A novel spectral index to automatically extract road networks from WorldView-2 satellite imagery

Egyptian Journal of Remote Sensing and Space Science

Volumn 18, Issue 1, 2015, Pages 27-33

  Shahi, Kaveh ^a   Shafri, Helmi Z M ^a   Taherzadeh, Ebrahim ^a   Mansor, Shattri ^a   Muniandy, Ratnasamy ^a  

^a UNIVERSITY PUTRA MALAYSIA   (Malaysia)

Author keywords

Asphalt road extraction; Band selection; Remote sensing; Spectral index; Spectroradiometer; WorldView 2

Indexed keywords

ASPHALT; DISCRIMINANT ANALYSIS; EXTRACTION; FEATURE EXTRACTION; RADIOMETERS; REMOTE SENSING; ROADS AND STREETS; SPECTROMETERS;

ASPHALT ROADS; BAND SELECTION; SPECTRAL INDICES; SPECTRO-RADIOMETERS; WORLDVIEW-2;

SATELLITE IMAGERY;

ASPHALT; DISCRIMINANT ANALYSIS; IMAGE CLASSIFICATION; REMOTE SENSING; ROAD; SATELLITE IMAGERY; SPECTRAL RESOLUTION; WORLDVIEW;

EID: 84943361518     PISSN: 11109823     EISSN: 20902476     Source Type: Journal    
DOI: 10.1016/j.ejrs.2014.12.003     Document Type: Article

References (36)

1. Andreou, C., Karathanassi, V., Kolokoussis, P., 2011. Investigation of hyperspectral remote sensing for mapping asphalt road conditions. Int. J. Remote Sens. 32 (21), 6315-6333.
2. Bacher, U., Mayer, H., 2005. Automatic road extraction from multispectral high resolution satellite images. In: Proc. CMRT05.
3. Bhatta, B., 2009. Analysis of urban growth pattern using remote sensing and GIS: a case study of Kolkata, India. Int. J. Remote Sens. 30, 4733-4746.
4. Chaudhuri, D., Kushwaha, N.K., Samal, A., 2012. Semi-automated road detection from high resolution satellite images by directional morphological enhancement and segmentation techniques. IEEE. J. Sel. Top. Appl. 5 (5), 1538-1544.
5. Clark, M.L., Roberts, D.A., Clark, D.B., 2005. Hyperspectral discrimination of tropical rain forest tree species at leaf to crown scales. Remote Sens. Environ. 96 (3), 375-398.
6. Cablk, M.E., Minor, T.B., 2003. Detecting and discriminating impervious cover with high-resolution IKONOS data using principal component analysis and morphological operators. Int. J. Remote Sens. 24 (23), 4627-4645.
7. Debba, P., Cho, M., Mathieu, R., 2009. Optimal individual supervised hyperspectral band selection distinguishing savannah trees at leaf level. In: IEEE WHISPERS'09. First Workshop. p. 1-4.
8. Digital Globe, 2009. White Paper: the benefits of the 8 spectral bands of World View-2. Longmont, CO, Digital Globe.
9. Das, S., Mirnalinee, T.T., 2011. Use of salient features for the design of a multistage framework to extract roads from high-resolution multispectral satellite images. IEEE Trans. Geosci. Remote Sens. 49 (10), 3906-3931.
10. Fung, T., Yan Ma, H.F., Siu, W.L., 2003. Band selection using hyperspectral data of subtropical tree species. Geocarto Int. 18 (4), 3-11.
11. Griffiths, P., Hostert, P., Gruebner, O., Van Der Linden, S., 2010. Mapping megacity growth with multi-sensor data. Remote Sens. Environ. 114, 426-439.
12. He, C., Shi, P., Xie, D., Zhao, Y., 2010. Improving the normalized difference built-up index to map urban built-up areas using a semiautomatic segmentation approach. Remote Sens. Lett. 1 (4), 213-221.
13. Herold, M., Roberts, D.A., Gardner, M.E., Dennison, P.E., 2004. Spectrometry for urban area remote sensing - development and analysis of a spectral library from 350 to 2400 nm. Remote Sens. Environ. 91 (3), 304-319.
14. Herold, M., Roberts, D., 2005. Spectral characteristics of asphalt road aging and deterioration: implications for remote-sensing applications. Appl. Opt. 44 (20), 4327-4334.
15. Hu, J., Razdan, A., Femiani, J.C., Cui, M., Wonka, P., 2007. Road network extraction and intersection detection from aerial images by tracking road footprints. IEEE Trans. Geosci. Remote Sens. 45 (12), 4144-4157.
16. Kavzoglu, T., Sen, Y.E., Cetin, M., 2009. Mapping urban road infrastructure using remotely sensed images. Int. J. Remote Sens. 30 (7), 1759-1769.
17. Kirthika, A., Mookambiga, A., 2011. Automated road network extraction using artificial neural network. In: Recent Trends in Information Technology (ICRTIT), IEEE Int. Con. p. 1061-1065.
18. Karaman, E., Cinar, U., Gedik, E., Yardemci, Y., Halici, U., 2012. A new algorithm for automatic road network extraction in multispectral satellite images. In: Proc 4th GEOBIA, p. 455-4598.
19. Lu, D., Weng, Q., 2009. Extraction of urban impervious surfaces from an IKONOS image. Int. J. Remote Sens. 30 (5), 1297-1311.
20. Morrison, D.G., 2011. Discriminant analysis and predictive classification, Marketing Classics Press.
21. Masek, J.G., Lindsay, F.E., Goward, S.N., 2000. Dynamics of urban growth in the Washington DC metropolitan area, 1973-1996, from Landsat observations. Int. J. Remote Sens. 21, 3473-3486.
22. Mohammadi, M. 2011. Road Classification and Condition Determination using Hyperspectral Imagery (Unpublished Master thesis). University of Appl. Sci. Stuttgart, Germany.
23. Mhangara, P., Odindi, J., Kleyn, L., Remas, H., 2011. Road extraction using object oriented classification. (Last accessed 01/04/2014).
24. Pu, R., Landry, S., Yu, Q., 2011. Object-based urban detailed land cover classification with high spatial resolution IKONOS imagery. Int. J. Remote Sens. 32 (12), 3285-3308.
25. Rajeswari, M., Gurumurthy, K.S., Prathap Reddy, L., Omkar, S.N., 2011. Automatic road extraction based on level set, normalized cuts and mean shift methods. Int. J. Comput. Sci. 8 (2), 250-257.
26. Resende, M., Jorge, S., Longhitano, G., Quintanilha, J.A., 2008. Use of hyperspectral and high spatial resolution image data in an asphalted urban road extraction. IEEE Int. Geosci. Remote Sens. IGARSS 2008 (3), 1323-1325.
27. Taherzadeh, E., Shafri, H.Z.M., 2011. Using hyperspectral remote sensing data in urban mapping over Kuala Lumpur. JURSE Proc. IEEE, 405-408.
28. Tupin, F., Houshmand, B., Datcu, M., 2002. Road detection in dense urban areas using SAR imagery and the usefulness of multiple views. IEEE Trans. Geosci. Remote Sens. 40, 2405-2414.
29. Varshney, A., 2013. Improved NDBI differencing algorithm for builtup regions change detection from remote sensing data: an automated approach. Remote Sens. Lett. 4 (5), 504-512.
30. Valero, S., Chanussot, J., Benediktsson, J.A., Talbot, H., Waske, B., 2010. Advanced directional mathematical morphology for the detection of the road network in very high resolution remote sensing images. Pattern Recognit. Lett. 31 (10), 1120-1127.
31. Wu, C., 2009. Quantifying high-resolution impervious surfaces using spectral mixture analysis. Int. J. Remote Sens. 30 (11), 2915-2932.
32. Xu, H., 2008. A new index for delineating built-up land features in satellite imagery. Int. J. Remote Sens. 29, 4269-4276.
33. Xinpeng, T., Shunlin, S., Yongzhao, Z., 2014. A novel road extraction algorithm for high resolution remote sensing images. Appl. Math 8 (3), 1435-1443.
34. Zarrinpanjeh, N., Samadzadegan, F., Schenk, T., 2013. A new ant based distributed framework for urban road map updating from high resolution satellite imagery. Comput. Geosci. 54, 337-350.
35. Zha, Y., Gao, J., Ni, S., 2003. Use of normalized difference built-up index in automatically mapping urban areas from TM imagery. Int. J. Remote Sens. 24 (3), 583-594.
36. Zha, Y., Ni, S.X., Yang, S., 2001. An effective approach to automatically extract urban land-use from TM imagery. J. Rem. Sens. Beijing 7 (1), 37-40.