Earth Science Informatics

Aims & Scope

The Earth Science Informatics [ESIN] journal aims at rapid publication of high-quality, current, cutting-edge, and provocative scientific work in the area of Earth Science Informatics as it relates to Earth systems science and space science.

This includes articles on the application of formal and computational methods, computational Earth science, spatial and temporal analyses, and all aspects of computer applications to the acquisition, storage, processing, interchange, and visualization of data and information about the materials, properties, processes, features, and phenomena that occur at all scales and locations in the Earth system’s five components (atmosphere, hydrosphere, geosphere, biosphere, cryosphere) and in space (see "About this journal" for more detail).

The quarterly journal publishes research, methodology, and software articles, as well as editorials, comments, and book and software reviews.

Review articles of relevant findings, topics, and methodologies are also considered.

View Aims & Scope

---

Metrics & Ranking

Impact Factor

Year	Value
2025	3
2024	2.70

Journal Rank

Year	Value
2024	9086

Journal Citation Indicator

Year	Value
2024	2271

SJR (SCImago Journal Rank)

Year	Value
2024	0.635

Quartile

Year	Value
2024	Q2

h-index

Year	Value
2024	44

---

---

Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Web of Science

---

Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Earth and Planetary Sciences, designed to support cutting-edge academic discovery.

---

Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• Application of analytical hierarchy process, frequency ratio, and certainty factor models for groundwater potential mapping using GIS

  Citation: 453

  Authors: Yousef, Hamid Reza, Najmeh Samani, Omid

• Change detection techniques for remote sensing applications: a survey

  Citation: 307

  Authors: Anju, J.

• Groundwater qanat potential mapping using frequency ratio and Shannon’s entropy models in the Moghan watershed, Iran

  Citation: 300

  Authors: Seyed Amir, Hamid Reza, Zohre Sadat, Ashkan

• DrinC: a software for drought analysis based on drought indices

  Citation: 262

  Authors: Dimitris, Harris, George

• Machine learning techniques for monthly river flow forecasting of Hunza River, Pakistan

  Citation: 138

  Authors: Dostdar, Aftab Ahmed

• Experimental analysis of different software packages for orientation and digital surface modelling from UAV images

  Citation: 112

  Authors: Giovanna, Livio, Diana, Daniele, Rossana

• A machine learning approach to predict drilling rate using petrophysical and mud logging data

  Citation: 112

  Authors: Mohammad, Mohsen, David A., Rasool, Mohammad, Alireza

• A deep learning approach for hydrological time-series prediction: A case study of Gilgit river basin

  Citation: 107

  Authors: Dostdar, Tahir, Aftab Ahmed, Syed Ali Asad, Akhtar

• A comparison of slope units and grid cells as mapping units for landslide susceptibility assessment

  Citation: 103

  Authors: Qianqian, Yumin, Susu, Jiaxin, Huifang

• An ensemble method to forecast 24-h ahead solar irradiance using wavelet decomposition and BiLSTM deep learning network

  Citation: 99

  Authors: Pardeep, Manoj, Sumit

---