Open Access
Issue |
BIO Web Conf.
Volume 100, 2024
International Scientific Forum “Modern Trends in Sustainable Development of Biological Sciences” (IFBioScFU 2024)
|
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Article Number | 02035 | |
Number of page(s) | 7 | |
Section | Current Issues in Biotechnology, Microbiology, and Bioengineering | |
DOI | https://doi.org/10.1051/bioconf/202410002035 | |
Published online | 08 April 2024 |
- Chen, J., Yuan Zhang, M., Wang, L., Shimazaki, H., & Tamura, M. A new index for mapping lichen-dominated biological soil crusts in desert areas. Remote Sensing of Environment, 96 (2), 165–175. (2005). https://doi.org/10.1016/j.rse.2005.02.011 [CrossRef] [Google Scholar]
- Belnap, J., Büdel, B., & Lange, O. L. Biological Soil Crusts: Characteristics and Distribution. In J. Belnap & O. L. Lange (Eds.), Biological Soil Crusts: Structure, Function, and Management (pp. 3–30). Springer. (2003). https://doi.org/10.1007/978-3-642-56475-8_1 [Google Scholar]
- Sun, H., Ma, X., Liu, Y., Zhou, G., Ding, J., Lu, L., Wang, T., Yang, Q., Shu, Q., & Zhang, F. A New Multiangle Method for Estimating Fractional Biocrust Coverage From Sentinel-2 Data in Arid Areas. IEEE Transactions on Geoscience and Remote Sensing, 62, 1–15. (2024). https://doi.otg/10.1109/TGRS.2024.3361249 [Google Scholar]
- Wessels, D. C. J. & V. V. D. R. J. (1986). Landsat imagery—Its possible use in mapping the distribution of major Lichen Communities in the Namib Desert, South West Africa. Madoqua, (4), 369-373. 1986 https://doi.org/10.10520/AJA10115498_474 [Google Scholar]
- Ager, C. M., & Milton, N. M. Spectral reflectance of lichens and their effects on the reflectance of rock substrates. GEOPHYSICS, 52 (7), 898–906. (1987). https://doi.org/10.1190Z1.1442360 [CrossRef] [Google Scholar]
- Karnieli, A., & Sarafis, V. Reflectance spectrophotometry of cyanobacteria within soil crusts—A diagnostic tool. International Journal of Remote Sensing, 17 (8), 1609–1615. (1996) https://doi.org/10.1080/01431169608948726 [CrossRef] [Google Scholar]
- Weber, B., Olehowski, C., Knerr, T., Hill, J., Deutschewitz, K., Wessels, D. C. J., Eitel, B., & Büdel, B. A new approach for mapping of Biological Soil Crusts in semidesert areas with hyperspectral imagery. Remote Sensing of Environment, 112 (5), 2187–2201. (2008). https://doi.org/10.1016/j.rse.2007.09.014 [CrossRef] [Google Scholar]
- O’Neill, A. L. Reflectance spectra of microphytic soil crusts in semi-arid Australia. International Journal of Remote Sensing, 15 (3), 675–681. (1994). https://doi.org/10.1080/01431169408954106 [CrossRef] [Google Scholar]
- Wang, Z., Wu, B., Zhang, M., Zeng, H., Yang, L., Tian, F., Ma, Z., & Wu, H. Indices enhance biological soil crust mapping in sandy and desert lands. Remote Sensing of Environment, 278, 113078. (2022). https://doi.org/10.1016/j.rse.2022.113078 [CrossRef] [Google Scholar]
- Martinson, W. S., & Barton, P. I. A Differentiation Index for Partial Differential-Algebraic Equations. SIAM Journal on Scientific Computing, 21 (6), 2295–2315. (2000). https://doi.org/10.1137/S1064827598332229 [CrossRef] [Google Scholar]
- Román, J. R., Rodríguez-Caballero, E., Rodríguez-Lozano, B., Roncero-Ramos, B., Chamizo, S., Águila-Carricondo, P., & Cantón, Y. Spectral Response Analysis: An Indirect and Non-Destructive Methodology for the Chlorophyll Quantification of Biocrusts. Remote Sensing, 11(11), Article 11. (2019). https://doi.org/10.3390/rs11111350 [CrossRef] [Google Scholar]
- Sosa-Quintero, J., Godínez-Alvarez, H., Camargo-Ricalde, S. L., Gutiérrez-Gutiérrez, M., Huber-Sannwald, E., Jiménez-Aguilar, A., Maya-Delgado, Y., Mendoza-Aguilar, D., Montaño, N. M., Pando-Moreno, M., & Rivera-Aguilar, V. Biocrusts in Mexican deserts and semideserts: A review of their species composition, ecology, and ecosystem function. Journal of Arid Environments, 199, 104712. (2022). https://doi.org/10.1016/j.jaridenv.2022.104712 [CrossRef] [Google Scholar]
- Zhang, Y. M., Chen, J., Wang, L., Wang, X. Q., & Gu, Z. H. The spatial distribution patterns of biological soil crusts in the Gurbantunggut Desert, Northern Xinjiang, China. Journal of Arid Environments, 68 (4), 599–610. (2007). https://doi.org/10.1016/jjaridenv.2006.06.012 [CrossRef] [Google Scholar]
- Crucil, G., & Van Oost, K. (2021). Towards Mapping of Soil Crust Using Multispectral Imaging. Sensors, 21(5), Article 5. https://doi.org/10.3390/s210518501. [CrossRef] [PubMed] [Google Scholar]
- Navin, M. S., & Agilandeeswari, L. Multispectral and hyperspectral images based land use / land cover change prediction analysis: An extensive review. Multimedia Tools and Applications, 79 (39), 29751–29774. (2020). https://doi.org/10.1007/s11042-020-09531-z [CrossRef] [Google Scholar]
- Vali, A., Comai, S., & Matteucci, M. Deep Learning for Land Use and Land Cover Classification Based on Hyperspectral and Multispectral Earth Observation Data: A Review. Remote Sensing, 12(15), Article 15. (2020). https://doi.org/10.3390/rs12152495 [CrossRef] [Google Scholar]
- Lehnert, L. W., Jung, P., Obermeier, W. A., Büdel, B., & Bendix, J. Estimating Net Photosynthesis of Biological Soil Crusts in the Atacama Using Hyperspectral Remote Sensing. Remote Sensing, 10(6), Article 6. (2018). https://doi.org/10.3390/rs10060891 [CrossRef] [Google Scholar]
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