Possibility for Identifying/Extracting Rock Outcrop Using Landsat 8 OLI/TIRS - Case Study of Thua Thien Hue Province
Main Article Content
Abstract
This paper approaches the ratio image method to extract the exposed rock information from the Landsat 8 OLI/TIRS satellite image (2019) according to the object orientation classification. Combining automatic interpretation and interpretation through threshold of image index values according to interpretation key the object orientation classification to separate soil object containing exposed rock and no exposed rock in Thua Thien Hue province. Using the Topsoil Grain Size Index (TGSI), the Normalized Difference Vegetation Index (NDVI), the Normalized Difference Built-up Index (NDBI) and other related analytical problems have identified 40 exposed rock storage areas in the study area. The results have been verified in the field and the Kappa index is 85.10%.
Keywords:
exposed rock, Soil map, TGSI, NDVI, NDBI.
References
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[2] B. Gurugnanam, K. Kalaivanan, S. Bairavi, Application of remote sensing and gis for soil mapping of kolli hill, South india, International Journal of Current Advanced Research, 3(12) (2014) 52-54. http://www.journalijcar. org/issues/ application-remote-sensing-and-gis-soil-mapping-kolli-hill-south-india (accessed 10 April 2020).
[3] Y.M. Yue, K.L. Wang , B. Liu, R. Li, B. Zhang, H.S. Chen & M.Y. Zhang, Development of new remote sensing methods for mapping green vegetation and exposed bedrock fractions within heterogeneous landscapes, International Journal of Remote Sensing, Volume 34, Issue 14 (2012) 5136-5153. https://doi.org/10.1080/01431161. 2013.787500.
[4] Y. Xu, S.E. Smith, S. Grunwald, A. Abd-Elrahman and S.P. Wani, Incorporation of satellite remote sensing pan-sharpened imagery into digital soil prediction and mapping models to characterize soil property variability in small agricultural fields. ISPRS Journal of Photogrammetry and Remote Sensing, (123) (2017) 1-19. http://dx. doi. org/10.1016/j.isprsjprs.2016.11.00.
[5] A. Djenaliev, O. Hellwich, Extraction of built-up areas from Landsat imagery using the object-oriented classification method, 9th International Symposium on Applied Informatics and Related Areas, Székesfehérvár, Hungary (2014) 156-161. https://www.academia.edu/11011541/Extraction_of_built_up_areas_from_Landsat_imagery_using_the_object_oriented_classification_method (accessed 15 June 2020).
[6] A.E. Hartemink, A. Mcbratney, M.L. Mendonca-Santos, Digital Soil Mapping with Limited Data, Springer Netherlands, 2008, https://link.springer. com/book/10.1007/978-1-4020-8592-5.
[7] C.J. Tucker, C.L. Vanpraet, M.J. Sharman, G. Van Ittersum, Satellite remote sensing of total herbaceous biomass production in the Senegalese Sahel: 1980–1984. Remote Sensing of Environment Jounal 17(3)(1985) 233-249. https:// doi.org/10.1016/0034-4257(85)90097-5.
[8] X. Qi, C. Zhang and K. Wang, Comparing Remote Sensing Methods for Monitoring Karst Rocky Desertification at Sub-pixel Scales in a Highly Heterogeneous Karst Region, Nature Research Journals, Vol. 9, 13368 (2019), https://doi.org/10. 1038/s41598-019-49730-9.
[9] S.L. Suryawanshi, M.D. Abuj, S.H. Bhutada V.S. Bhandare, Generation of soil map using remote sensing and geographic information system for Malegaon watershed in Maharastra, International Journal of Agricultural Engineering, Vol. 1 No. 2 (2008) 38-40. http://www.researchjournal.co.in/ online/IJAE/IJAE%201(2)/1_A-38-40.pdf. (accessed 17 March 2020).
[10] S.L. Suryawanshi, M.D. Abuj, S.H. Bhutada and V.S. Bhandare, Generation of land use/land cover using remote sensing and geographic information system for Malegaon watershed in Maharastra, International Journal of Agricultural Engineering, Vol. 1 No. 2 (2008) 81 - 84. http://www.research journal.co.in/online/IJAE/IJAE%201(2)/1_A-81-84.pdf. (accessed 17 March 2020).
[11] A.A. Elnaggar, J.S. Noller, Application of Remote-sensing Data and Decision-Tree Analysis to Mapping Salt-Affected Soils over Large Areas, Journal of Remote Sensing, Vol 2(1), (2010) 151-165, https://doi.org/10.3390/rs2010151.
[12] R. Setia, V.Verma, P. Sharma, Soil Informatics for Evaluating and Mapping Soil Productivity Index in an Intensively Cultivated Area of Punjab, India, Journal of Geographic Information System, Vol 4, No.1, (2012) 71-76. http://dx.doi.org/ 10.4236/ jgis.2012.41010.
[13] Z. Ahmed, J. Iqbal, Evaluation of Landsat TM5 Multispectral Data for Automated Mapping of Surface Soil Texture and Organic Matter in GIS, European Journal of Remote Sensing, Vol 47, Issue 1 (2014) 557-573. https://doi.org/10.5721/ EuJRS201447.
[14] A.R. Huete, A soil-adjusted vegetation index (SAVI), Remote Sensing of Environment, Vol. 25, Issue 3 (1988), 295-309. https://doi.org/10. 1016/0034-4257(88)90106-X.
[15] Thua Thien Hue Provincial People's Committee, Socio-economic situation of Thua Thien Hue province 2019, Report No. 368/BC-UBND 31 December 2019, Hue (2019). (In Vietnamese).
[16] M. Chen, W. Su, L. Li, C. Zhang, A. Yue, H. Li, A Comparison of Pixel-based and Object-oriented Knowledge-based Classification Methods Using SPOT5 Imagery, Proceedings of the 13th WSEAS International Conference on applied mathematics (Math'08) 6(3) (2008) 321-326. https://www. researchgate.net/ publication/ 228636844_A_ comparison _of_ pixel-based_and_objectorient ed_classification_using_SPOT5_imagery (accessed 17 March 2020).
[17] H. Bartholomeus, G. Epema, M. Schaepman, Determining iron content in Mediterranean soils in partly vegetated areas, using spectral reflectance and imaging spectroscopy. International Journal of Applied Earth Observation and Geoinformation 9 (2)(2007) 194-203. https://doi. org/10.1016/j.jag.2006.09.001.
[18] H.D. Duan, S. Mamoru, Studies on Hanoi Urban transition in the Late 20th century based on GIS/RS, Southeast Asian Studies, Vol. 46, No. 4, (2009), 496-518. http://repository.kulib.kyoto-u.ac.jp/dspace/handle/2433/88034. (accessed 17 March 2020).
[19] K. Tamta, H.S. Bhadauria, A.S. Bhadauria, Object-Oriented Approach of Information Extraction from High Resolution Satellite Imagery, IOSR Journal of Computer Engineering (IOSR-JCE), 17(3) (2015) 47-52. http://doi.org/ 10.6084/m9.figshare.1444273.v1.
[20] L.T.M. Phuong, D.T.B. Hoa, P.Q. Tuan, Classification of the ground cover in 2012 in the Hanoi area by classifying the object orientation from the satellite image Spot, Proceedings of GIS 2015 conference, Xay dung publisher, Hanoi Vietnam (2015) 443-448. (In Vietnamese).
[21] H. Wei, J. Wang, K. Cheng, G. Li, A. Ochir, D. Davaasuren, S. Chonokhuu, Desertification Information Extraction Based on Feature Space Combinations on the Mongolian Plateau, Journal of Remote Sensing (MDPI), 10(10) (2018) https:// doi.org/10.3390/rs10101614.
[22] J. Xiao, Y. Shen, R. Tateishi &W. Bayaer, Development of topsoil grain size index for monitoring desertification in arid land using remote sensing, International Journal of Remote Sensing 27(12) (2006) 2411-2422. https://doi. org/10.1080/01431160600554363.
[23] J. Cohen, A Coefficient of Agreement for Nominal Scales, Educational and Psychological Measurement, 20(1)(1960) 37-46. https://doi.org/ 10.1177/001316446002000104.