Internet-Based Spectral Database for Different Land Covers in Egypt

DOI: 10.4236/ars.2013.22012   PDF   HTML   XML   3,842 Downloads   6,683 Views   Citations


The spectral signatures of natural objects in the visible and near-infrared spectral range are influenced by the object’s physical and biochemical properties. These signatures can be compiled in a database and used to retrieve information of land cover types and their physical composition from actual hyperspectral observations. This paper describes development process of hyperstectral database of reflectance from different land cover types in Egypt. It has been compiled from data obtained using a ground-based spectroradiometer system that covers the spectral range from 350 to 2500 nm at 1 nm resolution. The database is accessible through a website, where the system includes also metadata that describes the site environment and measurement processes. The system provides flexible mechanisms and friendly interfaces to allow accessing the database by the non-specialized people, whereas spectral data can be sorted by sites, species or selected environmental parameters. The system presents sample results from different vegetation and soil covers. Development of such a database is essential for different remote sensing applications, satellite’s calibrations, data dissemination and linkage with other databases for scientific researches purposes.

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S. Arafat, E. Farg, M. Shokr and G. Al-Kzaz, "Internet-Based Spectral Database for Different Land Covers in Egypt," Advances in Remote Sensing, Vol. 2 No. 2, 2013, pp. 85-92. doi: 10.4236/ars.2013.22012.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] N. E. M. Nasarudin and H. Z. M. Shafri, “Development and Utilization of Urban Spectral Library for Remote Sensing of Urban Environment,” Journal of Urban and Environmental Engineering, Vol. 5, No. 1, 2011, pp. 44-56.
[2] L. Zhang, C. Huang, T. Wu, F. Zhang and Q. Tong, “Laboratory Calibration of a Field Imaging Spectrometer System,” Sensors, Vol. 11, No. 3, 2011, pp. 2408-2425. doi:10.3390/s110302408
[3] A. A. Darvishsefat, M. Abbasi and M. E. Schaepman, “Evaluation of Spectral Reflectance of Seven Iranian Rice Varieties Canopies,” Journal of Agricultural Science and Technology, Vol. 13, 2011, pp. 1091-1104.
[4] E. Adam, O. Mutanga and D. Rugege, “Multispectral and Hyperspectral Remote Sensing for Identification and Mapping of Wetland Vegetation: A Review,” Wetlands Ecology and Management, Vol. 18, No. 3, 2010, pp. 281-296. doi:10.1007/s11273-009-9169-z
[5] E. M. Abdel-Rahman and F. B. Ahmed, “The Application of Remote Sensing Techniques to Sugarcane (Saccharum spp. Hybrid) Production: A Review of the Literature,” International Journal of Remote Sensing, Vol. 29, No. 13, 2008, pp. 3753-3767. doi:10.1080/01431160701874603
[6] A. I. de Castro, M. Jurado-Exposito, M. Gomez-Casero, and F. Lopez-Granados, “Applying Neural Networks to Hyperspectral and Multispectral Field Data for Discrimination of Cruciferous Weeds in Winter Crops,” The Scientific World Journal, Vol. 2012, 2012, pp. 1-11. doi:10.1100/2012/630390
[7] S. S. Ray, J. P. Singh and S. Panigrahy, “Use of Hyperspectral Remote Sensing Data for Crop Stress Detection: Ground-Based Studies,” International Archives of the Photogrammetry, Remote Sensing and Spatial Information Science, Vol. 38, No. 8, 2010, pp. 562-567.
[8] C. P. Ferri, A. R. Formaggio and M. A. Schiavinato, “Narrow Band Spectral Indexes for Chlorophyll Determination in Soybean Canopies [Glycine Max (L.) Merril],” Brazilian Journal of Plant Physiology, Vol. 16, No. 3, 2004, pp. 131-136.
[9] Y. Cheng, E. Tom and S. L. Ustin, “Mapping an Invasive Species, Kudzu (Puerariamontana), Using Hyperspectral Imagery in Western Georgia,” Journal of Applied Remote Sensing, SPIE, Vol. 1, No. 1, 2007, Article ID: 013514. doi:10.1117/1.2749266
[10] S. Stagakis, V. Gonzalez-Dugo, P. Cid, M. L. GuillenCliment and P. J. Zarco-Tejada, “Monitoring Water Stress and Fruit Quality in an Orange Orchard under Regulated Deficit Irrigation Using Narrow-Band Structural and Physiological Remote Sensing,” Journal of Photogrammetry and Remote Sensing, Vol. 71, 2012, pp. 47-61. doi:10.1016/j.isprsjprs.2012.05.003
[11] T. H. Kurz, S. J. Buckley and J. A. Howell, “Close Range Hyperspectral Imaging Integrated with Terrestrial LIDAR Scanning Applied to Rock Characterization at Centimeter Scale,” International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. 39, No. 5, 2012, pp. 417-422.
[12] A. Hueni and M. Tuohy, “Spectroradiometer Data Structuring,” Pre-Processing and Analysis—An IT Based Approach, Spatial Science, Vol. 52, No. 2, 2006, pp. 93-102. doi:10.1080/14498 596.2006.9635084
[13] A. Hueni, J. Nieke, J. Schopfer, M. Kneubuhler and K. I. Itten, “The Spectral Database Specchio for Improved LongTerm Usability and Data Sharing,” Computers & Geosciences, Vol. 35, No. 3, 2009, pp. 557-565. doi:10.1016/j.cageo.2008.03.015
[14] S. Bojinski, M. Schaepman, D. Schlapfer and K. Itten, “SPECCHIO: A Spectrum Database for Remote Sensing Applications,” Computers & Geosciences, Vol. 29, No. 1, 2003, pp. 27-38. doi:10.1016/S009 8-3004(02)00107-3
[15] K. Pfitzner, A. Bollhofer and G. Carr, “A Standard Design for Collecting Vegetation Reference Spectra: Implementation and Implications for Data Sharing,” Spatial Science, Vol. 52, No. 2, 2006, pp. 79-92. doi:10.1080/14498596.2006.9635083
[16] A. Di Gregorio, “Land Cover Classification System (LCCS), Version 2: Classification Concepts and User Manual,” Food and Agriculture Organization of the United Nations, Rome, 2005.
[17] M. Abbasi, A. A. Darvishsefat, M. E. Schaepman and M. Abbasi, “E-Learning Support for Hyperspectral Remote Sensing Lectures with Emphasis on Spectral Library Database,” International Society for Photogrammetry and Remote Sensing (ISPRS), Vol. 38, No. 6, 2011, pp. 129-131.

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