defence University. http://ir.kdu.ac.lk/handle/345/3280.

Khan, M., Kashif, M. & Shah, A. (2021). Off-Road Trafficability for Military Operations Using Multi-Criteria Decision Analysis. International Journal of Advanced Remote Sensing and GIS, v. 10, p. 3425-3437. https://doi.org/10.23953/cloud.ijarsg.489.

Moher, D., Liberati, A., Tetzlaff, J. & Altman, D. G. (2009). Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement. BMJ, p. 1-8. https://doi.org/10.1136/bmj.b2535.

Oliveira, I. C. (2006). O uso da análise espacial no processo de integração terreno, condições meteorológicas e inimigo (PITCI) do Exército brasileiro. [Dissertação de Mestrado em Geologia, Instituto de Geociências, Universidade de Brasília (UnB), Brasília, DF]. https://www.researchgate.net/publication/40437463_O_ uso_da_analise_espacial_no_processo_de_integracao_terreno_condicoes_meteorologicas_e_inimigo_PITCI_do_exercito_brasileiro.

Partida, R. D. L. (2017). Geotecnologias e análise espacial: planejamento de mobilidade com unidades blindadas tipo lagarta na bacia hidrográfica do lago de Maracaibo - Venezuela. [Dissertação de Mestrado em Geografia, Programa de Pós-Graduação em Geografia, Universidade Federal de Santa Maria (UFSM), Santa Maria, Rio Grande do Sul]. http://repositorio.ufsm.br/handle/1/14417.

Pimpa, W. (2012). Terrain analysis for path finding of combat cross-country movement. [Doctoral Thesis in Philosophy and Geoinformatics, School of Remote Sensing, Institute of Science, Suranaree University of Technology, Thailand]. http://sutir.sut.ac.th:8080/jspui/handle/123456789/4972.

Pimpa, W., Sarapirome, S. & Dasananda, S. (2014). GIS application to development of military cross-country movement maps at Mae Sot district, western Thailand. Suranaree Journal of Science and Technology, 21(3), p. 215-232. https://doi.org/10.14456/sjst.2014.26.

Pokonieczny, K. (2017, 1º de maio). Automatic military passability map generation system. In: International Conference on Military Technologies (ICMT). Brno, Czech Republic: p. 285-292. https://doi.org/10.1109/MILTECHS.2017.7988771.

Pokonieczny, K. (2018a). Comparison of land passability maps created with use of different spatial data bases. Geografie, 123(3), p. 317-352. https://doi.org/10.37040/geografie2018123030317.

Pokonieczny, K. (2018b, junho). Methodology of cartographic visualisation of military maps of passability. In: 7th International Conference on Cartography and GIS. Sozopol, Bulgaria: p. 613-622. https://www.researchgate.net/publication/330534058_Methodology_of_cartographic_visualisation_of_military_maps_of_passability.

Pokonieczny, K. (2018c). Use of a Multilayer Perceptron to Automate Terrain Assessment for the Needs of the Armed Forces. ISPRS International Journal of Geo-Information, 7(11). https://doi.org/10.3390/ijgi7110430.

Pokonieczny, K. (2020). The Methodology of Creating Variable Resolution Maps Based on the Example of Passability Maps. ISPRS International Journal of Geo-Information, 9(12). https://doi.org/10.3390/ijgi9120738.

Pokonieczny, K. (2022). Methodology of developing the dynamic maps of passability. In: 8th International Conference on Cartography and GIS. Nessebar, Bulgaria: v. 2, p. 244-252. https://www.researchgate.net/publication/368364984_METHODOLOGY_OF_DEVELOPING_THE_DYNAMIC_MAPS_OF_PASSABILITY.

Pokonieczny, K. & Borkowska, S. (2019, 1º de maio). Using High Resolution Spatial Data to Develop Military Maps of Passability. In: International Conference on Military Technologies (ICMT). Brno, Czech Republic: p. 1-8. https://doi.org/10.1109/MILTECHS.2019.8870022.

Pokonieczny, K. & Dawid, W. (2023). The application of artificial neural networks for the generalisation of military passability maps. International Journal of Cartography, 9(3), p. 638-654. https://doi.org/10.1080/23729333.2023.2231589.

Pokonieczny, K., Dawid, W. & Borkowska, S. (2021). Comparison of the military maps of trafficability developed by different methods. In: International Conference on Military Technologies (ICMT). Brno, Czech Republic, p. 1-8. https://doi.org/10.1109/ICMT52455.2021.9502833.

Pokonieczny, K. & Moscicka, A. (2018). The Influence of the Shape and Size of the Cell on Developing Military Passability Maps. International Journal of Geo-Information (Int. J. Geo-Inf), v. 7, p. 261-288. https://doi.org/10.3390/ijgi7070261.

Pokonieczny, K. & Rybansky, M. (2018). Method of developing the maps of passability for unmanned ground vehicles. IOP Conference Series: Earth and Environmental Science, 169(1), p. 1-9. https://doi.org/10.1088/1755-1315/169/1/012027.

Potic, I., Stojanovic, M., Curcic, N., Dordevic, D. & Bankovic, R. (2024). Development of geospatial passability maps: a multicriteria analysis approach. Journal of the Geographical Institute Jovan Cvijic, 74(1), p. 29-45. https://doi.org/10.2298/IJGI230822002P.

Pundir, S. K. & Garg, R. D. (2020a). Development of mapping techniques for off road trafficability to support military operation. Spatial Information Research, 28(4), p. 495-506. https://doi.org/10.1007/s41324-019-00310-z.

Pundir, S. K. & Garg, R. D. (2020b). Development of rule-based approach for assessment of off-road trafficability using remote sensing and ancillary data. Quaternary International, v. 5, p. 575-584. https://doi.org/10.1016/j.quaint.2020.07.017.

Pundir, S. K. & Garg, R. D. (2021). Development of an empirical relation to assess soil spatial variability for off-road trafficability using terrain similarity analysis & geospatial data. Remote Sensing Letters, 12(3), p. 259-268. https://doi.org/10.1080/2150704X.2021.1880657.

Pundir, S. K. & Garg, R. D. (2022). A comprehensive approach for off-road trafficability evaluation and development of modified equation for estimation of RCI to assess regional soil variation using geospatial technology. Quaternary Science Advances, v. 5, p. 1-16. https://doi.org/10.1016/j.qsa.2021.100042.

Rada, J., Rybansky, M. & Dohnal, F. (2020). Influence of Quality of Remote Sensing Data on Vegetation Passability by Terrain Vehicles. ISPRS International Journal of Geo-Information, 9(11). https://doi.org/10.3390/ijgi9110684.

Rada, J., Rybansky, M. & Dohnal, F. (2021). The Impact of the Accuracy of Terrain Surface Data on the Navigation of Off-Road Vehicles. ISPRS International Journal of Geo-Information, 10(3), p. 106-124. https://doi.org/10.3390/ijgi10030106.

Rehrer, S. E., Griffin, A. W. & Renner, M. (2022). Cross country mobility (CCM) modeling using triangulated irregular networks (TIN). United States: Engineer Research and Development Center. Technical Report ERDC/GRL TR-22-5. https://erdc-library.erdc.dren.mil/jspui/handle/11681/46082.

Rybansky, M. (2007). Effect of the Geographic Factors on the Cross-Country Movement during Military Operations and the Natural Disasters. In: Cartographic Renaissance. Brno, Czech Republic. https://www.semanticscholar.org/paper/Effect-of-the-Geographic-Factors-on-the-Cross-and-Rybansky/823e70ccf260cdc2336956935e11a9c79100107d.

Rybansky, M., Hofmann, A., Hubacek, M., Kovarik, V. & Talhofer, V. (2015). Modelling of cross-country transport in raster format. Environmental Earth Sciences, 74(10), p. 7049-7058. https://doi.org/10.1007/s12665-015-4759-y.

Rybansky, M., Hubacek, M., Hofmann, A., Kovarik, V. & Talhofer, V. (2014, 1º de janeiro). The Impact of Terrain on Cross-Country Mobility – Geographic Factors and their Characteristics. In: 18th International Conference of the ISTVS. Seoul, Korea. https://www.researchgate.net/publication/276847750_ The_Impact_of_Terrain_on_Cross-Country_Mobility_-_Geographic_Factors_and_their_Characteristics.

Sadiya, T. B., James, G. K. & Oladiti, I. (2017). Military Terrain Trafficability Analysis for North-East Nigeria: A GIS and Remote Sensing-Based Approach. IOSR Journal of Mobile Computing & Application, 4(1), p. 34-46. https://doi.org/10.9790/0050-04013446.

Suvinen, A. (2006). A GIS-based simulation model for terrain tractability. Journal of Terramechanics, v. 43, p. 427-449. https://doi.org/10.1016/j.jterra.2005.05.002.

Torrealba, Y. V. (2015). Mapa de transitabilidade para operações táticas com auxílio de SIG e sistema especialista. [Dissertação de Mestrado em Ciências Geodésicas, Programa de Pós-Graduação em Ciências Geodésicas, Setor de Ciências da Terra, Universidade Federal do Paraná (UFPR), Curitiba, Paraná]. https://acervodigital.ufpr.br/handle/1884/40826.

Veloza, E. V. (2020). O emprego da Geointeligência como ferramenta para aprimorar a análise do terreno no planejamento de operações militares do Exército brasileiro. [Dissertação de Mestrado em Sistemas de Informação Geográfica, NOVA Information Management School (NIMS), Lisboa, Portugal]. https://run.unl.pt/handle/10362/98833.

Wicander, M. (2018). Requirements for Cross Country Movement in Land Warfare. [Master's Thesis in Defense, Swedish Defence University, Sweden]. https://urn.kb.se/resolve?urn=urn:nbn:se:fhs:diva-7411.

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