Ruilin Chen , Wei Yang , Xuehong Chen , Zhuoning Gu , Benfeng Yin , Yuanming Zhang , Jin Chen
{"title":"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","authors":"Ruilin Chen , Wei Yang , Xuehong Chen , Zhuoning Gu , Benfeng Yin , Yuanming Zhang , Jin Chen","doi":"10.1016/j.rse.2025.114986","DOIUrl":null,"url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"330 ","pages":"Article 114986"},"PeriodicalIF":11.4000,"publicationDate":"2025-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Harmoni-Planet: A holistic harmonization method for PlanetScope constellation imagery leveraging a graph-based greedy optimization strategy\",\"authors\":\"Ruilin Chen , Wei Yang , Xuehong Chen , Zhuoning Gu , Benfeng Yin , Yuanming Zhang , Jin Chen\",\"doi\":\"10.1016/j.rse.2025.114986\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>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.</div></div>\",\"PeriodicalId\":417,\"journal\":{\"name\":\"Remote Sensing of Environment\",\"volume\":\"330 \",\"pages\":\"Article 114986\"},\"PeriodicalIF\":11.4000,\"publicationDate\":\"2025-08-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Remote Sensing of Environment\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0034425725003906\",\"RegionNum\":1,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Remote Sensing of Environment","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0034425725003906","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Harmoni-Planet: A holistic harmonization method for PlanetScope constellation imagery leveraging a graph-based greedy optimization strategy
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.
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.