International Journal of Remote Sensing

Aims & Scope

The International Journal of Remote Sensing ( IJRS) is concerned with the theory, science and technology of remote sensing and novel applications of remotely sensed data.

The journal’s focus includes remote sensing of the atmosphere, biosphere, cryosphere and the terrestrial earth, as well as human modifications to the earth system.

Principal topics include: • Remotely sensed data collection, analysis, interpretation and display. • Surveying from space, air, water and ground platforms. • Imaging and related sensors. • Image processing. • Use of remotely sensed data. • Economic surveys and cost-benefit analyses. • Drones Section: Remote sensing with unmanned aerial systems (UASs, also known as unmanned aerial vehicles (UAVs), or drones).

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	2.6
2024	3.00

SJR (SCImago Journal Rank)

Year	Value
2024	0.676

Quartile

Year	Value
2024	Q2

h-index

Year	Value
2024	210

Journal Rank

Year	Value
2024	8452

Journal Citation Indicator

Year	Value
2024	3538

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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

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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.

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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.

• The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features

  Citation: 5607

  Authors: S. K.

• Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery

  Citation: 4302

  Authors: Hanqiu

• Review Article Digital change detection techniques using remotely-sensed data

  Citation: 2787

  Authors: ASHBINDU

• Random forest classifier for remote sensing classification

  Citation: 2627

  Authors: M.

• A survey of image classification methods and techniques for improving classification performance

  Citation: 2517

  Authors: D., Q.

• Characteristics of maximum-value composite images from temporal AVHRR data

  Citation: 2408

  Authors: BRENT N.

• Change detection techniques

  Citation: 2225

  Authors: D., P., E., E.

• Development of a global land cover characteristics database and IGBP DISCover from 1 km AVHRR data

  Citation: 2047

  Authors: T. R., B. C., J. F., D. O., Z., L., J. W.

• Use of normalized difference built-up index in automatically mapping urban areas from TM imagery

  Citation: 2035

  Authors: Y., J., S.

• An extended AVHRR 8‐km NDVI dataset compatible with MODIS and SPOT vegetation NDVI data

  Citation: 1956

  Authors: Compton J., Jorge E., Molly E., Daniel A., Edwin W., Robert, Eric F., Nazmi

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