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 Advances in Deep Learning for Hyperspectral Image Analysis and Classification

Guest Editors: Masoumeh Zareapoor, Jinchang Ren, Huiyu Zhou, and Wankou Yang

Small unmanned aerial model accuracy for photogrammetrical fluvial bathymetric survey

Neil S. Entwistle and George L. Heritage

Spatial and spectral pattern identification for the automatic selection of high-quality MODIS images

Lluís Pesquer, Cristina Domingo-Marimon, and Xavier Pons

January 2019

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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


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


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


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


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


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

Sebastian Varela et al. (2017) Open Access


Plankton Aerosol, Cloud, ocean Ecosystem mission: atmosphere measurements for air quality applications

Ali H. Omar, Maria Tzortziou, Odele Coddington, Lorraine A. Remer (2018) 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


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


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