Open Access
Issue |
E3S Web Conf.
Volume 477, 2024
International Conference on Smart Technologies and Applied Research (STAR'2023)
|
|
---|---|---|
Article Number | 00017 | |
Number of page(s) | 9 | |
DOI | https://doi.org/10.1051/e3sconf/202447700017 | |
Published online | 16 January 2024 |
- Uryu, “Entwicklung eines multifunktionalen Energieversorgungssystems und Validierung anhand optimierter Testprozeduren für den Kleinsatelliten Flying Laptop,” Universität Stuttgart, 2012. [Google Scholar]
- W. Kleynhans, J. C. Olivier, K. J. Wessels, F. van den Bergh, B. P. Salmon, and K. C. Steenkamp, “Improving Land Cover Class Separation Using an Extended Kalman Filter on MODIS NDVI Time-Series Data,” IEEE Geoscience and Remote Sensing Letters , vol. 7, no. 2, pp. 381–385, 2010. [CrossRef] [Google Scholar]
- W. Zhu, Y. Pan, H. He, L. Wang, M. Mou, and J. Liu, “A changing-weight filter method for reconstructing a high-quality NDVI time series to preserve the integrity of vegetation phenology,” IEEE Transactions on Geoscience and Remote Sensing , vol. 50, no. 4, pp. 1085–1094, 2012. [CrossRef] [Google Scholar]
- S. G. Santos, J. C. Melo, R. G. Constantino, and A. v. Brito, “A Solution for Vegetation Analysis, Separation and Geolocation of Management Zones using Aerial Images by UAVs,” in Brazilian Symposium on Computing System Engineering, SBESC, Nov. 2019, vol. 2019. [Google Scholar]
- P. Bo, S. Fenzhen, and M. Yunshan, “A Cloud and Cloud Shadow Detection Method Based on Fuzzy c-Means Algorithm,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , vol. 13, pp. 1714–1727, 2020. [CrossRef] [Google Scholar]
- X. Kang, G. Gao, Q. Hao, and S. Li, “A coarse-to-fine method for cloud detection in remote sensing images,” IEEE Geoscience and Remote Sensing Letters , vol. 16, no. 1, pp. 110–114, 2019. [CrossRef] [Google Scholar]
- Z. Zhu and C. E. Woodcock, “Object-based cloud and cloud shadow detection in Landsat imagery,” 118:83–94.(2012). [Google Scholar]
- L. Kang, Y. Shao, B. Zhang, L. Di, E. Yu, and R. Shrestha, “Study of the NDVI-precipitation correlation stratified by crop type and soil permeability,” in 2013 Second International Conference on Agro-Geoinformatics (Agro-Geoinformatics), Aug. 2013, pp. 194–199. [Google Scholar]
- Y. Guo, L. Li, L. Jin, and K. Wang, “Study on cloud processing methods with MODIS data,” 2013 5th IEEE International Symposium on Microwave, Antenna, Propagation and EMC Technologies for Wireless Communications, MAPE 2013, pp. 694–696, 2013. [Google Scholar]
- Chen, T., Zhang, X. P., Wang, J., Li, J., Wu, C., Hu, M., & Bian, H. (2020). A review on electric vehicle charging infrastructure development in the UK. Journal of Modern Power Systems and Clean Energy, 8(2), 193-205. [CrossRef] [Google Scholar]
- Shibl, M., Ismail, L., & Massoud, A. (2021). Electric vehicles charging management using machine learning considering fast charging and vehicle-to-grid operation. Energies, 14(19), 6199. [CrossRef] [Google Scholar]
- N. Shekhawat, A. P. Dadhich, and R. Goyal, “Temporal Analysis of Land Surface Temperature and Land Use / Land Cover using Remote Sensing,” Journal of Civil Engineering and Environmental Technology , vol. 5, no. 2, pp. 71–77, 2018. [Google Scholar]
- X. Song, Z. Liu, and Y. Zhao, “Cloud detection and analysis of MODIS image,” International Geoscience and Remote Sensing Symposium (IGARSS) , vol. 4, no. c, pp. 2764–2767, 2004. [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.