An Overview of the Applications of Earth Observation Satellite Data: Impacts and Future Trends

Abstract

As satellite observation technology develops and the number of Earth observation (EO) satellites increases, satellite observations have become essential to developments in the understanding of the Earth and its environment. However, the current impacts to the remote sensing community of different EO satellite data and possible future trends of EO satellite data applications have not been systematically examined. In this paper, we review the impacts of and future trends in the use of EO satellite data based on an analysis of data from 15 EO satellites whose data are widely used. Articles that reference EO satellite missions included in the Web of Science core collection for 2020 were analyzed using scientometric analysis and meta-analysis. We found the following: (1) the number of publications and citations referencing EO satellites is increasing exponentially; however, the number of articles referencing AVHRR, SPOT, and TerraSAR is tending to decrease; (2) papers related to EO satellites are concentrated in a small number of journals: 43.79% of the articles that were reviewed were published in only 13 journals; and (3) remote sensing impact factor (RSIF), a new impact index, was constructed to measure the impacts of EO satellites and to predict future trends in applications of their data. Landsat, Sentinel, MODIS, Gaofen, and WorldView were found to be the most significant current EO satellite missions and MODIS data to have the widest range of applications. Over the next five years (2021–2025), it is expected that Sentinel will become the satellite mission with the greatest influence.

The role of remote sensing during a global disaster: COVID-19 pandemic as case study

“…This table is not exhaustive, as we focus on passive remote sensing techniques, and give reference primarily to the satellites and sensors introduced in this article. For a more complete discussion on remote sensing techniques and applications, see ( Kuenzer et al, 2014 ; Zhao et al, 2022 ).…”

The use of remote sensing indices to understand flood‐recharged soil moisture impacts on trees in semi‐arid floodplains: A review

“…The ML algorithms can efficiently handle big and high dimensional spatial data to parsimoniously model complex patterns with much higher accuracy than traditional methods (Maxwell et al, 2018). For example, Zhao et al (2022) noted that RF is a popular ML classification scheme widely used for RS image processing. Stojanova et al (2010) determined height and canopy size of individual trees using ML with LiDAR data applying 3D extraction.…”

“…The developments in Earth Observation (EO) technologies aim to improve instrumentation specifications to achieve higher data quality (Zhao et al, 2022). Typical examples include the ESA space roadmap (Atzei et al, 1996), the Germany hyperspectral Environmental Mapping and Analysis Program (EnMAP) (Foerster et al, 2016; Guanter et al, 2015) and NASA's Landsat 9 missions (Zhao et al, 2022).…”

“…The developments in Earth Observation (EO) technologies aim to improve instrumentation specifications to achieve higher data quality (Zhao et al, 2022). Typical examples include the ESA space roadmap (Atzei et al, 1996), the Germany hyperspectral Environmental Mapping and Analysis Program (EnMAP) (Foerster et al, 2016; Guanter et al, 2015) and NASA's Landsat 9 missions (Zhao et al, 2022). Accordingly, as of October 2020, the Committee on EO Satellites recorded 327 satellite missions, 845 instruments either operational or to be launched in less than 2 decades from only 30 affiliate national space agencies (Zhao et al, 2022).…”

“…However, it is important to note that broadband multispectral RSIs can inform what target materials are; e.g., the NDVI distinguishes vegetation from non‐vegetation landcover, while the recently developed hyperspectral RSIs can discriminate more on the physiological characteristics such as plant light use efficiency, photosynthetic and stomatal behaviour (Coops et al, 2010; Dorigo et al, 2007; Marino, 2014). The application of SAR based indices is also emerging especially with Sentinel‐1 SAR open data policy (Zhao et al, 2022).…”