Applying Multi-Index approach from Sentinel-2 Imagery to Extract Urban Area in dry season (Semi-Arid Land in North East Algeria)

K. Rouibah, M. Belabbas

Abstract

The mapping of urban areas mostly presents a big difficulty, particularly, in arid and semi-arid environments. For that reason, in this research, we expect to increase built up accuracy mapping for Bordj Bou Arreridj city in semi-arid regions (North-East Algeria) by focusing on the identification of appropriate combination of the remotely sensed spectral indices. The study applies the ‘k–means’ classifier. In this regard, four spectral indexes were selected, namely normalized difference tillage index (NDTI) for built-up, and both bare soil index (BSI) and dry bare-soil index (DBSI), which are related to bare soil, as well as the normalized difference vegetation index (NDVI). All previous spectral indices mentioned were derived from Sentinel-2 data acquired during the dry season. Two combinations of them were generated using layer stack process, keeping both of NDTI and NDVI index constant in both combinations so that the multi-index NDTI/BSI/NDVI was the first single dataset combination, and the multi-index NDTI/DBSI/NDVI as the second component. The results show that BSI index works better with NDTI index compared to the use of DBSI index. Therefore, BSI index provides improvements: bare soil classes and built-up were better discriminated, where the overall accuracy increased by 5.67% and the kappa coefficient increased by 12.05%. The use of k-means as unsupervised classifier provides an automatic and a rapid urban area detection. Therefore, the multi-index dataset NDTI/ BSI / NDVI was suitable for mapping the cities in dry climate, and could provide a better urban management and future remote sensing applications in semi-arid areas particularly.


Keywords

Sentinel-2A; Multi- Index dataset; Built-Up Area; Bare Soil; Semi-Arid Land

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References

Al-Quraishi, A. ( 2011). Drought mapping using Geoinformation technology for some sites in the Iraqi Kurdistan region. International Journal of Digital Earth, 4, 239-257. https://doi.org/10.1080/17538947.2010.489971

Becerril-Piña, R., Mastachi-Loza, C. A., González-Sosa, E., Díaz-Delgado, C., Bâ, K. M. ( 2015). Assessing desertification risk in the semi-arid highlands of central Mexico. Journal of Arid Environments, 120, 4-13. https://doi.org/10.1016/j.jaridenv.2015.04.006

Bouzekri, S., Aziz Lasbet, A., Lachehab, A. ( 2015). A New Spectral Index for Extraction of Built-Up Area Using Landsat-8 Data. Journal of the Indian Society of Remote Sensing, 43. https://doi.org/10.1007/s12524-015-0460-6

Bramhe, V., Ghosh, S., Garg, P. ( 2018). EXTRACTION OF BUILT-UP AREA BY COMBINING TEXTURAL FEATURES AND SPECTRAL INDICES FROM LANDSAT-8 MULTISPECTRAL IMAGE. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLII-5, 727-733. https://doi.org/10.5194/isprs-archives-XLII-5-727-2018

Chen, W., Liu, L., Zhang, C., Wang, J., Wang, J., Pan, Y. ( 2004). Monitoring the seasonal bare soil areas in Beijing using multitemporal TM images. Paper presented at the IGARSS 2004. 2004 IEEE International Geoscience and Remote Sensing Symposium. (Vol. 5, pp. 3379-3382). https://doi.org/10.1109/IGARSS.2004.1370429

Congalton, R. ( 1991). A Review of Assessing the Accuracy of Classifications of Remotely Sensed Data (Vol. 37). https://doi.org/10.1016/0034-4257(91)90048-B

Congedo, L. (2016). Semi-Automatic Classification Plugin Documentation. Release 6.0.1.1.

Côte, M. ( 1996). L'algerie espace er societe paris: masson.

Daughtry, C. S. T., Serbin, G., Reeves, J. B., Doraiswamy, P. C., Hunt, E. R. ( 2010). Spectral Reflectance of Wheat Residue during Decomposition and Remotely Sensed Estimates of Residue Cover. Remote Sensing, 2(2), 416-431. https://doi.org/10.3390/rs2020416

Deng, C., Wu, C. ( 2012). BCI: A biophysical composition index for remote sensing of urban environments. Remote Sensing of Environment, 127, 247-259. https://doi.org/10.1016/j.rse.2012.09.009

Deventer, A., Ward, A. D., Gowda, P. H., Lyon, J. G. (1997). Using thematic mapper data to identify contrasting soil plains and tillage practices. Photogrammetric engineering and remote sensing., 63(1), 87-93.

Diek, S., Fornallaz, F., Schaepman, M., Jong, R. ( 2017). Barest Pixel Composite for Agricultural Areas Using Landsat Time Series. Remote Sensing, 9, 1245. https://doi.org/10.3390/rs9121245

Doumit, J., Sakr, S. ( 2015). La Cartographie du Sol nu dans la Vallee de la Bekaa à partir de la Tetedetection. InterCarto. InterGIS, 1, 19-24. https://doi.org/10.24057/2414-9179-2015-1-21-19-24

Drusch M, U., D. B., S., C., Colin, O., Fernandez, V., Gascon, F., . . . Bargellini, P. ( 2012). Sentinel-2: ESA's Optical High-Resolution Mission for GMES Operational Services. Remote Sensing of Environment, 120, 25-36. https://doi.org/10.1016/j.rse.2011.11.026

Eskandari, I., Navid, H., Rangzan, K. ( 2016). Evaluating spectral indices for determining conservation and conventional tillage systems in a vetch-wheat rotation. International Soil and Water Conservation Research, 4(2), 93-98. https://doi.org/10.1016/j.iswcr.2016.04.002

Ettehadi Osgouei, P., Kaya, S., Sertel, E., Alganci, U. ( 2019). Separating Built-Up Areas from Bare Land in Mediterranean Cities Using Sentinel-2A Imagery. Remote Sensing, 11(3). https://doi.org/10.3390/rs11030345

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

Gašparović, M., Zrinjski, M., Gudelj, M. ( 2019). Automatic cost-effective method for land cover classification (ALCC). Computers, Environment and Urban Systems, 76, 1-10. https://doi.org/10.1016/j.compenvurbsys.2019.03.001

Gllavata, J., Ewerth, R., Freisleben, B. (2004). Text detection in images based on unsupervised classification of high-frequency wavelet coefficients. Paper presented at the Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004. https://doi.org/10.1109/ICPR.2004.1334146

Gupta, G., Singh, J., Pandey, P., Tomar, V., Rani, M., Kumar, P. ( 2014). Geospatial Strategy for Estimation of Soil Organic Carbon in Tropical Wildlife Reserve. pp. 69-83. https://doi.org/10.1007/978-3-319-05906-8_5.

Jamalabad, M. ( 2004). Forest canopy density monitoring using satellite images. Paper presented at the Geo-Imagery Bridging Continents XXth ISPRS Congress, Istanbul, Turkey, 2004.

Jieli, C. M., L.; Yongxue, L.; Chenglei, S.; Wei, H. ( 2010). Extract residential areas automatically by New Built-up Index. . Paper presented at the In Proceedings of the 2010 18th International Conference on Geoinformatics, Beijing, China. https://doi.org/10.1109/GEOINFORMATICS.2010.5567823

Lee, J., Acharya, T., Lee, D. ( 2018). Exploring Land Cover Classification Accuracy of Landsat 8 Image using Spectral Indices Layer Stacking in Hilly Region of South Korea. Sensors and Materials, 30(12), 2927-2941. https://doi.org/2910.18494/SAM.12018.11934.

Leroux, L., Congedo, L., Bellón, B., Gaetano, R., Bégué, A. ( 2018). Land Cover Mapping Using Sentinel-2 Images and the Semi-Automatic Classification Plugin: A Northern Burkina Faso Case Study (pp. 131-165). https://doi.org/10.1002/9781119457107.ch4

Li, H., Wang, C., Zhong, C., Su, A., Xiong, C., Wang, J., Liu, J. ( 2017). Mapping Urban Bare Land Automatically from Landsat Imagery with a Simple Index. Remote Sensing, 9(3). https://doi.org/10.3390/rs9030249

Liu, Y., Chen, J., Cheng, W., Sun, C., Zhao, S., Yingxia, P. ( 2014). Spatiotemporal dynamics of the urban sprawl in a typical urban agglomeration: a case study on Southern Jiangsu, China (1983–2007).

Frontiers of Earth Science, 8, 490-504. https://doi.org/10.1007/s11707-014-0423-1

Loi, D., Chou, T.-Y., Fang, Y.-M. ( 2017). Integration of GIS and Remote Sensing for Evaluating Forest Canopy Density Index in Thai Nguyen Province, Vietnam. International Journal of Environmental Science and Development, 8, 539-542. https://doi.org/10.18178/ijesd.2017.8.8.1012

Louis, J., Debaecker, V., Pflug, B., Main-Knorn, M., Bieniarz, J., Müller-Wilm, U., . . . Gascon, F. ( 2016). SENTINEL-2 SEN2COR: L2A Processor for Users.

Lynch, P., Blesius, L. ( 2019). Urban Remote Sensing: Feature Extraction.

MacQueen, J. ( 1967). Some Methods for Classification and Analysis of Multivariate Observations. Paper presented at the In L. M. Le Cam & J. Neyman (eds.) Proceedings of the 5th Berkeley Symposium on Mathematical Statistics and Probability University of California Press, Berkeley, CA, USA.

Muna, E., Walker, S. ( 2010). Environmental Degradation of Natural Resources in Butana Area of Sudan. https://doi.org/10.1007/978-90-481-8657-0_13.

Nur Hidayati, I., Suharyadi, R., Danoedoro, P. ( 2018). Developing an Extraction Method of Urban Built-Up Area Based on Remote Sensing Imagery Transformation Index. Forum Geografi, 32. https://doi.org/10.23917/forgeo.v32i1.5907

Pal, M., Antil, K. ( 2017). Comparison of Landsat 8 and Sentinel 2 data for Accurate Mapping of Built-Up Area and Bare Soil. Paper presented at the The 38th Asian Conference on Remote Sensing, New Delhi, India.

Patel, N., Mukherjee, R. ( 2014). Extraction of impervious features from spectral indices using artificial neural network. Arabian Journal of Geosciences, 8. https://doi.org/10.1007/s12517-014-1492-x

Rasul, A., Balzter, H., Ibrahim, G. R. F., Hameed, H. M., Wheeler, J., Adamu, B., . . . Najmaddin, P. M. ( 2018). Applying Built-Up and Bare-Soil Indices from Landsat 8 to Cities in Dry Climates. Land, 7(3), 81. https://doi.org/10.3390/land7030081

Rikimaru, A., Miyatake, S. ( 1997). Development of Forest Canopy Density Mapping and Monitoring Model using Indices of Vegetation, Bare soil and Shadow. . Paper presented at the Proceeding of the 18th Asian Conference on Remote Sensing (ACRS) 1997, Kuala Lumpur, Malaysia.

Rikimaru, A., Roy, P., Miyatake, S. ( 2002). Tropical forest cover density mapping. Tropical ecology, 43(1), 39-47.

Rouse, J., Haas, R., Schell, J., Deering, D., Freden, S. ( 1973). Monitoring vegetation systems in the Great Plains with ERTS.(pp. 309–317). Paper presented at the Proceedings of 3rd Earth Resources Technology Satellite-1 Symposium. pp. 309-317

Sun, G., Chen, X., Jia, X., Yao, Y., Wang, Z. ( 2016). Combinational Build-Up Index (CBI) for Effective Impervious Surface Mapping in Urban Areas. IEEE Journal of selected topics in applied earth observations and remote sensing, 9(5), 2081-2092. https://doi.org/10.1109/JSTARS.2015.2478914

Tola, E., Al-Gaadi, K. A., Madugundu, R. ( 2019). Employment of GIS techniques to assess the long-term impact of tillage on the soil organic carbon of agricultural fields under hyper-arid conditions. PLOS ONE, 14, e0212521. https://doi.org/10.1371/journal.pone.0212521

Tucker, C. J. ( 1979). Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment, 8(2), 127-150. https://doi.org/10.1016/0034-4257(79)90013-0

Useya, J., Chen, S., Murefu, M. ( 2019). Cropland Mapping and Change Detection: Toward Zimbabwean Cropland Inventory. IEEE Access, 7, 53603-53620. https://doi.org/10.1109/ACCESS.2019.2912807

Valdiviezo-N, J., Téllez-Quiñones, A., Salazar-Garibay, A., López-Caloca, A. ( 2018). Built-up index methods and their applications for urban extraction from Sentinel 2A satellite data: discussion. Journal of the Optical Society of America A, 35, 35. https://doi.org/10.1364/JOSAA.35.000035

Vanhellemont, Q., Ruddick, K. (2016). Acolite for Sentinel-2: Aquatic applications of MSI imagery. Paper presented at the Proceedings of the 2016 ESA Living Planet Symposium, 09 - 13 May 2016,

Prague, Czech Republic. pp. 9-13.

Vapnik, V. N. ( 1995). The nature of statistical learning theory: Springer-Verlag. https://doi.org/10.1007/978-1-4757-2440-0

Vigneshwaran, S., Vasantha Kumar, S. ( 2018). EXTRACTION OF BUILT-UP AREA USING HIGH RESOLUTION SENTINEL-2A AND GOOGLE SATELLITE IMAGERY. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLII-4/W9, 165-169. https://doi.org/10.5194/isprs-archives-XLII-4-W9-165-2018

Waqar, M., Mirza, J., Mumtaz, R., Hussain, E. ( 2012). Development of New Indices for Extraction of Built-Up Area & Bare Soil from Landsat Data. Open Access Scientific Reports, 1(1), 01-04.

Xi, Y., Xuan Thinh, N., Li, C. ( 2019). Preliminary comparative assessment of various spectral indices for built-up land derived from Landsat-8 OLI and Sentinel-2A MSI imageries. European Journal of Remote Sensing, 52, 240-252. https://doi.org/10.1080/22797254.2019.1584737

Xian, G., Homer, C., Fry, J. ( 2009). Updating the 2001 National Land Cover Database land cover classification to 2006 by using Landsat imagery change detection methods. Remote Sensing of Environment, 113(6), 1133-1147. https://doi.org/10.1016/j.rse.2009.02.004

Xu, H. ( 2007). Extraction of Urban Built-up Land Features from Landsat Imagery Using a Thematicoriented Index Combination Technique. Photogrammetric Engineering & Remote Sensing, 73(12), 1381-1391. https://doi.org/10.14358/PERS.73.12.1381

Xu, H. ( 2008). A new index for delineating built-up land features in satellite imagery. International Journal of Remote Sensing, 29, 4269-4276. https://doi.org/10.1080/01431160802039957

Yilmaz, E., Varol, B., topaloğlu, R., Sertel, E. ( 2019). Object-Based Classification of Izmir Metropolitan City by Using Sentinel-2 Images. 2019 9th International Conference on Recent Advances in Space Technologies (RAST), 407-412. https://doi.org/10.1109/RAST.2019.8767781

Zha, Y., Gao, J., 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

Zuur, A. F., Ieno, E. N., Smith, G. M. ( 2007). Principal component analysis and redundancy analysis. Analysing ecological data, 193-224. https://doi.org/10.1007/978-0-387-45972-1

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