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Bare soil mapping is inevitable for the monitoring of soil resources, as it acts as a major indicator of urban development. Although remote sensing based indices are largely used for the delineation of bare soil, their effectiveness has always been a challenge due to overlapping spectral characteristics of the bare soil and built up areas. Recently, built up indices have been employed to increase the accuracy of bare soil mapping, which can induce discrepancies due to lesser sensitivity in smaller patches of bare soil areas in high density urban regions. In this context, modified normalized difference bare soil index (MNDBSI) is developed using a logical combination of index with additional constraint for the precise delineation of bare soil area using Sentinel 2 images. The qualitative and quantitative analyses adopted to evaluate the performance of the MNDBSI revealed an overall agreement value of above 95% and the improvement percentage of MNDBSI over the other indices compared in terms of spectral discrimination index and transformed divergence varied from 8% to 166% and 15% to 97%, respectively, across all study areas. The comparative analyses of results indicate that MNDBSI is an effective alternative to the existing indices for precise bare soil mapping which can be used as a promising indicator of urban expansion.
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167--180
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Bibliogr. 34 poz., rys., tab.
Twórcy
autor
- National Centre for Earth Science Studies, Akkulam, Thiruvananthapuram, India
autor
- National Centre for Earth Science Studies, Akkulam, Thiruvananthapuram, India
- Indian Institute of Technology Madras, Chennai, India
- M/S Vassar Labs Pvt Ltd, Hyderabad, India
autor
- National Centre for Earth Science Studies, Akkulam, Thiruvananthapuram, India
autor
- National Centre for Earth Science Studies, Akkulam, Thiruvananthapuram, India
Bibliografia
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- 3. Deng, Y.B., Wu, C.S., Li, M., Chen, R.R. 2015. RNDSI: A ratio normalized difference soil index for remote sensing of urban/suburban environments. Int J Appl Earth Obs. 39, 40–48.
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- 16. Liu, Y., Meng, Q., Zhang, L., Wu, C. 2022. NDBSI: A normalized difference bare soil index for remote sensing to improve bare soil mapping accuracy in urban and rural areas, Catena. 214, 106265.
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- 21. Piyoosh, A.K., Ghosh, S.K. 2018. Development of a modified bare soil and urban index for Landsat 8 satellite data. Geocarto Int. 33, 423–442.
- 22. Rasul, A., Balzter, H., Ibrahim, G.R.F., Hameed, H.M., Wheeler, J., Adamu, B., Ibrahim, S., Najmaddin, P.M. 2018. Applying built-up and bare-soil indices from Landsat 8 to cities in dry climates. Land. 7, 81.
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- 25. Salas, E.A.L., Kumaran, S.S. 2023. Hyperspectral Bare Soil Index (HBSI): Mapping soil using an ensemble of spectral indices in machine learning environment. Land. 12, 1375.
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- 28. Tolpekin, V., Stein, A. 2009. Quantication of the effects of land-cover-class spectral separability on the accuracy of markov-random-eld-based super resolution mapping. IEEE Trans. Geosci. Remote Sens. 47, 3283–3297.
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- 30. Wang, Y., Li, M. 2019. Urban impervious surface detection from remote sensing images: A review of the methods and challenges. IEEE Geoscience and Remote Sensing Magazine. 7 (3), 64–93.
- 31. Wentzel, K. 2002. Determination of the overall soil erosion potential in the Nsikazi District (Mpumalanga Province, South Africa) using remote sensing and GIS. Can. J. Remote Sens. 28, 322–327.
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- 33. Zhao, H., Chen, X. 2005. Use of normalized difference bareness index in quickly mapping bare areas from TM/ETM+. Int. Geosci. Remote Sens. Symp. 3, 1666–1668.
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Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-842ddc8f-184c-4507-96d9-11b4095a4093
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