Earth Science Annotated Bibliography
Ge, Yong, et al. “Principles and methods of scaling geospatial Earth science data.” Earth-Science Reviews (2019): 102897.
The article is written by Ge Yong affiliated to theInstitute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences in Beijing. It discusses how various geographical phenomena change with variations in the measurement scale. The article is well written and divided into various sections for ease of understanding. The paper provides a review of different geospatial scaling methods used in earth science data.
Flechtner, Frank, et al. “What can be expected from the GRACE-FO laser ranging interferometer for Earth science applications?.” Remote Sensing and Water Resources. Springer, Cham, 2016. 263-280.
The article is written by frank Flechtner affiliated to the department of geodesy and remote sensing, GFZ german research center for geosciences, and it focuses on the objectives of the GRACE-FO satellite mission. Its main aim is to determine the effectiveness of laser ranging interferometer (LRI) in enhancing the measurement performance of satellite to satellite tracking. It is done to improve applications of earth science. The article is well organized for ease of understanding.. Don't use plagiarised sources.Get your custom essay just from $11/page
Guo, Huadong, Lizhe Wang, and Dong Liang. “Big Earth Data from space: a new engine for Earth science.” Science Bulletin 61.7 (2016): 505-513.
The paper is written by Huadong Guo, Wang Lizhe, and Dong Liang, affiliated to the institute of remote sensing and digital earth, Chinese academy of sciences. It evaluates the use of earth observation, also known as Big Earth Data, and how it creates new openings for the revolutionization of thought patterns and methodologies for earth sciences. It focuses on how big earth data can be used to encourage scientific discoveries.
Thessen, Anne. “Adoption of machine learning techniques in ecology and earth science.” One Ecosystem 1 (2016): e8621.
The article is written by Anne Thessen, affiliated to the ronin institute for independent scholarship. It talks about how machine learning can be used to enhance earth sciences and ecology and to improve the quality and pace of understanding science. Machine learning will enable the full realization of earth science. The paper is divided into various sections for simplicity.
Baumann, Peter, et al. “Fostering cross-disciplinary earth science through datacube analytics.” Earth Observation Open Science and Innovation. Springer, Cham, 2018. 91-119.
Peter Bauman writes the article, and it is about the changes occurring in the landscape of geospatial information markets. It discusses how the rapid growth of information and communication technology has made it easy for data-intensive research to be done by transparency, data availability, access to large volumes of complex data, high levels of computing power, and research collaboration. Its objective is to show how cloud computing has changed the way data is accessed and exploited. The article has headings and subheadings for ease of understanding.
Works Cited
Baumann, Peter, et al. “Fostering cross-disciplinary earth science through datacube analytics.” Earth Observation Open Science and Innovation. Springer, Cham, 2018. 91-119.
Flechtner, Frank, et al. “What can be expected from the GRACE-FO laser ranging interferometer for Earth science applications?.” Remote Sensing and Water Resources. Springer, Cham, 2016. 263-280.
Ge, Yong, et al. “Principles and methods of scaling geospatial Earth science data.” Earth-Science Reviews (2019): 102897.
Guo, Huadong, Lizhe Wang, and Dong Liang. “Big Earth Data from space: a new engine for Earth science.” Science Bulletin 61.7 (2016): 505-513.
Thessen, Anne. “Adoption of machine learning techniques in ecology and earth science.” One Ecosystem 1 (2016): e8621.