Journal of Applied Remote Sensing

Editor-in-Chief: Ni-Bin Chang, University of Central Florida

The Journal of Applied Remote Sensing (JARS) is an online journal that optimizes the communication of concepts, information, and progress within the remote sensing community to improve the societal benefit for monitoring and management of natural disasters, weather forecasting, agricultural and urban land-use planning, environmental quality monitoring, ecological restoration, and numerous other commercial and scientific applications. 

Journal of Applied Remote Sensing

Special Section on Optics in Atmospheric Propagation and Adaptive Systems

Guest Editors: Karin Stein, Szymon Gladysz, Christian Eisele, and Vladimir Lukin

Special Section on Advances in Agro-Hydrological Remote Sensing for Water Resources Conservation

Guest Editors: Antonino Maltese and Christopher M. U. Neale

Special Section on Advances in Remote Sensing for Air Quality Management

Guest Editors: Barry Gross, Klaus Schäfer, Philippe Keckhut

September 2018

TOP DOWNLOADS

from the Journal of Applied Remote Sensing


Comprehensive survey of deep learning in remote sensing: theories, tools, and challenges for the community

John E. Ball, Derek T. Anderson, Chee Seng Chan (2017) Open Access


Above-ground biomass prediction by Sentinel-1 multitemporal data in central Italy with integration of ALOS2 and Sentinel-2 data

Gaia Vaglio Laurin et al. (2018) Open Access


Remote sensing estimation of surface oil volume during the 2010 Deepwater Horizon oil blowout in the Gulf of Mexico: scaling up AVIRIS observations with MODIS measurements

Chuanmin Hu et al. (2018) Open Access


Advances in multiangle satellite remote sensing of speciated airborne particulate matter and association with adverse health effects: from MISR to MAIA

David J. Diner et al. (2018) Open Access


Rapid broad area search and detection of Chinese surface-to-air missile sites using deep convolutional neural networks

Richard A. Marcum, Curt H. Davis, Grant J. Scott, Tyler W. Nivin (2017) Open Access


Spatio-temporal evaluation of plant height in corn via unmanned aerial systems

Sebastian Varela et al. (2017) Open Access


Extracting distribution and expansion of rubber plantations from Landsat imagery using the C5.0 decision tree method

Zhongchang Sun, Patrick Leinenkugel, Huadong Guo, Chong Huang, Claudia Kuenzer (2017) Open Access


Comparison of mosaicking techniques for airborne images from consumer-grade cameras

Huaibo Song, Chenghai Yang, Jian Zhang, Wesley C. Hoffmann, Dongjian He, J. Alex Thomasson (2016) Open Access


Segmentation model based on convolutional neural networks for extracting vegetation from Gaofen-2 images

Chengming Zhang, Jiping Liu, Fan Yu, Shujing Wan, Yingjuan Han, Jing Wang, Gang Wang (2018) Open Access


Evaluation of ceilometer attenuated backscattering coefficients for aerosol profile measurement

Yoshitaka Jin et al. (2018) Open Access


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Author Benefits:

  • Rigorous, prompt peer review (median time from submission to first decision: 37 days)
  • Rapid, e-first publication of articles (median time from acceptance to publication: 23 days)
  • Professional copyediting and typesetting
  • Free online color figures
  • Free inclusion of video and multimedia content
  • 5 free downloads from the SPIE Digital Library for authors
  • Open access publication option at a low cost
  • Eligibility for one of three annual best paper awards. See the press release about the most recent awards here.
  • Integration with Code Ocean, a cloud-based code development and publishing platform

 

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