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Most Cited Articles from 2018

International Journal of Remote Sensing

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.

The Most Cited papers from 2018 reflect the broad range of coverage of IJRS, including both methods and applications of remote sensing. Many of the papers have a focus on general and application-specific classification methods. Notably, three of the papers deal with unmanned aerial systems (UAS), reflecting the journals special focus on this area and the establishment of our new section to the journal titled “Drones.”

International Journal of Remote Sensing

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IJRS ranks 14/30 in Remote Sensing with a 2018 Impact Factor of 2.493*
       *Copyright: Journal Citation Reports®, Clarivate Analytics, 2019.

Article TitleAuthor(s)Volume Issue
Implementation of machine-learning classification in remote sensing: an applied review
Aaron Maxwell, Timothy Warner & Fang Fang 399
Land cover 2.0
Michael Wulder, Nicholas Coops, David Roy, Joanne White & Txomin Hermosilla 3912
Deciduous tree species classification using object-based analysis and machine learning with unmanned aerial vehicle multispectral data
Steven Franklin & Oumer Ahmed 3915-16
Assessing the status of forest regeneration using digital aerial photogrammetry and unmanned aerial systems
Tristan Goodbody, Nicholas Coops, Txomin Hermosilla, Piotr Tompalski & Patrick Crawford 3915-16
Visual descriptors for content-based retrieval of remote-sensing images
Paolo Napoletano 395
SAR-based detection of flooded vegetation - a review of characteristics and approaches
Viktoriya Tsyganskaya, Sandro Martinis, Philip Marzahn & Ralf Ludwig 398
Observation scope and spatial coverage analysis for earth observation from a Moon-based platform
Hanlin Ye, Huadong Guo, Guang Liu & Yuanzhen Ren 3918
Calibration and accuracy assessment in a direct georeferencing system for UAS photogrammetry
Petr Gabrlik, Anders la Cour-Harbo, Petra Kalvodova, Ludek Zalud & Premysl Janata 3915-16
Object-based land-cover change detection applied to Brazilian seasonal savannahs using geostatistical features
Eduardo de Oliveira Silveira, Jose de Mello, Fausto Acebri Junior & Luis de Carvalho 398
The effect of fusing Sentinel-2 bands on land-cover classification
Mateo Gasparovic & Tomislav Jogun 393

Taylor & Francis Earth & Environmental Sciences

Remote Sensing Letters is IJRS' sister journal.