Analysis of Built-Up Classes in Urbanised Zones Using Radar Images

BIP [Biuletyn Informacji Publicznej], 2021. Biuletyn Informacji Publicznej Urzędu Miasta Gdyni. Online: bip.um.gdynia.pl (accessed 8 July 2021). BIP [Biuletyn Informacji Publicznej] , 2021 . Biuletyn Informacji Publicznej Urzędu Miasta Gdyni . Online: bip.um.gdynia.pl ( accessed 8 July 2021 ). Search in Google Scholar

Braun A., Hochschild V., 2015. Combining SAR and optical data for environmental assessments around refugee camps. Eberhard Karls University, Tybinga. Braun A. Hochschild V. , 2015 . Combining SAR and optical data for environmental assessments around refugee camps . Eberhard Karls University , Tybinga . Search in Google Scholar

Braun A., Saulgau B., 2019. Radar satellite imagery for humanitarian response. Bridging the gap between technology and application. Eberhard Karls University, Tybinga. Braun A. Saulgau B. , 2019 . Radar satellite imagery for humanitarian response. Bridging the gap between technology and application . Eberhard Karls University , Tybinga . Search in Google Scholar

Breinman L., 2001. Random forests. Machine Learning 45(1): 5–32. Breinman L. , 2001 . Random forests . Machine Learning 45 ( 1 ): 5 – 32 . Search in Google Scholar

Breinman L., Cutler A., 2021. Online: https://www.stat.berkeley.edu/~breiman/RandomForests/cc_home.htm (accessed 14 February 2021). Breinman L. Cutler A. , 2021 Online https://www.stat.berkeley.edu/~breiman/RandomForests/cc_home.htm ( accessed 14 February 2021 ). Search in Google Scholar

Chen C.H., 2008. Image processing for remote sensing. Taylor & Francis Group Boca Raton: 39–106, 341–354. Chen C.H. , 2008 . Image processing for remote sensing . Taylor & Francis Group Boca Raton : 39–106 , 341 – 354 . Search in Google Scholar

Chen D., Stow D.A., Gong P., 2004. Examining the effect of spatial resolution and texture window size on classification accuracy: An urban environment case. International Journal of Remote Sensing 25(11): 2177–2192. DOI 10.1080/01431160310001618464. Chen D. Stow D.A. Gong P. , 2004 . Examining the effect of spatial resolution and texture window size on classification accuracy: An urban environment case . International Journal of Remote Sensing 25 ( 11 ): 2177 – 2192 . DOI 10.1080/01431160310001618464 . Open DOISearch in Google Scholar

Clausi D.A., 2002. An analysis of co-occurrence texture statistics as a function of grey level quantization. Canadian Journal of Remote Sensing 28(1): 45–62. Clausi D.A. , 2002 . An analysis of co-occurrence texture statistics as a function of grey level quantization . Canadian Journal of Remote Sensing 28 ( 1 ): 45 – 62 . Search in Google Scholar

Congalton R.G., Green K., 2009. Assessing the accuracy of remotely sensed data: Principles and practices. 2nd edn. Lewis Publishers, Boca Raton. Congalton R.G. Green K. , 2009 . Assessing the accuracy of remotely sensed data: Principles and practices . 2nd edn . Lewis Publishers , Boca Raton . Search in Google Scholar

Creodias Finder. Online: https://finder.creodias.eu/ (accessed 2 March 2021). Creodias Finder . Online: https://finder.creodias.eu/ ( accessed 2 March 2021 ). Search in Google Scholar

Dell’Acqua F., Gamba P., 2003. Texture-based characterisation of urban environments on satellite SAR images. IEEE Transactions on Geoscience and Remote Sensing 41(1): 153–159. Dell’Acqua F. Gamba P. , 2003 . Texture-based characterisation of urban environments on satellite SAR images . IEEE Transactions on Geoscience and Remote Sensing 41 ( 1 ): 153 – 159 . Search in Google Scholar

Denis M., 2018. Selected issues regarding small compact city – Advantages and disadvantages. Space and Form 34: 151–162. DOI 10.21005/pif.2018.34.C-03. Denis M. , 2018 . Selected issues regarding small compact city – Advantages and disadvantages . Space and Form 34 : 151 – 162 . DOI 10.21005/pif.2018.34.C-03 . Open DOISearch in Google Scholar

Eckardt R., Urbazaev M., Salepci N., Pathe C., Schmullius Ch., Woodhouse I., Stewart Ch., 2021. Echoes in Space. Introduction to Radar Remote Sensing. SAR MOOC Manuscript, EO-College.org, ESA, EOS. Friedrich-Schiller-University of Jena. Online: https://eo-college.org/resource/urban_lc/ (accessed 03 September 2021). Eckardt R. Urbazaev M. Salepci N. Pathe C. Schmullius Ch. Woodhouse I. Stewart Ch. , 2021 . Echoes in Space. Introduction to Radar Remote Sensing . SAR MOOC Manuscript, EO-College.org, ESA, EOS . Friedrich-Schiller-University of Jena . Online: https://eo-college.org/resource/urban_lc/ ( accessed 03 September 2021 ). Search in Google Scholar

GHSL [Global Human Settlement Layer], 2022. Urban footprint. Online: https://ghsl.jrc.ec.europa.eu/ (accessed 19 December 2022). GHSL [Global Human Settlement Layer] , 2022 . Urban footprint . Online: https://ghsl.jrc.ec.europa.eu/ ( accessed 19 December 2022 ). Search in Google Scholar

Giannini M.B., Merola P., Allegrini A., 2012. Texture analysis for urban areas classification in high resolution satellite imagery. Applied Remote Sensing Journal 2(2): 65–71. Giannini M.B. Merola P. Allegrini A. , 2012 . Texture analysis for urban areas classification in high resolution satellite imagery . Applied Remote Sensing Journal 2 ( 2 ): 65 – 71 . Search in Google Scholar

Goodman J.W., 1976. Some fundamental properties of speckle. Journal of the Optical Society of America 66(11): 1145–1150. Goodman J.W. , 1976 . Some fundamental properties of speckle . Journal of the Optical Society of America 66 ( 11 ): 1145 – 1150 . Search in Google Scholar

Hall-Beyer M., 2017a. GLCM texture: A tutorial v. 3.0. Department of Geography, University of Calgary. Hall-Beyer M. , 2017a . GLCM texture: A tutorial v. 3.0 . Department of Geography, University of Calgary . Search in Google Scholar

Hall-Beyer M., 2017b. Practical guidelines for choosing GLCM textures to use in landscape classification tasks over a range of moderate spatial scales. International Journal of Remote Sensing 38(5): 1312–1338. Hall-Beyer M. , 2017b . Practical guidelines for choosing GLCM textures to use in landscape classification tasks over a range of moderate spatial scales . International Journal of Remote Sensing 38 ( 5 ): 1312 – 1338 . Search in Google Scholar

Haralick R.M., Shanmugam K., Dinstein I., 1973. Textural features for image classification. IEEE Transactions on Systems, Man, and Cybernetics 3: 610–621. Haralick R.M. Shanmugam K. Dinstein I. , 1973 . Textural features for image classification . IEEE Transactions on Systems, Man, and Cybernetics 3 : 610 – 621 . Search in Google Scholar

Herold M., Goldstein N.C., Clarke K.C., 2003. The spatiotemporal form of urban growth: Measurement, analysis and modeling. Remote Sensing of Environment 86(3): 286–302. DOI 10.1016/S0034-4257(03)00075-0. Herold M. Goldstein N.C. Clarke K.C. , 2003 . The spatiotemporal form of urban growth: Measurement, analysis and modeling . Remote Sensing of Environment 86 ( 3 ): 286 – 302 . DOI 10.1016/S0034-4257(03)00075-0 . Open DOISearch in Google Scholar

Holobâcă I.-H., Ivan K., Alexe M., 2019. Extracting built-up areas from Sentinel-1 imagery using land-cover classification and texture analysis. International Journal of Remote Sensing 40: 8054–8069. Holobâcă I.-H. Ivan K. Alexe M. , 2019 . Extracting built-up areas from Sentinel-1 imagery using land-cover classification and texture analysis . International Journal of Remote Sensing 40 : 8054 – 8069 . Search in Google Scholar

Huang X., Zhang T., 2020. Morphological building index (MBI) and its applications to urban areas. In: Weng Q., Quattrochi D., Gamba P. (eds), Urban remote sensing. 2nd edition Taylor & Francis Group Boca Raton: 33–49. Huang X. Zhang T. , 2020 . Morphological building index (MBI) and its applications to urban areas . In: Weng Q. Quattrochi D. Gamba P. (eds), Urban remote sensing . 2^nd edition Taylor & Francis Group Boca Raton : 33 – 49 . Search in Google Scholar

ICEYE Specification. Online: https://www.iceye.com/satellite-missions (accessed 2 March 2021). ICEYE Specification . Online: https://www.iceye.com/satellite-missions ( accessed 2 March 2021 ). Search in Google Scholar

Joelsson S.R., Benediktsson J.A., Sveinsson J.R., 2008. Random forest classification of remote sensing data. In: Chen C.H. (ed.), Image processing for remote sensing. Taylor & Francis Group: 61–78. Joelsson S.R. Benediktsson J.A. Sveinsson J.R. , 2008 . Random forest classification of remote sensing data . In: Chen C.H. (ed.), Image processing for remote sensing . Taylor & Francis Group : 61 – 78 . Search in Google Scholar

Kamusoko C., 2022. Optical and SAR remote sensing of urban areas. A practical guide. Springer: 71–103. Kamusoko C. , 2022 . Optical and SAR remote sensing of urban areas. A practical guide . Springer : 71 – 103 . Search in Google Scholar

Kupidura P., 2015. Application of image granulometry to classification of satellite images. Publishing House of Warsaw University of Technology, Warsaw. Kupidura P. , 2015 . Application of image granulometry to classification of satellite images . Publishing House of Warsaw University of Technology , Warsaw . Search in Google Scholar

Kupidura P., 2019. The comparison of different methods of texture analysis for their efficacy for land use classification in satellite imagery. Remote Sensing 11(10): 1233. DOI 10.3390/rs11101233. Kupidura P. , 2019 . The comparison of different methods of texture analysis for their efficacy for land use classification in satellite imagery . Remote Sensing 11 ( 10 ): 1233 . DOI 10.3390/rs11101233 . Open DOISearch in Google Scholar

Kupidura P., Uwarowa I., 2017. The comparison of GLCM and granulometry for distinction of different classes of urban area. In: 2017 Joint Urban Remote Sensing Event (JURSE). IEEE. DOI 10.1109/JURSE.2017.7924615. Kupidura P. Uwarowa I. , 2017 . The comparison of GLCM and granulometry for distinction of different classes of urban area . In: 2017 Joint Urban Remote Sensing Event (JURSE) . IEEE . DOI 10.1109/JURSE.2017.7924615 . Open DOISearch in Google Scholar

Lewiński S., Aleksandrowicz S., 2012. Evaluation of usability of texture in identifying basic land cover classes on the satellite images of different resolutions. Archiwum Fotogrametrii, Kartografii i Teledetekcji 23: 229–237. Lewiński S. Aleksandrowicz S. , 2012 . Evaluation of usability of texture in identifying basic land cover classes on the satellite images of different resolutions . Archiwum Fotogrametrii, Kartografii i Teledetekcji 23 : 229 – 237 . Search in Google Scholar

Mohanaiah P., Sathyanarayana P., GuruKumar L., 2013. Image texture feature extraction using GLCM approach. International Journal of Scientific and Research Publications 3(5): 1–5. Mohanaiah P. Sathyanarayana P. GuruKumar L. , 2013 . Image texture feature extraction using GLCM approach . International Journal of Scientific and Research Publications 3 ( 5 ): 1 – 5 . Search in Google Scholar

Molch K., 2009. Radar earth observation imagery for urban area characterizations. JRC Scientific and Technical Reports, European Communities, Luxembourg. Molch K. , 2009 . Radar earth observation imagery for urban area characterizations . JRC Scientific and Technical Reports, European Communities , Luxembourg . Search in Google Scholar

Okwuashi O., Isong M., Eyo E., Eyoh A., Nwanekezie O., Olayinka D.N., Udoudo D.O., Ofem B., 2012. GIS cellular automata using artificial neural network for land use change simulation of Lagos, Nigeria. Journal of Geography and Geology 4(2): 94–101. Okwuashi O. Isong M. Eyo E. Eyoh A. Nwanekezie O. Olayinka D.N. Udoudo D.O. Ofem B. , 2012 . GIS cellular automata using artificial neural network for land use change simulation of Lagos, Nigeria . Journal of Geography and Geology 4 ( 2 ): 94 – 101 . Search in Google Scholar

Park Y., Guldmann J.-M., 2020. Measuring continuous landscape patterns with gray-level co-occurrence matrix (GLCM) indices: An alternative to patch metrics? Ecological Indicators 109: 105802, DOI 10.1016/j.ecol-ind.2019.105802. Park Y. Guldmann J.-M. , 2020 . Measuring continuous landscape patterns with gray-level co-occurrence matrix (GLCM) indices: An alternative to patch metrics? Ecological Indicators 109 : 105802 , DOI 10.1016/j.ecol-ind.2019.105802 . Open DOISearch in Google Scholar

Pathak V., Dikshit O., 2010. A new approach for finding an appropriate combination of texture parameters for classification. Geocarto International 25: 295–313. Pathak V. Dikshit O. , 2010 . A new approach for finding an appropriate combination of texture parameters for classification . Geocarto International 25 : 295 – 313 . Search in Google Scholar

Richards J.A., 2013. Remote sensing digital image analysis. An introduction, 5th edn. Springer-Verlag Berlin Heidelberg: 247–315, 381–433. Richards J.A. , 2013 . Remote sensing digital image analysis. An introduction , 5th edn . Springer-Verlag Berlin Heidelberg : 247–315 , 381 – 433 . Search in Google Scholar

SDG [Sustainable Development Goals], 2015. Goals/Tasks 11.1.1 and 11.3.1. 2022. Online: https://sdgs.un.org/ goals/goal11 (accessed 23 May 2022). SDG [Sustainable Development Goals] , 2015 . Goals/Tasks 11.1.1 and 11.3.1. 2022 . Online: https://sdgs.un.org/goals/goal11 ( accessed 23 May 2022 ). Search in Google Scholar

Semenzato A., Pappalardo S.E., Codato D., Trivelloni U., De Zorzi S., Ferrari S., De Marchi M., Massironi M., 2020. Mapping and monitoring urban environment through sentinel-1 SAR data: A case study in the Veneto Region (Italy). ISPRS International Journal of Geo-Information 9: 375. DOI 10.3390/ijgi9060375. Semenzato A. Pappalardo S.E. Codato D. Trivelloni U. De Zorzi S. Ferrari S. De Marchi M. Massironi M. , 2020 . Mapping and monitoring urban environment through sentinel-1 SAR data: A case study in the Veneto Region (Italy) . ISPRS International Journal of Geo-Information 9 : 375 . DOI 10.3390/ijgi9060375 . Open DOISearch in Google Scholar

Sentinel-1 Specification. Online: https://sentinels.coperni-cus.eu/web/sentinel/user-guides/sentinel-1-sar/data-formats/safe-specification (accessed 2 March 2021). Sentinel-1 Specification . Online: https://sentinels.coperni-cus.eu/web/sentinel/user-guides/sentinel-1-sar/data-formats/safe-specification ( accessed 2 March 2021 ). Search in Google Scholar

Snitkowska E., 2004. Analiza tekstur w obrazach cyfrowych i jej zastosowanie do obrazów angiograficznych – rozprawa doktorska. Politechnika Warszawska, Wydział Elektroniki i Technik Informacyjnych, Instytut Automatyki i Informatyki Stosowanej. Snitkowska E. , 2004 . Analiza tekstur w obrazach cyfrowych i jej zastosowanie do obrazów angiograficznych – rozprawa doktorska . Politechnika Warszawska, Wydział Elektroniki i Technik Informacyjnych, Instytut Automatyki i Informatyki Stosowanej . Search in Google Scholar

Urban Atlas Database. Online: https://land.copernicus.eu/local/urban-atlas (accessed 2 March 2021). Urban Atlas Database . Online: https://land.copernicus.eu/local/urban-atlas ( accessed 2 March 2021 ). Search in Google Scholar

Urban Atlas Guide. Online: https://land.copernicus.eu/user-corner/technical-library/urban-atlas-mapping-guide (accessed 2 March 2021). Urban Atlas Guide . Online: https://land.copernicus.eu/user-corner/technical-library/urban-atlas-mapping-guide ( accessed 2 March 2021 ). Search in Google Scholar

Wellmann T., Haase D., Knapp S., Salbach C., Selsam P., Lausch A., 2018. Urban land use intensity assessment: The potential of spatio-temporal spectral traits with remote sensing. Ecological Indicators 85: 190–203. Wellmann T. Haase D. Knapp S. Salbach C. Selsam P. Lausch A. , 2018 . Urban land use intensity assessment: The potential of spatio-temporal spectral traits with remote sensing . Ecological Indicators 85 : 190 – 203 . Search in Google Scholar

Yoshioka M., Fujinaka T., Omatu S., 2008. SAR image classification by support vector machine. In: Chen C.H. (ed.), Image processing for remote sensing. Taylor & Francis Group: 341–353. Yoshioka M. Fujinaka T. Omatu S. , 2008 . SAR image classification by support vector machine . In: Chen C.H. (ed.), Image processing for remote sensing . Taylor & Francis Group : 341 – 353 . Search in Google Scholar

Zhang Q, Wang J., 2001. Texture analysis for urban spatial pattern study using SPOT imagery. In: Proceedings IEEE International Geoscience and Remote Sensing Symposium: 2149–2151. 9–13 July 2001, University of New South Wales, Sydney, Australia. Zhang Q Wang J. , 2001 . Texture analysis for urban spatial pattern study using SPOT imagery . In: Proceedings IEEE International Geoscience and Remote Sensing Symposium: 2149–2151 . 9 – 13 July 2001 , University of New South Wales , Sydney, Australia . Search in Google Scholar