دورية أكاديمية
HISTIF: A New Spatiotemporal Image Fusion Method for High-Resolution Monitoring of Crops at the Subfield Level
| العنوان: | HISTIF: A New Spatiotemporal Image Fusion Method for High-Resolution Monitoring of Crops at the Subfield Level |
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| المؤلفون: | Jiale Jiang, Qiaofeng Zhang, Xia Yao, Yongchao Tian, Yan Zhu, Weixing Cao, Tao Cheng |
| المصدر: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 13, Pp 4607-4626 (2020) |
| بيانات النشر: | IEEE, 2020. |
| سنة النشر: | 2020 |
| المجموعة: | LCC:Ocean engineering LCC:Geophysics. Cosmic physics |
| مصطلحات موضوعية: | Crops, heterogeneity, image fusion, spatiotemporal fusion, subfield monitoring, Ocean engineering, TC1501-1800, Geophysics. Cosmic physics, QC801-809 |
| الوصف: | Satellite-based time-series crop monitoring at the subfield level is essential to the efficient implementation of precision crop management. Existing spatiotemporal image fusion techniques can be helpful, but they were often proposed to generate medium-resolution images. This study proposed a high-resolution spatiotemporal image fusion method (HISTIF) consisting of filtering for cross-scale spatial matching (FCSM) and multiplicative modulation of temporal change (MMTC). In FCSM, we considered both point spread function effect and geo-registration errors between fine and coarse resolution images. Subsequently, MMTC used pixel-based multiplicative factors to estimate the temporal change between reference and prediction dates without image classification. The performance of HISTIF was evaluated using both simulated and real datasets with one from real Gaofen-1 (GF-1) and simulated Landsat-like/Sentinel-like images, and the other from real GF-1 and real Landsat/Sentinel-2 data on two sites. HISTIF was compared with the existing methods spatial and temporal adaptive reflectance fusion model (STARFM), FSDAF, and Fit-FC. The results demonstrated that HISTIF produced substantial reduction in the fusion error from cross-scale spatial mismatch and accurate reconstruction in spatial details within fields, regardless of simulated or real data. The images predicted by STARFM exhibited pronounced blocky artifacts. While the images predicted by HISTIF and Fit-FC both showed clear within-field variability patterns, HISTIF was able to reduce the spectral distortion more significantly than Fit-FC. Furthermore, HISTIF exhibited the most stable performance across sensors. The findings suggest that HISTIF could be beneficial for the frequent and detailed monitoring of crop growth at the subfield level. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 2151-1535 |
| Relation: | https://ieeexplore.ieee.org/document/9165877/; https://doaj.org/toc/2151-1535 |
| DOI: | 10.1109/JSTARS.2020.3016135 |
| URL الوصول: | https://doaj.org/article/00a7ee053bdf46aa9bffe849bf775f4b |
| رقم الأكسشن: | edsdoj.00a7ee053bdf46aa9bffe849bf775f4b |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 21511535 |
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| DOI: | 10.1109/JSTARS.2020.3016135 |