ABSTRACT

Spatiotemporal fusion technique can combine the advantages of temporal resolution and spatial resolution of different images to achieve continuous monitoring for the Earth’s surface, which is a feasible solution to resolve the trade-off between the temporal and spatial resolutions of remote sensing images. In this paper, an object-based spatiotemporal fusion model (OBSTFM) is proposed to produce spatiotemporally consistent data, especially in areas experiencing non-shape changes (including phenology changes and land cover changes without shape changes). Considering different changes that might occur in different regions, multi-resolution segmentation is first employed to produce segmented objects, and then a linear injection model is introduced to produce preliminary prediction. In addition, a new optimized strategy to select similar pixels is developed to obtain a more accurate prediction. The performance of proposed OBSTFM is validated using two remotely sensed dataset experiencing phenology changes in the heterogeneous area and land cover type changes, experimental results show that the proposed method is advantageous in such areas with non-shape changes, and has satisfactory robustness and reliability in blending large-scale abrupt land cover changes. Consequently, OBSTFM has great potential for monitoring highly dynamic landscapes.

摘要

时空融合技术可以结合不同图像的时间分辨率和空间分辨率的优势，实现对地球表面的连续监测，这是解决遥感图像时间分辨率和空间分辨率之间权衡问题的可行解决方案。本文提出了一种基于对象的时空融合模型（OBSTFM），以产生时空一致的数据，尤其是在经历非形状变化的区域（包括物候变化和没有形状变化的土地覆盖变化）时。考虑到可能在不同区域发生的不同变化，首先采用多分辨率分割来生成分割的对象，然后引入线性注入模型以生成初步预测。此外，开发了一种新的优化策略来选择相似像素，以获得更准确的预测。OBSTFM的性能得到了两个异质区域物候变化和土地覆盖类型变化的遥感数据集的验证，实验结果表明，该方法在非形状变化的区域具有优势，具有令人满意的鲁棒性和可靠性。混合大规模突然的土地覆盖变化。因此，OBSTFM在监视高度动态的景观方面具有巨大的潜力。实验结果表明，该方法在非形状变化区域具有优势，在混合大面积突变土地覆盖方面具有令人满意的鲁棒性和可靠性。因此，OBSTFM在监视高度动态的景观方面具有巨大的潜力。实验结果表明，该方法在不发生形状变化的区域具有优势，在混合大面积突然土地覆盖变化方面具有令人满意的鲁棒性和可靠性。因此，OBSTFM在监视高度动态的景观方面具有巨大的潜力。