Open Access
Issue |
E3S Web Conf.
Volume 626, 2025
International Conference on Energy, Infrastructure and Environmental Research (EIER 2025)
|
|
---|---|---|
Article Number | 01005 | |
Number of page(s) | 7 | |
Section | GIS and Remote Sensing in Environmental Research | |
DOI | https://doi.org/10.1051/e3sconf/202562601005 | |
Published online | 15 April 2025 |
- Otukei, J. R., Blaschke, T., & Collins, M., Fusion of TerraSAR-x and Landsat ETM+ data for protected area mapping in Uganda, Int. J. Appl. Earth Obs. Geoinf., 38 (2015) [Google Scholar]
- Vidal-Macua, J.J., Ninyerola, M., Zabala, A., Domingo-Marimon, C., Pons, X., Factor affecting forest dynamics in the Iberian Peninsula from 1987 to 2012. The role of topography and drought, For. Ecol. Manag., 406 (2017) [Google Scholar]
- Zhu, Z., Wulder, M.A., Roy, D.P., Woodcock, C.E., Hansen, M.C., Radeloff, V.C., Healey, S.P., et al., Benefits of the free and open Landsat data policy, Remote Sens. Environ., 224 (2019) [Google Scholar]
- Walessa, M., Datcu, M. Model-based despeckling and information extraction from SAR images, IEEE Trans. Geosci. Remote Sens., 5 (2000) [Google Scholar]
- Lee, J.-S., Pottier, E, Polarimetric Radar Imaging: From Basics to Applications. CRC Press. Trisasongko, T., Urban area mapping using dual-polarized SAR data, Int. J. Remote Sens., 31 (2010) [Google Scholar]
- Jia, X., Wang, X. L., Urban land use mapping using SAR and optical data fusion, IEEE Geosci. Remote Sens. Lett., 15 (2018) [Google Scholar]
- Ghahremani, M., Ghassemian, H., A compressed-sensing-based pan-sharpening method for spectral distortion reduction, IEEE Trans. Geosci. Remote Sens., 54 (2016) [Google Scholar]
- Kulkarni, S. C., Rege, P., Pixel level fusion techniques for SAR and optical images: A review, Inf. Fusion, 59 (2020) [Google Scholar]
- Guo, Q., Ehlers, M., Wang, Q., Pohl, C., Hornberg, S., Li, A,. Ehlers pan-sharpening performance enhancement using HCS transform for n-band data sets, Int. J. Remote Sens., 38 (2017) [Google Scholar]
- Laben, C. A., & Brower, B. V., U.S. Patent No. 6,011,875. Washington, DC: U.S. Patent and Trademark Office, Alexandria, United States, 2000 [Google Scholar]
- Gonzalez-Audicana, M., Saleta, J. L., Catalan, R. G., Garcia, R., Fusion of multispectral and panchromatic images using improved IHS and PCA mergers based on wavelet decomposition, IEEE Trans. Geosci. Remote Sens., 42 (2004) [Google Scholar]
- Ming et al., Synergistic use of Sentinel-1 and Sentinel-2 for wetland classification, Remote Sens. Environ., 231 (2019) [Google Scholar]
- Small, D., Flattening Gamma: Radiometric Terrain Correction for SAR Imagery, IEEE Trans. Geosci. Remote Sens., 49 (2011) [Google Scholar]
- Martinis, S., Kersten, J., Twele, A., A fully automated TerraSAR-X based flood service, ISPRS J. Photogramm. Remote Sens., 104 (2015) [Google Scholar]
- Balzter, H., Luckman, A., Skinner, L., Groom, G., Bunting, P., & Dawson, T., Detection of tree cover changes using SAR polarimetric decomposition ratios, Remote Sens. Environ., 169 (2015) [Google Scholar]
- Pérez, F., et al., Normalization and Feature Extraction Methods for Land Cover Classification using SAR and Optical Data, Remote Sens., 10 (2018) [Google Scholar]
- Maurer, T., How to pan-sharpen images using the gram-schmidt pan-sharpen method-A recipe. ISPRS Int. Arch. Photogramm., 2013 [Google Scholar]
- Altangerel, Munkh-Erdene, Amarsaikhan, D. Jargaldalai, Enhktuya, Batdorj, Byambadolgor, Urban land use change study in Ulaanbaatar city using RS and GIS. Journal of Institute of Mathematics and Digital Technology, 5 (2023) [Google Scholar]
- Pohl, C., van Genderen, J.L, Multisensor Image Fusion in Remote Sensing: Concepts, Methods and Applications. Int. J. Remote Sens., 19 (1998) [Google Scholar]
- Wang, Q., Atkinson, P. M., Spatio-temporal fusion for daily sentinel-2 images. Remote Sens. Environ., 204 (2018) [Google Scholar]
- Ghahremani, M., Ghassemian, H., A compressed-sensing-based pan-sharpening method for spectral distortion reduction. IEEE Trans. Geosci. Remote Sens., 54 (2016) [Google Scholar]
- Z. Wang, A.C. Bovik, H.R. Sheikh, E.P., Simoncelli, Image quality assessment:From error visibility to structural similarity, IEEE Trans. Image Process., 13 (2004) [Google Scholar]
- Dee, D. P., et al., The ERA-Interim reanalysis: Configuration and performance of the data assimilation system, Q. J. R. Meteorol. Soc., 137 (2011) [Google Scholar]
- Phạm & Nguyễn, Random forest in machine learning and remote sensing applications. J. Surv. Map. Sci., 39 (2019) [Google Scholar]
- Breiman, L., Random Forests, Machine Learning, 45 (2001) [Google Scholar]
- Fawcett, T., An Introduction to ROC Analysis. Pattern Recognition Letters, 27 (2006) [Google Scholar]
- Hanley, J. McNEil, B., The Meaning and Use of the Area under a Receiver Operating Characteristic (ROC) Curve. Radiology, 143 (1982) [Google Scholar]
- L.M. Hằng, T.V. Anh, Fusion of Sentinel-1 SAR and optical remote sensing imagery. VNU J. Sci.: Earth Environ. Sci., 32 (2016) [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.