Snow Cover Detection Using Multi-Temporal Remotely Sensed Images of Fengyun-4A in Qinghai-Tibetan Plateau

作者：Guangyi Ma, Linglong Zhu, Yonghong Zhang, Kenny Thiam Choy Lim Kam Sian, Yixin Feng, Tianming Yu · 发表于：Water · 年份：2023 · DOI：10.3390/w15193329 · 被引用次数：1 · 研究领域：Cryospheric studies and observations、Urban Heat Island Mitigation

Differentiating between snow and clouds presents a formidable challenge in the context of mapping snow cover over the Qinghai–Tibetan Plateau (QTP). The frequent presence of cloudy conditions severely complicates the discrimination of snow cover from satellite imagery. To accurately monitor the spatiotemporal evolution of snow cover, it is imperative to address these challenges and enhance the segmentation schemes employed for snow cover assessment. In this study, we devised a pixel-wise classification algorithm based on Support Vector Machine (SVM) called the 3-D Orientation Gradient algorithm (3-D OG), which captures the variations of the gradient direction of snow and clouds in spatiotemporal dimensions based on geostationary satellite “Fengyun-4A” (FY-4A) multi-spectral and multi-temporal optical imagery. This algorithm assumes that the speed and direction of clouds and snow are different in the process of movement leading to their discrepancy of gradient characteristics in time and space. Therefore, in this algorithm, the gradient of the images in the spatiotemporal dimensions is calculated first, and then the movement angle and trend are obtained based on that. Finally, the feature space is composed of the multi-spectral image, gradient image, and movement feature maps, which are used as the input of the SVM. Our results demonstrate that the proposed algorithm can identify snow and clouds more accurately during snowfall by utilizing the FY-4A’s high temporal resolution ...