RT info:eu-repo/semantics/article
T1 Assessment of Spatiotemporal Fusion Algorithms for Planet and Worldview Images
A1 Kwan, Chiman
A1 Zhu, Xiaolin
A1 Gao, Feng
A1 Chou, Bryan
A1 Perez, Daniel
A1 Li, Jiang
A1 Shen, Yuzhong
A1 Koperski, Krzysztof
A1 Marchisio, Giovanni
A1 Islam, Kazi
A1 Hill, Victoria
A1 Zimmerman, Richard
A1 Schaeffer, Blake
A2 Ingenieria de Sistemas y Automatica
K1 Aeronáutica
K1 Image fusion
K1 Planet
K1 Worldview
K1 Pansharpening
K1 Forward prediction
K1 Spatiotemporal
K1 3324 Tecnología del Espacio
AB [EN] Although Worldview-2 (WV) images (non-pansharpened) have 2-m resolution, the re-visit times for the same areas may be seven days or more. In contrast, Planet images are collected using small satellites that can cover the whole Earth almost daily. However, the resolution of Planet images is 3.125 m. It would be ideal to fuse these two satellites images to generate high spatial resolution (2 m) and high temporal resolution (1 or 2 days) images for applications such as damage assessment, border monitoring, etc. that require quick decisions. In this paper, we evaluate three approaches to fusing Worldview (WV) and Planet images. These approaches are known as Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM), Flexible Spatiotemporal Data Fusion (FSDAF), and Hybrid Color Mapping (HCM), which have been applied to the fusion of MODIS and Landsat images in recent years. Experimental results using actual Planet and Worldview images demonstrated that the three aforementioned approaches have comparable performance and can all generate high quality prediction images.
PB MDPI
LK https://hdl.handle.net/10612/21564
UL https://hdl.handle.net/10612/21564
NO Kwan, C., Zhu, X., Gao, F., Chou, B., Pérez, D., Li, J., Shen, Y., Koperski, K., & Marchisio, G. (2018). Assessment of spatiotemporal fusion algorithms for planet and worldview images. Sensors (Switzerland), 18(4). https://doi.org/10.3390/S18041051
DS BULERIA. Repositorio Institucional de la Universidad de León
RD Jul 5, 2024