Harmoni-Planet: A holistic harmonization method for PlanetScope constellation imagery leveraging a graph-based greedy optimization strategy

IF 11.4 1区 地球科学 Q1 ENVIRONMENTAL SCIENCES
Ruilin Chen , Wei Yang , Xuehong Chen , Zhuoning Gu , Benfeng Yin , Yuanming Zhang , Jin Chen
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引用次数: 0

Abstract

The PlanetScope CubeSat constellation provides unprecedentedly high spatiotemporal resolution for Earth observations but is limited by radiometric inconsistencies resulting from sensor degradation and spectral configuration differences. Existing harmonization methods often rely on internal or external references, limiting harmonization to only a subset of spectral bands or restricting applicability to localized spatiotemporal scales. To address these limitations, we propose Harmoni-Planet, a novel harmonization method that leverages graph-based greedy optimization to achieve holistic radiometric consistency across all PlanetScope bands without requiring reference data. The method consists of two components: (1) graph construction, which integrates unharmonized images into a graph with nodes representing images and edges connecting intersecting images, and (2) graph optimization, which iteratively minimizes radiometric inconsistencies between each image and its intersecting images to optimize consistency. Harmoni-Planet was validated across four geographically diverse regions (the Nile, Beijing, Indonesia, and Greenland), achieving substantial mean absolute error (MAE) reductions of 53 %, 53 %, 57 %, and 25 %, respectively, and outperforming the CubeSat-enabled spatiotemporal enhancement method (CESTEM; 40 %, 41 %, 47 %, and − 69 %, respectively) and the official harmonization algorithm (25 %, 33 %, −9 %, and 9 %, respectively). Harmoni-Planet significantly improves the spatial and temporal comparability of imagery across all PlanetScope bands, regardless of whether images are acquired by the same or different generations of satellites. In addition, it supports flexible scene-based and strip-based implementations, effectively resolving both intra-strip and cross-strip inconsistencies. It also demonstrates robust potential for near-real-time harmonization of newly acquired imagery to accommodate the rapidly expanding data volume of the PlanetScope constellation. Furthermore, Harmoni-Planet supports seamless integration with standard third-party reflectance products such as Landsat-8 and Sentinel-2. Harmoni-Planet provides a practical solution to address cross-sensor radiometric inconsistencies, substantially improving the quality and reliability of PlanetScope data for diverse Earth observation applications.
Harmoni-Planet:利用基于图的贪婪优化策略对PlanetScope星座图像进行整体协调的方法
PlanetScope CubeSat星座为地球观测提供了前所未有的高时空分辨率,但由于传感器退化和光谱配置差异导致的辐射不一致性受到限制。现有的协调方法通常依赖于内部或外部参考,将协调限制在光谱波段的子集或限制在局部时空尺度上的适用性。为了解决这些限制,我们提出了Harmoni-Planet,这是一种新的协调方法,利用基于图的贪婪优化来实现所有PlanetScope波段的整体辐射一致性,而不需要参考数据。该方法由两个部分组成:(1)图构建,将未协调的图像整合成一个图,节点代表图像,边缘连接相交图像;(2)图优化,迭代最小化每幅图像与其相交图像之间的辐射不一致性,以优化一致性。Harmoni-Planet在四个地理不同的区域(尼罗河、北京、印度尼西亚和格陵兰岛)进行了验证,分别实现了53%、53%、57%和25%的显著平均绝对误差(MAE)降低,优于cubesat支持的时空增强方法(CESTEM;分别为40%、41%、47%和- 69%)和官方协调算法(分别为25%、33%、- 9%和9%)。Harmoni-Planet显著提高了所有PlanetScope波段图像的时空可比性,无论图像是由同一代还是不同代的卫星获得的。此外,它还支持灵活的基于场景和基于条带的实现,有效地解决了条带内和跨条带的不一致性。它还展示了对新获得的图像进行近实时协调的强大潜力,以适应PlanetScope星座快速扩展的数据量。此外,Harmoni-Planet支持与标准的第三方反射产品(如Landsat-8和Sentinel-2)无缝集成。Harmoni-Planet为解决跨传感器辐射测量不一致性提供了一个实用的解决方案,大大提高了PlanetScope数据的质量和可靠性,适用于各种地球观测应用。
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来源期刊
Remote Sensing of Environment
Remote Sensing of Environment 环境科学-成像科学与照相技术
CiteScore
25.10
自引率
8.90%
发文量
455
审稿时长
53 days
期刊介绍: Remote Sensing of Environment (RSE) serves the Earth observation community by disseminating results on the theory, science, applications, and technology that contribute to advancing the field of remote sensing. With a thoroughly interdisciplinary approach, RSE encompasses terrestrial, oceanic, and atmospheric sensing. The journal emphasizes biophysical and quantitative approaches to remote sensing at local to global scales, covering a diverse range of applications and techniques. RSE serves as a vital platform for the exchange of knowledge and advancements in the dynamic field of remote sensing.
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