Abstract
Aiming at the remote sensing application has been increasingly relying on ground object spectral characteristics. In order to further research the spectral reflectance characteristics in arid area, this study was performed in the typical delta oasis of Weigan and Kuqa rivers located north of Tarim Basin. Data were collected from geo-targets at multiple sites in various field conditions. The spectra data were collected for different soil types including saline–alkaline soil, silt sandy soil, cotton field, and others; vegetations of Alhagi sparsifolia, Phragmites australis, Tamarix, Halostachys caspica, etc., and water bodies. Next, the data were processed to remove high-frequency noise, and the spectral curves were smoothed with the moving average method. The derivative spectrum was generated after eliminating environmental background noise so that to distinguish the original overlap spectra. After continuum removal of the undesirable absorbance, the spectrum curves were able to highlight features for both optical absorbance and reflectance. The spectrum information of each ground object is essential for fully utilizing the multispectrum data generated by remote sensing, which will need a representative spectral library. In this study using ENVI 4.5 software, a preliminary spectral library of surface features was constructed using the data surveyed in the study area. This library can support remote sensing activities such as feature investigation, vegetation classification, and environmental monitoring in the delta oasis region. Future plan will focus on sharing and standardizing the criteria of professional spectral library and to expand and promote the utilization of the spectral databases.














Similar content being viewed by others
Explore related subjects
Discover the latest articles and news from researchers in related subjects, suggested using machine learning.References
Aparicio, N., Villegas, D., Casadesus, J., Araus, J. L., & Royo, C. (2000). Spectral vegetation indices as non-destructive tools for determining durum wheat yield. Agronomy Journal, 92(1), 83–91.
Baldridge, A. M., Hook, S. J., Grove, C. I., & Rivera, G. (2009). The ASTER spectral library version 2.0. Remote Sensing of Environment, 113(4), 711–715.
Ben-Dor, E., & Banin, A. (1994). Visible and near infrared (0.4 1.1 μm) of arid and semi-arid soils. Remote Sensing of Environment, 48(3), 261–274.
Brown, D. J., Shepherd, K. D., Walsh, M. G., Dewayne Mays, M., & Reinsch, T. G. (2006). Global soil characterization with VNIR diffuse reflectance spectroscopy. Geoderma, 132(3–4), 273–290.
Cao, R. Y., Chen, Y. H., & Huang, W. J. (2008). Design and development of hyperspectral library for recognizing disease of crops. Journal of Natural Disasters, 17(6), 73–76.
Chen, J., Yang, W., Zhang, Y. M., & Wang, X. Q. (2008). Spectral characteristics of biological soil crusts in Gurbantonggut Desert, Xinjiang. Spectroscopy and Spectral Analysis, 28(1), 28–32.
Cloutis, E. A. (1996). Hyperspectral geological remote sensing: evaluation of analytical techniques. Journal of Remote Sensing, 17(12), 2215–2242.
Clark, R. N. (1999). Spectroscopy of rocks and minerals, and principles of spectroscopy. In A. N. Rencz (Ed.), Remote sensing for earth sciences (pp. 3–58). New York: Wiley.
Daniel, K. W., Tripathi, N. K., Honda, H., & Apisit, E. (2004). Analysis of VNIR (400∼1100 nm) spectral signatures for estimation of soil organic matter in tropical soils of Thailand. International Journal of Remote Sensing, 25(3), 643–652.
Hu, S. J., Song, Y. D., Tian, C. Y., Li, Y. T., Li, X. C., & Chen, X. B. (2006). Proper scale of Weigan River plain oasis. Science in China Series D: Earth Sciences, 36(z2), 51–57.
Lillesand, T. M., & Kiefer, R. W. (2000). Remote sensing and image interpretation. New York: Wiley.
Liu, C. S., Tiyip, T., & Ding, J. L. (2003). Landcover change of Yu Tian Oasis based on remote sensing and GIS. Journal of Desert Research, 23(1), 59–63.
Liu, W. D., Frédéric, B., Zhang, B., Zheng, L. F., & Tong, Q. X. (2004). Extraction of soil moisture information by hyperspectral remote sensing. Acta Pedologica Sinica, 41(5), 700–706.
Ramarao, N. (2008). Development of a crop-specific spectral library and discrimination of various agricultural crop varieties using hyperspectral imagery. International Journal of Remote Sensing, 29(1), 131–144.
Schmid, T., Koch, M., Gumuzzio, J., & Mather, P. M. (2004). A spectral library for a semi-arid wetland and its application to studies of wetland degradation using hyperspectral and multispectral data. International Journal of Remote Sensing, 25(13), 2485–2496.
Shrestha, D. P., Margate, D. E., Meer, F. V. D., & Anh, H. V. (2005). Analysis and classification of hyperspectral data for mapping land degradation: an application in southern Spain. International Journal of Applied Earth Observation and Geoinformation, 7(2), 85–96.
Tang, Y. L., Huang, J. F., Wang, X. Z., Wang, R. C., & Wang, F. M. (2004). Comparison of the characteristics of hyper spectra and the red edge in rice, corn and cotton. Scientia Agricultura Sinica, 37(1), 29–35.
Tian, Q. J., Gong, P., Zhao, C. J., & Guo, X. W. (2000). A feasibility study on diagnosing wheat water status using spectral reflectance. Chinese Science Bulletin, 45(24), 2645–2650.
Wang, J., & Xu, R. S. (2008). Spectral characteristics of main types of soil in western of Guangdong. Ecology and Environment, 5, 1931–1936.
Wan, Y. Q., Yan, Y. Z., & Zhang, F. L. (2001). A research on the hyperspectral indexes of dominant vegetation in YANHE drainage area. Remote Sensing for Land and Resources, 49(3), 15–20.
Xu, W. D., Yin, Q., & Kuang, D. B. (2005). Comparison of different spectral match models. Journal Infrared and Millimeter Waves, 24(4), 296–300.
Yuan, C. Q., Shen, T., Liu, C. S., & He, Q. (2003). Analysis on ground reflected spectrum and remote sensing data of Mengjin reservoir and vicinities. Journal of Desert Research, 23(5), 549–553.
Yue, Y. M., Wang, K. L., Zhang, B., Chen, Z. C., Jiao, Q. J., Liu, B., et al. (2010). Exploring the relationship between vegetation spectra and eco-geo-environmental conditions in Karst region, Southwest China. Environmental Monitoring and Assessment, 160, 157–168.
Zhou, P., Wang, R. S., Yan, B. K., Yang, S. M., & Wang, Q. H. (2008). Extraction of soil organic matter information by hyperspectral remote sensing. Progress in Geography, 27(5), 28–34.
Zomer, R. J., Trabucco, A., & Ustin, S. L. (2009). Building spectral libraries for wetlands land cover classification and hyperspectral remote sensing. Journal of Environmental Management, 90(7), 2170–2177.
Acknowledgments
This study was carried out with the financial assistance of the National Key Program for Developing Basic Research Science (grant no.2009CB421302), the Chinese National Natural Science Foundation (grant no. 40861020, no.40961025 and no.40901163), and the Open Foundation of State Key Laboratory of Resources and Environment Information Systems (grant no.2010KF0003SA).
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Zhang, F., Tiyip, T., Ding, J. et al. Spectral reflectance properties of major objects in desert oasis: a case study of the Weigan–Kuqa river delta oasis in Xinjiang, China. Environ Monit Assess 184, 5105–5119 (2012). https://doi.org/10.1007/s10661-011-2326-x
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10661-011-2326-x


