Built-up area analysis using Sentinel data in metropolitan areas of Transylvania, Romania
Abstract
The anthropic and natural elements have become more closely monitored and analysed through the use of remote sensing and GIS applications. In this regard, the study aims to feature a different approach to produce more and more thematic information, focusing on the development of built-up areas. In this paper, multispectral images and Synthetic Aperture Radar (SAR) images were the basis of a wide range of proximity analyses.
These allow the extraction of data about the distribution of built-up space on the areas with potential for economic and social development. Application of interferometric coherence and supervised classifications have been accomplished on various territories, such as metropolitan areas of the most developed region of Romania, more specifically Transylvania. The results indicate accuracy values, which can reach 94 per cent for multispectral datasets and 93 per cent for SAR datasets. The accuracy of resulted data will reveal a variety of city patterns, depending mainly on local features regarding natural and administrative environments. In this way, a comparison will be made between the accuracy of both datasets to provide an analysis of the manner of built-up areas distribution to assess the expansion of the studied metropolitan areas. Therefore, this study aims to apply well-established methods from the remote sensing field to enhance the information and datasets in some areas lacking recent research.
References
Abdikan, S., Sanli, F.B., Ustuner, M. and Calò, F. 2016. Land cover mapping using SENTINEL-1 SAR data. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B7. 757-761. https://doi.org/10.5194/isprs-archives-XLI-B7-757-2016
As-Syakur, A.R., Adnyana, I.W.S., Arthana, I.W. and Nuarsa, I.W. 2012. Enhanced Built-up and Bareness Index (EBBI) for mapping built-up and bare land in an urban area. Remote Sensing 4. 2957-2970. https://doi.org/10.3390/rs4102957
Cîmpianu, C. and Corodescu, E. 2013. Landscape dy namics analysis in Iași Metropolitan Area (Romania) using remote sensing data. Cinq Continents 3. (7): 18-32.
Congalton, R.G. 1991. A review of assessing the accu racy of classifications of remotely sensed data. Remote Sensing of Environment 37. (1): 35-46. https://doi.org/10.1016/0034-4257(91)90048-B
Congalton, R.G. and Green, K. 2009. Assessing the Accuracy of Remotely Sensed Data: Principles and Practices. Boca Raton, Lewis Publishers. https://doi.org/10.1201/9781420055139
Copăcean, L., Popescu, C. and Cojocariu, L. 2015. Remote sensing methods for analysing vegetation and urban expansion. Research Journal of Agricultural Science 47. (4): 41-46.
Corbane, C., Faure, J.F., Baghdadi, N., Villeneuve, N. and Petit, M. 2008. Rapid urban mapping using SAR/Optical Imagery Synergy. Sensors 8. (11): 7125-7143. https://doi.org/10.3390/s8117125
Corbane, C., Pesaresi, M., Politis, P., Syrris, V., Florczyk, A.J., Soille, P., Maffenini, L., Burger, A., Vasilev, V., Rodriguez, D., Sabo, F., Dijkstra, L. and Kemper, T. 2017. Big earth data analytics on Sentinel-1 and Landsat imagery in support to global human settlements mapping. Big Earth Data 1. (1-2): 18-144. https://doi.org/10.1080/20964471.2017.1397899
Corodescu, E. and Cîmpianu, C. 2014. Assessing the spatial differences among some urban expansion driving forces in Constanța Metropolitan Area (Romania). Scientific Annals of "Al. I. Cuza" University of Iaşi Geography Series 60. (2): 77-95.
Deng, Y., Fan, F. and Chen, R. 2012. Extraction and analysis of impervious surfaces based on a spectral un-mixing method using Pearl River Delta of China Landsat TM/ETM+ Imagery from 1998 to 2008. Sensors 12. (2): 1846-1862. https://doi.org/10.3390/s120201846
Dewan, A.M. and Yamaguchi, Y. 2009. Land use and land cover change in Greater Dhaka, Bangladesh: Using remote sensing to promote sustainable urbani sation. Applied Geography 29. 390-401. https://doi.org/10.1016/j.apgeog.2008.12.005
EEA 2006. The Changing Faces of Europe's Coastal Areas. Copenhagen, Denmark, European Environment Agency. Report No 6/2006.
Esch, T., Marconcini, M., Felbier, A., Roth, A., Heldens, W., Huber, M., Schwinger, M., Taubenböck, H., Müller, A. and Dech, A. 2013. Urban footprint processor - fully automated processing chain gen erating settlement masks from global data of the TanDEM-X Mission. IEEE Geoscience and Remote Sensing Letters 10. (6): 1617-1621. https://doi.org/10.1109/LGRS.2013.2272953
Ferretti, A., Monti-Guarnieri, A., Prati, C., Rocca, F. and Massonnet, D. 2008. InSAR Principles: Guidelines for SAR Interferometry Processing and Interpretation. ESA Publications.
Forkour, G., Dibobe, K., Serme, I. and Tondoh, J.E. 2018. Landsat-8 vs. Sentinel-2: examining the added value of sentinel-2's red-edge bands to land-use and land cover mapping in Burkina Faso. GIScience & Remote Sensing 55. (3): 331-354. https://doi.org/10.1080/15481603.2017.1370169
FZMAUR 2013. Federation of Metropolitan Areas and Urban Agglomerations in Romania. Bucharest, Studiu POLICENTRIC.
Grigorescu, I., Mitrică, B., Mocanu, I. and Ticana, N. 2012. Urban sprawl and residential development in the Romanian metropolitan areas. Romanian Journal of Geography 56. (1): 43-59.
Grigorescu, I., Kucsicsa, G. and Mitrică, B. 2014. Assessing spatio-temporal dynamics of urban sprawl in the Bucharest metropolitan area over the last century. In Land Use/Cover Changes in Selected Regions in the World. Volume V. Eds.: Bičík, I., Himiyama, Y. and Feranec, J., Prague, Czech Republic, IGU LUCC, 19-27.
Holobâcă, I.H., Ivan, K. and Alexe, M. 2019. Extracting built-up areas from Sentinel-1 imagery using land cover classification and texture analysis. International Journal of Remote Sensing 40. (20): 8054-8069. https://doi.org/10.1080/01431161.2019.1608391
Huzui, A.E., Călin, I. and Stupariu, P.I. 2012. Spatial pattern analyses of landscape using multi temporal data sources. Procedia Environmental Sciences 14. 98-110. https://doi.org/10.1016/j.proenv.2012.03.010
INS, National Institute of Statistics Romania. 2019. Permanent Resident Population. Bucharest, Romania. Accessed July 2019. http://www.insse.ro.
Ivan, K. 2015. The spatio-temporal analysis of imper vious surfaces in Cluj-Napoca, Romania. Geographia Technica 10 (2): 50-58.
Kaimaris, D. and Patias, P. 2016. Identification and area measurement of the built-up area with the Built-up Index (BUI). International Journal of Advanced Remote Sensing and GIS 5. (6): 1844-1858. https://doi.org/10.23953/cloud.ijarsg.64
Khalil, R.Z. and Haque, S.U. 2017. InSAR coherence based land cover classification of Okara, Pakistan. The Egyptian Journal of Remote Sensing and Space Science 21. (1): 523-528. https://doi.org/10.1016/j.ejrs.2017.08.005
Koppel, K., Zalite, K., Sisas, A., Voormansik, K., Praks, J. and Noorma, M. 2015. Sentinel-1 for urban area monitoring - analysing local-area statistics and interferometric coherence methods for buildings' detec tion. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 26-31 July 2015. Milan, Italy. 1175-1178. https://doi.org/10.1109/IGARSS.2015.7325981
Kuemmerle, T., Muller, D., Griffiths, P. and Rusu, M. 2008. Land use change in Southern Romania after the collapse of socialism. Regional Environmental Change 9. (1): 1-12. https://doi.org/10.1007/s10113-008-0050-z
Li, H., Wang, C., Zhong, C., Su, A., Xiong, C., Wang, J. and Liu, J. 2017. Mapping urban bare land au tomatically from Landsat imagery with a simple index. Remote Sensing 9. (3): 249. https://doi.org/10.3390/rs9030249
Lillesand, T.M. and Kiefer, R.W. 1994. Remote Sensing and Image Interpretation. 3rd Edition. Hoboken, N.Y., John Wiley and Sons, Inc.
Ma, Y. and Xu, R. 2010. Remote sensing monitoring and driving force analysis of urban expansion in Guangzhou City, China. Habitat International 34. (2): 228-235. https://doi.org/10.1016/j.habitatint.2009.09.007
Mihai, B., Nistor, C. and Simion, G. 2015. Post-socialist urban growth of Bucharest, Romania - a change de tection analysis on Landsat imagery (1984-2010). Acta Geographica Slovenica 55. (2): 223-234. https://doi.org/10.3986/AGS.709
Mitrică, B. and Grigorescu, I. 2016. Dezvoltarea urbană şi ariile metropolitane (Urban develop ment and metropolitan areas). In Romania. Natura si Societate. Eds.: Balteanu, D., Dumitrascu, M., Geacu, S., Mitrica, B. and Sima, M., Bucuresti, Editura Academiei Romane, 250-291.
Mucsi, L., Liska, C.M., Henits, L., Tobak, Z., Csendes, B. and Nagy, L. 2017. The evaluation and applica tion of an urban land cover map with image data fusion and laboratory measurements. Hungarian Geographical Bulletin 66. (2): 145-15. https://doi.org/10.15201/hungeobull.66.2.4
Padmanaban, R., Bhowmik, A.K., Cabral, P., Zamyatin, A., Almegdadi, O. and Wang, S. 2017.Modelling urban sprawl using remotely sensed data: A case study of Chennai City, Tamilnadu. Entropy 19. (4): 163. https://doi.org/10.3390/e19040163
Pesaresi, M., Corbane, C., Julea, A., Florczyk, A.J., Syssis, V. and Soille, P. 2016. Assessment of the added-value of Sentinel-2 for detecting built-up areas. Remote Sensing 8. (4): 299. https://doi.org/10.3390/rs8040299
Sandric, I., Mihai, B., Savulescu, I., Suditu, B. and Chitu, Z. 2007. Change detection analysis for urban development in Bucharest-Romania, using high resolution satellite imagery. Urban Remote Sensing Joint Event 2007. 1-8. https://doi.org/10.1109/URS.2007.371848
Sekertekin, A., Marangoz, A.M. and Akcin, H. 2017. Pixel-based classification analysis of land use land cover using SENTINEL-2 and LANDSAT-8 data. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W6. 91-93. https://doi.org/10.5194/isprs-archives-XLII-4-W6-91-2017
Vorovencii, I. 2017. Analysis of the changes in the metropolitan area of Brașov, Romania, us ing Landsat multi-temporal satellite image. Environmental Engineering and Management Journal (EEMJ) 16. (2): 303-316. https://doi.org/10.30638/eemj.2017.031
Xu, H. 2010. A new index for delineating built-up land features in satellite imagery. International Journal of Remote Sensing 29. (14): 4269-4276. https://doi.org/10.1080/01431160802039957
Yuan, F., Sawaya, K.E., Loeffelholz, B.C. and Bauer, M.E. 2005. Land cover classification and change analysis of the Twin Cities (Minnesota) Metropolitan Area by multi-temporal Landsat remote sensing. Remote Sensing of Environment 98. (2): 317-328. https://doi.org/10.1016/j.rse.2005.08.006
Zakeri, H., Yamazaki, F. and Liu, W. 2017. Texture analysis and land cover classification of Tehran us ing polarimetric Synthetic Aperture Radar imagery. Applied Sciences 7. 452. https://doi.org/10.3390/app7050452
Zha, Y., Gao, J. and Ni, S. 2003. Use of normalized difference built-up index in automatically mapping urban areas from TM imagery. International Journal of Remote Sensing 24. (3): 583-594. https://doi.org/10.1080/01431160304987
Zoran, M. and Weber, C. 2007. Use of multi-temporal and multispectral satellite data for urban change detection analysis. Journal of Optoelectronics and Advanced Materials 9. (6): 1926-1932.
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