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UrduA pioneering study (DOI: 10.34133/remotesensing.0403) from Tsinghua University’s Department of Earth System Science, recently published in Journal of Remote Sensing, delves into this very challenge. The research dissects publication trends and utilizes the Remote Sensing Impact Factor (RSIF) to uncover a surge in EO data applications. Key satellites—Landsat, MODIS, and Sentinel—stand out for their pivotal roles in driving climate action (SDG 13) and conserving biodiversity (SDG 15).
The findings reveal an impressive surge in EO satellite data usage over the past three years. Sentinel and Gaofen satellites have seen remarkable growth in demand, with Sentinel surpassing MODIS in recent years. Meanwhile, Landsat and MODIS continue to be cornerstones for environmental monitoring and historical data analysis. Big data cloud platforms like Google Earth Engine have further accelerated data processing and analysis, spotlighting the growing significance of open data policies and cross-platform collaboration.
Analyzing articles from 2020 to 2023, the study reports a leap in EO satellite-related publications—from 45,673 to 59,703. Open-source datasets, particularly Landsat and MODIS, dominate the research landscape. Sentinel data has seen a dramatic rise, with related publications soaring from 2,702 in 2020 to 7,231 in 2023—an unmistakable sign of its expanding scientific relevance. Notably, China has overtaken the United States to become the global leader in EO satellite data research output.
To ensure comprehensive insights, the research team meticulously curated literature on widely used EO satellites and sensors from the Web of Science Core Collection. By refining their search criteria, they bolstered the accuracy and depth of their analysis. Advanced bibliometric tools like CiteSpace and VOSviewer enabled the team to map emerging trends and key developments from 2020 to 2023. The RSIF metric was recalibrated to incorporate the latest data, providing a more accurate measure of research impact.
Experts involved in the study emphasize that EO satellite data is indispensable for achieving the SDGs. Beyond supporting individual goals, these datasets create powerful synergies—Sentinel satellites aid both marine ecosystem health and climate resilience, while Landsat data enhances food security and water resource management.
Looking ahead, satellites like Sentinel, Landsat, MODIS, Gaofen, and ALOS are poised to remain vital in the EO data landscape over the next five years. As technological innovations and new satellite launches unfold, the value of EO data will only intensify, offering richer, more reliable insights for global environmental monitoring and sustainable development. Furthermore, advances in artificial intelligence, machine learning, and collaborative frameworks are set to unlock even broader applications of EO data, propelling humanity closer to the 2030 sustainability targets.
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References
DOI
Original Source URL
https://doi.org/10.34133/remotesensing.0403
Funding information
This work was supported by the National Key R&D Program of China (2022YFE0195900) and the Investigation Research Program between Ecological Environment and Human Health in Wuyi Mountain (20242120035).
About Journal of Remote Sensing
The Journal of Remote Sensing, an online-only Open Access journal published in association with AIR-CAS, promotes the theory, science, and technology of remote sensing, as well as interdisciplinary research within earth and information science.
