Fiabilidad en la detección de las superficies selladas empleando datos del programa Copernicus

Contenido principal del artículo

Emilio José Illán-Fernández
Alfredo Pérez-Morales
Asunción Romero-Díaz

Resumen

Durante los últimos 50 años se han producido cambios significativos en las cubiertas y usos del suelo, principalmente aquellos catalogados como artificiales. Este proceso, y su generalización a escala global, afectan de forma directa a las funciones básicas del suelo, acrecentando otros problemas como pueden ser la pérdida de biodiversidad, contaminación, degradación edáfica, inundaciones, o los efectos del cambio climático. En el área de estudio (Mazarrón, Región de Murcia) el problema anterior resulta ejemplar: el binomio desarrollo urbano asociado al turismo de sol y playa y la agricultura intensiva (bajo invernaderos) alteran de forma drástica la naturaleza del suelo. El objetivo es establecer un modelo de clasificación supervisada que distinga, con un error asumible, las distintas clases establecidas, destacando sobre todas ellas las que supongan superficies sellantes y, además, realizar una comparación con la información del último Corine Land Cover disponible (2018). Para ello, se seleccionaron imágenes del satélite Sentinel 2A y se ejecutó una clasificación de máxima verosimilitud. Para validar los resultados, se elaboró una matriz de confusión en la que se obtuvo una precisión general del 89 %. Finalmente, se observó una subestimación significativa, por parte del Corine Land Cover, del 75 % de las superficies selladas debido a su resolución.



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Illán-Fernández, E. J., Pérez-Morales, A., & Romero-Díaz, A. (2022). Fiabilidad en la detección de las superficies selladas empleando datos del programa Copernicus. Boletín De La Asociación De Geógrafos Españoles, (93). https://doi.org/10.21138/bage.3288

Bibliografía

Amro, I., Mateos, J., Vega, M., Molina, R., & Katsaggelos, A.K. (2011). A survey of classical methods and new trends in pansharpening of multispectral images. EURASIP Journal on Advances in Signal Processing, 2011(1), 1-22. https://doi.org/10.1186/1687-6180-2011-79

Anderson, J.R. (1976). A land use and land cover classification system for use with remote sensor data (Vol. 964). US Government Printing Office.

Araya, Y.H., & Cabral, P. (2010). Analysis and modeling of urban land cover change in Setúbal and Sesimbra, Portugal. Remote Sensing, 2(6), 1549-1563. https://doi.org/10.3390/rs2061549

Arnfield, A.J. (2003). Two decades of urban climate research: a review of turbulence, exchanges of energy and water, and the urban heat island. International Journal of Climatology: a Journal of the Royal Meteorological Society, 23(1), 1-26. https://doi.org/10.1002/joc.859

Barreira González, P., González Cascon, V., & Bosque Sendra, J. (2012). Detección de errores temáticos en el CORINE Land Cover a través del estudio de cambios: Comunidad de Madrid (2000-2006). Estudios geográficos, 73(272), 7-34. https://doi.org/10.3989/estgeogr.201201

Borràs, J., Delegido, J., Pezzola, A., Pereira, M., Morassi, G., & Camps-Valls, G. (2017). Clasificación de usos del suelo a partir de imágenes Sentinel-2. Revista de Teledetección, (48), 55-66. https://doi.org/10.4995/raet.2017.7133

Bossard, M., Feranec, J., & Otahel, J. (2000). CORINE land cover technical guide: Addendum 2000, 40. Copenhagen: European Environment Agency. https://www.eea.europa.eu/publications/tech40add

Casciere, R., Franci, F., & Bitelli, G. (2014). Use of Landsat imagery to detect land cover changes for monitoring soil sealing; case study: Bologna province (Italy). Second International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2014). https://doi.org/10.1117/12.2066432

Chen, L., Zhang, M., Zhu, J., Wang, Y., & Skorokhod, A. (2018). Modeling impacts of urbanization and urban heat island mitigation on boundary layer meteorology and air quality in Beijing under different weather conditions. Journal of Geophysical Research: Atmospheres, 123(8), 4323-4344. https://doi.org/10.1002/2017JD027501

Choudhury, D., Das, K., & Das, A. (2019). Assessment of land use land cover changes and its impact on variations of land surface temperature in Asansol-Durgapur Development Region. The Egyptian Journal of Remote Sensing and Space Science, 22(2), 203-218. https://doi.org/10.1016/j.ejrs.2018.05.004

Congalton, R.G. (1988). A comparison of sampling schemes used in generating error matrices for assessing the accuracy of maps generated from remotely sensed data. Photogrammetric Engineering and Remote Sensing, 54(5), 593-600. https://scholars.unh.edu/faculty_pubs/1249/

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

Crutzen, P.J. (2006). The “Anthropocene”. In Earth system science in the anthropocene (pp. 13-18). Springer. https://doi.org/10.1007/3-540-26590-2_3

Curtis, K., & Youngquist, S.T. (2013). Part 21: categoric analysis: Pearson chi-square test. Air medical journal, 32(4), 179-180, https://doi.org/10.1016/j.amj.2013.04.007

Deng, J.S., Wang, K., Hong, Y., & Qi, J.G. (2009). Spatio-temporal dynamics and evolution of land use change and landscape pattern in response to rapid urbanization. Landscape and urban planning, 92(3-4), 187-198. https://doi.org/10.1016/j.landurbplan.2009.05.001

Díaz-Pacheco, J., & Gutiérrez, J. (2014). Exploring the limitations of CORINE Land Cover for monitoring urban land-use dynamics in metropolitan areas. Journal of Land Use Science, 9(3), 243-259. https://doi.org/10.1080/1747423X.2012.761736

Duarte, C.M., Alonso, S., Benito, G., Dachs, J., Montes, C., Pardo Buendía, M., Ríos, A.F., Simó, Rafel & Valladares, F. (2006). Cambio Global. Impacto de la actividad humana sobre el sistema Tierra. CSIC. http://hdl.handle.net/10016/8520

EEA (1995). CORINE Land Cover. https://www.eea.europa.eu/publications/COR0-landcover

EEA (2010). The European environment — state and outlook 2010: soil. European Environment Agency. http://dx.doi.org/10.2800/58866

EEA (2012). The state of soil in Europe. A contribution of the JRC to the EEA Environment State and Outlook Report — SOER2010. European Environment Agency, Joint Research Centre. https://doi.org/10.2788/75626

EEA (2021). Copernicus Land Monitoring Service: CORINE Land Cover. User Manual. European Union. https://land.copernicus.eu/user-corner/technical-library/clc-product-user-manual

Erener, A. (2013). Classification method, spectral diversity, band combination and accuracy assessment evaluation for urban feature detection. International Journal of Applied Earth Observation and Geoinformation, 21, 397-408. https://doi.org/10.1016/j.jag.2011.12.008

European Space Agency (2015). Sentinel-2 User Handbook. https://sentinel.esa.int/documents/247904/685211/Sentinel-2_User_Handbook

Ferreira, C.S., Seifollahi-Aghmiuni, S., Destouni, G., Ghajarnia, N., & Kalantari, Z. (2022). Soil degradation in the European Mediterranean region: Processes, status and consequences. Science of the Total Environment, 805, 150106. https://doi.org/10.1016/j.scitotenv.2021.150106

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

Foody, G.M. (2005). Local characterization of thematic classification accuracy through spatially constrained confusion matrices. International Journal of Remote Sensing, 26(6), 1217-1228. https://doi.org/10.1080/01431160512331326521

Foody, G.M. (2008). Harshness in image classification accuracy assessment. International Journal of Remote Sensing, 29(11), 3137-3158. https://doi.org/10.1080/01431160701442120

Foody, G.M. (2020). Explaining the unsuitability of the kappa coefficient in the assessment and comparison of the accuracy of thematic maps obtained by image classification. Remote Sensing of Environment, 239, 111630. https://doi.org/10.1016/j.rse.2019.111630

Fu, B., Meadows, M.E., & Zhao, W. (2021). Geography in the Anthropocene: Transforming our world for sustainable development. Geography and Sustainability, 3(1), 1-6. https://doi.org/10.1016/j.geosus.2021.12.004

García, P., & Pérez, E. (2016). Mapping of soil sealing by vegetation indexes and built-up index: A case study in Madrid (Spain). Geoderma, 268, 100-107. https://doi.org/10.1016/j.geoderma.2016.01.012

Gašparović, M., & Jogun, T. (2018). The effect of fusing Sentinel-2 bands on land-cover classification. International journal of remote sensing, 39(3), 822-841. https://doi.org/10.1080/01431161.2017.1392640

Goldewijk, K.K. (2001). Estimating global land use change over the past 300 years: the HYDE database. Global biogeochemical cycles, 15(2), 417-433. https://doi.org/10.1029/1999GB001232

Grullón, Y.R., Alhaddad, B., & Cladera, J.R. (2009, October). The analysis accuracy assessment of CORINE land cover in the Iberian coast. In Remote Sensing for Environmental Monitoring, GIS Applications, and Geology IX (Vol. 7478, p. 74781N). International Society for Optics and Photonics. https://doi.org/10.1117/12.830121

Hansen, A. J., DeFries, R. S., & Turner, W. (2012). Land use change and biodiversity. In Land change science (pp. 277-299). Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-2562-4_16

Hooke, R.L., Martín Duque, J.F., & Pedraza Gilsanz, J.D. (2013). Land transformation by humans: a review. Ene, 12(43). https://eprints.ucm.es/id/eprint/20528/

Ibarra Marinas, D., Belmonte Serrato, F., & Rubio Iborra, J. (2017). El impacto territorial del uso agrícola y turístico del litoral: evolución de los cambios de uso del suelo en las cuencas litorales del sur de la Región de Murcia (1956-2013). Boletín de la Asociación de Geógrafos Españoles, (73). https://doi.org/10.21138/bage.2419

Illán-Fernández, E.J., Pérez-Morales, A., & Romero-Díaz, A. (2022). El sellado antropogénico del suelo. Análisis bibliométrico. Cuadernos Geográficos, 61(1), 107-128. https://doi.org/10.30827/cuadgeo.v61i1.22293

Jacobson, C.R. (2011). Identification and quantification of the hydrological impacts of imperviousness in urban catchments: A review. Journal of environmental management, 92(6), 1438-1448. https://doi.org/10.1016/j.jenvman.2011.01.018

Lambin, E.F., & Geist, H.J. (Eds.). (2008). Land-use and land-cover change: local processes and global impacts. Springer Science & Business Media. https://doi.org/10.1007/3-540-32202-7

Lambin, E.F., & Meyfroidt, P. (2011). Global land use change, economic globalization, and the looming land scarcity. Proceedings of the National Academy of Sciences, 108(9), 3465-3472. https://doi.org/10.1073/pnas.1100480108

Landis, J.R., & Koch, G.G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33(1), 159-174. https://doi.org/10.2307/2529310

Lark, R.M. (1995). Components of accuracy of maps with special reference to discriminant analysis on remote sensor data. International Journal of Remote Sensing, 16(8), 1461-1480. https://doi.org/10.1080/01431169508954488

Loncan, L., De Almeida, L.B., Bioucas-Dias, J.M., Briottet, X., Chanussot, J., Fabre, S., Liao, W., Licciardi, G.A., Simoes, M., Tourneret, J.-Y., Veganzones, M.A., Vivone, G., Wei, Q., & Yokoya, N. (2015). Hyperspectral pansharpening: A review. IEEE Geoscience and remote sensing magazine, 3(3), 27-46. https://doi.org/10.1109/MGRS.2015.2440094

Martín-Górriz, B., Gallego-Elvira, B., Martínez-Alvarez, V., & Maestre-Valero, J.F. (2020). Life cycle assessment of fruit and vegetable production in the Region of Murcia (south-east Spain) and evaluation of impact mitigation practices. Journal of Cleaner Production, 265, 121656. https://doi.org/10.1016/j.jclepro.2020.121656

McGrane, S.J. (2016). Impacts of urbanisation on hydrological and water quality dynamics, and urban water management: a review. Hydrological Sciences Journal, 61(13), 2295-2311. https://doi.org/10.1080/02626667.2015.1128084

McGwire K.C., & Fisher P. (2001). Spatially Variable Thematic Accuracy: Beyond the Confusion Matrix. In C.T. Hunsaker, M.F. Goodchild, M.A. Friedl & T.J. Case (Eds.), Spatial Uncertainty in Ecology. Springer. https://doi.org/10.1007/978-1-4613-0209-4_14

Meyer, W.B., & Turner, B.L. (1992). Human population growth and global land-use/cover change. Annual review of ecology and systematics, 23(1), 39-61. https://doi.org/10.1146/annurev.es.23.110192.000351

Meyer, W.B., & Turner, B.L. (1994). Changes in land use and land cover: a global perspective (Vol. 4). Cambridge University Press. https://doi.org/10.1002/ldr.3400060308

Miller, J.D., & Hutchins, M. (2017). The impacts of urbanisation and climate change on urban flooding and urban water quality: A review of the evidence concerning the United Kingdom. Journal of Hydrology: Regional Studies, 12, 345-362. https://doi.org/10.1016/j.ejrh.2017.06.006

Mitsuda, Y., & Ito, S. (2011). A review of spatial-explicit factors determining spatial distribution of land use/land-use change. Landscape and Ecological Engineering, 7(1), 117-125. https://doi.org/10.1007/s11355-010-0113-4

Montanarella, L. (2007). Trends in land degradation in Europe. In Climate and land degradation (pp. 83-104). Springer. https://doi.org/10.1007/978-3-540-72438-4_5

Moore, A. (2016). Anthropocene anthropology: reconceptualizing contemporary global change. Journal of the Royal Anthropological Institute, 22(1), 27-46. https://doi.org/10.1111/1467-9655.12332

Naciones Unidas (2019). World Urbanization Prospects 2018: Highlights (ST/ESA/SER.A/421). Department of Economic and Social Affairs, Population Division. https://population.un.org/wup/Publications/Files/WUP2018-Highlights.pdf

Netzband, M., & Meinel, G. (1998). Identifying Urban Soil Sealing by High Resolution Remote Sensing Methods. In Urban Ecology (pp. 451-455). https://doi:10.1007/978-3-642-88583-9_91

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

Pedraza, A.C., Díaz, A.R., & Soto, I.E. (2015). Cambios paisajísticos y efectos medioambientales debidos a la agricultura intensiva en la Comarca de Campo de Cartagena - Mar Menor (Murcia). Estudios geográficos, 76(279), 473-498. https://doi.org/10.3989/estgeogr.201517

Peduzzi, P. (2019). The disaster risk, global change, and sustainability nexus. Sustainability, 11(4), 957. https://doi.org/10.3390/su11040957

Pistocchi, A., Calzolari, C., Malucelli, F., & Ungaro, F. (2015). Soil sealing and flood risks in the plains of Emilia-Romagna, Italy. Journal of Hydrology: Regional Studies, 4, 398-409. https://doi.org/10.1016/j.ejrh.2015.06.021

Radoux, J., Bogaert, P., Fasbender, D., & Defourny, P. (2011). Thematic accuracy assessment of geographic object-based image classification. International Journal of Geographical Information Science, 25(6), 895-911. https://doi.org/10.1080/13658816.2010.498378

Rodríguez-Galiano, V.F., & Chica-Rivas, M. (2014). Evaluation of different machine learning methods for land cover mapping of a Mediterranean area using multi-seasonal Landsat images and Digital Terrain Models. International Journal of Digital Earth, 7(6), 492-509. https://doi.org/10.1080/17538947.2012.748848

Rodríguez-Galiano, V., & Chica-Olmo, M. (2012). Land cover change analysis of a Mediterranean area in Spain using different sources of data: Multi-seasonal Landsat images, land surface temperature, digital terrain models and texture. Applied Geography, 35(1-2), 208-218. https://doi.org/10.1016/j.rse.2011.12.003

Romero Díaz, A., Caballero Pedraza, A., & Pérez Morales, A. (2017). Expansión urbana y turismo en la Comarca del Campo de Cartagena-Mar Menor (Murcia). Impacto en el sellado del suelo. Cuadernos de Turismo, (39), 521-546. https://doi.org/10.6018/turismo.39.290691

Rwanga, S.S., & Ndambuki, J.M. (2017). Accuracy assessment of land use/land cover classification using remote sensing and GIS. International Journal of Geosciences, 8(04), 611-622. https://doi.org/10.4236/ijg.2017.84033

Sage, R.F. (2020). Global change biology: A primer. Global Change Biology, 26(1), 3-30. https://doi.org/10.1111/gcb.14893

Sánchez Muñoz, J.M. (2016). Análisis de calidad cartográfica mediante el estudio de la matriz de confusión. Pensamiento Matemático, 6(2), 9-26. https://dialnet.unirioja.es/servlet/articulo?codigo=5998855

Sánchez-Picón, A., Aznar-Sánchez, J.A., & García-Latorre, J. (2011). Economic cycles and environmental crisis in arid southeastern Spain. A historical perspective. Journal of arid environments, 75(12), 1360-1367. https://doi.org/10.1016/j.jaridenv.2010.12.014

Scalenghe, R., & Marsan, F.A. (2009). The anthropogenic sealing of soils in urban areas. Landscape and urban planning, 90(1-2), 1-10. https://doi.org/10.1016/j.landurbplan.2008.10.011

Shuster, W.D., Bonta, J., Thurston, H., Warnemuende, E., & Smith, D.R. (2005). Impacts of impervious surface on watershed hydrology: A review. Urban Water Journal, 2(4), 263-275. https://doi.org/10.1080/15730620500386529

Śleszyński, P., Gibas, P., & Sudra, P. (2020). The problem of mismatch between the CORINE Land Cover data classification and the development of settlement in Poland. Remote Sensing, 12(14), 2253. https://doi.org/10.3390/rs12142253

Smith, P., House, J.I., Bustamante, M., Sobocká, J., Harper, R., Pan, G., West, P.C., Clark, J.M., Adhya, T., Rumpel, C., Paustian, K., Kuikman, P., Cotrufo, M.F., Elliott, J.A., McDowell, R., Griffiths, R.I., Asakawa, S., Bondeau, A., Jain, A.K., Meersmans, J., & Pugh, T.A.M. (2016). Global change pressures on soils from land use and management. Global change biology, 22(3), 1008-1028. https://doi.org/10.1111/gcb.13068

Song, X.P., Hansen, M.C., Stehman, S.V., Potapov, P.V., Tyukavina, A., Vermote, E.F., & Townshend, J.R. (2018). Global land change from 1982 to 2016. Nature, 560(7720), 639-643. https://doi.org/10.1038/s41586-018-0411-9

Srivastava, P.K., Han, D., Rico-Ramirez, M.A., Bray, M., & Islam, T. (2012). Selection of classification techniques for land use/land cover change investigation. Advances in Space Research, 50(9), 1250-1265. https://doi.org/10.1016/j.asr.2012.06.032

Steffen, W., Grinevald, J., Crutzen, P., & McNeill, J. (2011). The Anthropocene: conceptual and historical perspectives. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 369(1938), 842-867. https://doi.org/10.1098/rsta.2010.0327

Steffen, W., Sanderson, R.A., Tyson, P.D., Jäger, J., Matson, P.A., Moore III, B., Oldfield, F., Richardson, K., Schellnhuber, H.-J., Turner, B.L., & Wasson, R.J. (2006). Global change and the earth system: a planet under pressure. Springer Science & Business Media. https://doi.org/10.1007/b137870

Stehman, S.V. (2009). Sampling designs for accuracy assessment of land cover. International Journal of Remote Sensing, 30(20), 5243-5272. https://doi.org/10.1080/01431160903131000

Stehman, S.V., & Foody, G.M. (2019). Key issues in rigorous accuracy assessment of land cover products. Remote Sensing of Environment, 231, 111199. https://doi.org/10.1016/j.rse.2019.05.018

Strahler, A.H., Boschetti, L., Foody, G.M., Friedl, M. A., Hansen, M. C., Herold, M., Mayaux, P., Morisette, J.T., Stehman, S.V., & Woodcock, C.E. (2006). Global Land Cover Validation: Recommendations for Evaluation and Accuracy Assessment of Global Land Cover Maps (Report of Institute of Environmental Sustainability). Joint Research Centre, European Commission, Ispra. https://gofcgold.umd.edu/sites/default/files/docs/ReportSeries/GOLD_25.pdf

Thépaut, J.N., Dee, D., Engelen, R., & Pinty, B. (2018). The Copernicus programme and its climate change service. In IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium (pp. 1591-1593). IEEE. 10.1109/IGARSS.2018.8518067

Thomlinson, J.R., Bolstad, P.V., & Cohen, W.B. (1999). Coordinating methodologies for scaling landcover classifications from site-specific to global: Steps toward validating global map products. Remote Sensing of Environment, 70(1), 16-28. https://doi.org/10.1016/S0034-4257(99)00055-3

Tombolini, I., Munafò, M., & Salvati, L. (2016). Soil sealing footprint as an indicator of dispersed urban growth: a multivariate statistics approach. Urban Research & Practice, 9(1), 1-15. https://doi.org/10.1080/17535069.2015.1037340

Torrellas, M., Antón, A., López, J.C., Baeza, E. J., Parra, J.P., Muñoz, P., & Montero, J.I. (2012). LCA of a tomato crop in a multi-tunnel greenhouse in Almeria. The International Journal of Life Cycle Assessment, 17(7), 863-875. https://doi.org/10.1007/s11367-012-0409-8

Unión Europea (2021). European Parliament resolution on soil protection (2021/2548(RSP), 28 April 2021, P9_TA(2021)0143. https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:52021IP0143

Valera Lozano, A., Añó Vidal, C., & Sánchez Díaz, J. (2011). Crecimiento urbano (1956-2005) y sellado antropogénico del suelo en el municipio de Alacant. Serie Geográfica, (17), 97-108. https://digital.csic.es/handle/10261/43161

van Vliet, J., Bregt, A.K., & Hagen-Zanker, A. (2011). Revisiting Kappa to account for change in the accuracy assessment of land-use change models. Ecological modelling, 222(8), 1367-1375. https://doi.org/10.1016/j.ecolmodel.2011.01.017

Viera, A. J., & Garrett, J. M. (2005). Understanding interobserver agreement: the kappa statistic. Fam med, 37(5), 360-363. http://www1.cs.columbia.edu/~julia/courses/CS6998/Interrater_agreement.Kappa_statistic.pdf

Vitousek, P.M., Mooney, H.A., Lubchenco, J., & Melillo, J.M. (1997). Human domination of Earth's ecosystems. Science, 277(5325), 494-499. https://doi.org/10.1126/science.277.5325.494

Wickham, J., Stehman, S.V., Gass, L., Dewitz, J.A., Sorenson, D.G., Granneman, B.J., Poss, R.V., & Baer, L.A. (2017). Thematic accuracy assessment of the 2011 national land cover database (NLCD). Remote Sensing of Environment, 191, 328-341. https://doi.org/10.1016/j.rse.2016.12.026

Xiao, R., Su, S., Zhang, Z., Qi, J., Jiang, D., & Wu, J. (2013). Dynamics of soil sealing and soil landscape patterns under rapid urbanization. Catena, 109, 1-12. https://doi.org/10.1016/j.catena.2013.05.004

Zhang, N., Gao, Z., Wang, X., & Chen, Y. (2010). Modeling the impact of urbanization on the local and regional climate in Yangtze River Delta, China. Theoretical and applied climatology, 102(3), 331-342. https://doi.org/10.1007/s00704-010-0263-1