Towards a Unified Identifier of Satellite Remote Sensing Images

The rapid growth of Earth observation technologies has resulted in over 2000 operational remote sensing satellites, collectively generating an exabyte-scale volume of data. However, despite the availability of large data-sharing platforms, global remote sensing imagery still faces challenges in seam...

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Main Authors: Jiahe Wang, Jin Wu, Mingbo Wu, Yuxiang Lu, Shangwen Lu, Dayong Zhu, Chenghu Zhou
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/17/3/465
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author Jiahe Wang
Jin Wu
Mingbo Wu
Yuxiang Lu
Shangwen Lu
Dayong Zhu
Chenghu Zhou
author_facet Jiahe Wang
Jin Wu
Mingbo Wu
Yuxiang Lu
Shangwen Lu
Dayong Zhu
Chenghu Zhou
author_sort Jiahe Wang
collection DOAJ
description The rapid growth of Earth observation technologies has resulted in over 2000 operational remote sensing satellites, collectively generating an exabyte-scale volume of data. However, despite the availability of large data-sharing platforms, global remote sensing imagery still faces challenges in seamless access, precise querying, and efficient retrieval. To address these limitations, this study introduces the concept of the “Digital Imagery Object” (DIO) and develops a unified identification framework for satellite remote sensing imagery. The proposed approach establishes a structured identification and parsing system based on core metadata, including data acquisition platforms and imaging timestamps. This enhances the consistency and standardization of multisource imagery encoding, enabling unified identification and interpretation under a common set of rules. The system’s feasibility and effectiveness were demonstrated through the integration and management of diverse global datasets, highlighting its ability to streamline multisource data workflows. By supporting standardized management and one-click parsing, this framework facilitates efficient imagery sharing and lays the foundation for its use as a tradable digital resource on the internet. The study offers a practical solution for addressing current challenges in remote sensing imagery management, paving the way for improved accessibility and interoperability of Earth observation data.
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spelling doaj-art-dd520663c7264c0caba360c99a886df32025-08-20T02:12:29ZengMDPI AGRemote Sensing2072-42922025-01-0117346510.3390/rs17030465Towards a Unified Identifier of Satellite Remote Sensing ImagesJiahe Wang0Jin Wu1Mingbo Wu2Yuxiang Lu3Shangwen Lu4Dayong Zhu5Chenghu Zhou6State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaState Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaState Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaDigitwinology International (Kunshan) Information Technology Co., Ltd., Suzhou 215300, ChinaDigitwinology International (Kunshan) Information Technology Co., Ltd., Suzhou 215300, ChinaDigitwinology International (Kunshan) Information Technology Co., Ltd., Suzhou 215300, ChinaState Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaThe rapid growth of Earth observation technologies has resulted in over 2000 operational remote sensing satellites, collectively generating an exabyte-scale volume of data. However, despite the availability of large data-sharing platforms, global remote sensing imagery still faces challenges in seamless access, precise querying, and efficient retrieval. To address these limitations, this study introduces the concept of the “Digital Imagery Object” (DIO) and develops a unified identification framework for satellite remote sensing imagery. The proposed approach establishes a structured identification and parsing system based on core metadata, including data acquisition platforms and imaging timestamps. This enhances the consistency and standardization of multisource imagery encoding, enabling unified identification and interpretation under a common set of rules. The system’s feasibility and effectiveness were demonstrated through the integration and management of diverse global datasets, highlighting its ability to streamline multisource data workflows. By supporting standardized management and one-click parsing, this framework facilitates efficient imagery sharing and lays the foundation for its use as a tradable digital resource on the internet. The study offers a practical solution for addressing current challenges in remote sensing imagery management, paving the way for improved accessibility and interoperability of Earth observation data.https://www.mdpi.com/2072-4292/17/3/465remote sensing imageryunified identifiergeographic information systemobject-oriented
spellingShingle Jiahe Wang
Jin Wu
Mingbo Wu
Yuxiang Lu
Shangwen Lu
Dayong Zhu
Chenghu Zhou
Towards a Unified Identifier of Satellite Remote Sensing Images
Remote Sensing
remote sensing imagery
unified identifier
geographic information system
object-oriented
title Towards a Unified Identifier of Satellite Remote Sensing Images
title_full Towards a Unified Identifier of Satellite Remote Sensing Images
title_fullStr Towards a Unified Identifier of Satellite Remote Sensing Images
title_full_unstemmed Towards a Unified Identifier of Satellite Remote Sensing Images
title_short Towards a Unified Identifier of Satellite Remote Sensing Images
title_sort towards a unified identifier of satellite remote sensing images
topic remote sensing imagery
unified identifier
geographic information system
object-oriented
url https://www.mdpi.com/2072-4292/17/3/465
work_keys_str_mv AT jiahewang towardsaunifiedidentifierofsatelliteremotesensingimages
AT jinwu towardsaunifiedidentifierofsatelliteremotesensingimages
AT mingbowu towardsaunifiedidentifierofsatelliteremotesensingimages
AT yuxianglu towardsaunifiedidentifierofsatelliteremotesensingimages
AT shangwenlu towardsaunifiedidentifierofsatelliteremotesensingimages
AT dayongzhu towardsaunifiedidentifierofsatelliteremotesensingimages
AT chenghuzhou towardsaunifiedidentifierofsatelliteremotesensingimages