• Conference Proceedings
  • Journals
  • Journal of Applied Remote Sensing
    JARS Information for Authors
    Journal of Astronomical Telescopes, Instruments, and Systems
    Journal of Biomedical Optics
    Journal of Electronic Imaging
    Journal of Medical Imaging
    Journal of Micro/Nanolithography, MEMS, and MOEMS
    Journal of Nanophotonics
    Journal of Photonics for Energy
    Neurophotonics
    Optical Engineering
    Individual Subscriptions
    Institutional Subscriptions
    For Subscription Agents
  • SPIE Digital Library
  • Books
  • Open Access
  • Contact SPIE Publications
Print PageEmail Page

Journal of Applied Remote Sensing Special Section Calls for Papers


To submit a manuscript for consideration in a Special Section, please prepare the manuscript according to the journal guidelines and use the Online Submission System. A cover letter indicating that the submission is intended for this special section should be included with the paper. Papers will be peer‐reviewed in accordance with the journal's established policies and procedures. 

View the list of special sections that have already been published on the SPIE Digital Library.

CALLS FOR PAPERS:

Recent Advances in Geophysical Sensing of the Ocean: Remote and In Situ Methods

Feature and Deep Learning in Remote Sensing Applications

Improved Intercalibration of Earth Observation Data

Remote Sensing Assessment of Invasive Species Dynamics under Policy and Climate Change Impacts


ocean sensing

July-Sept 2017

Recent Advances in Geophysical Sensing of the Ocean: Remote and In Situ Methods

Weilin "Will" Hou
US Naval Research Laboratory
NRLSSC Code 7333
Stennis Space Center, Mississippi 39529, United States
E-mail: hou@nrlssc.navy.mil

Robert Arnone
University of Southern Mississippi
Department of Marine Science
Stennis Space Center, Mississippi 39529, United States
E-mail: robert.arnone@usm.edu

Call for papers: The special section seeks to address many issues related to remote and in situ sensing of the ocean. Open and coastal oceans are key areas to comprehensive understanding of our planet, from large-scale events such as El Nino, hurricane formation and tracking, to long-term events such as global climate change, to short-term weather predictions of both the atmosphere and the ocean, and small-scale oceanic properties as mixing patterns, biological layers, and visibility. Traditional ocean research techniques are widely augmented today with in situ sampling packages on moorings, buoys, floats, flow-through systems, mobile platforms (gliders, autonomous underwater vehicles, and remotely operated underwater vehicles), integrated sensor networks, and observatories. These are vibrant research and development areas and generate the most accurate data available, in 3-D, often in real-time, and are less affected by adverse conditions. However, spot sampling lacks the rapid, broad coverage that is critical in real-time decision making. In situ observations at times are not available for unsafe or inaccessible environments. Remote sensing techniques (both active and passive) have been proven to offer synoptic surface coverage with adequate accuracy, when sensors are calibrated and validated correctly. It is essential to establish and maintain precise protocols for deciding the appropriate mix and application of different sensor systems in order to maintain data coherence and comparability. Because of such requirements, it is important to understand how the oceanic and related atmospheric environment affects sensor performance, and what techniques are being developed to enhance sensor performance in challenging ocean environments.

The Journal of Applied Remote Sensing will publish a special section focusing on recent remote sensing advances in oceanic environment. While it is impossible to navigate through the many aspects of ocean remote sensing in one section, we do intend to focus on key elements and recent advances amongst the dynamic research areas (in bold below), including but not limited to the following:

Active and passive remote sensing of the ocean and atmosphere

  • ocean color-sensing sensors, algorithms, and products
  • recent development in lidar systems and algorithms
  • sea surface temperature (SST) sensors and algorithms
  • inversion techniques for active and passive measurements, basic physical properties
  • intercomparison for remote sensing applications
  • calibration and characterization of satellite/airborne sensors and related cal/val efforts

Sensors, in situ measurements, and platforms

  • in situ ocean optical measurement and sensors development
  • unmanned aerial vehicle (UAV or drones) sensing platform and sensors
  • unmanned underwater vehicle (UUV) and sensors
  • coastal ocean observation from buoys, observatories, and ships of opportunities

Ocean forecasting and applications

  • 3-D/4-D environmental forecasting
  • uncertainty assessment
  • ecosystem monitoring
  • fishery forecast

Marine physics

  • surface and internal waves, currents, tides, small-scale eddies, and turbulence
  • benthic and bathymetric properties
  • surf zones and shallow water optics.

The special section is open to everyone, and participants in the recent SPIE Ocean Sensing and Monitoring conference track are particularly invited to submit papers based on their presentations. All submissions will be peer reviewed.

Closed for submissions.

Top


October-December 2017

Feature and Deep Learning in Remote Sensing Applications

Guest Editors:

John E. Ball
Mississippi State University
Bagley College of Engineering
Electrical & Computer Engineering Department
Mississippi State, Mississippi, United States
E-mail: jeball@ece.msstate.edu

Derek T. Anderson
Mississippi State University
Bagley College of Engineering
Electrical & Computer Engineering Department
Mississippi State, Mississippi, United States
E-mail: anderson@ece.msstate.edu

Chee Seng Chan
University of Malaya
Faculty of Computer Science & Information Technology
Kuala Lumpur, Malaysia
E-mail: cs.chan@um.edu.my

Call for Papers: The shift from ‘human features' to machine-learned features has resulted in phenomenal results in numerous signal/image processing applications, from computer vision to speech recognition. Well-known examples of deep learning include deep belief nets (DBNs), convolutional neural networks (CNNs) and morphological shared weight neural networks (MSNNs), whereas feature learning in general includes techniques such as evolutionary constructed features (ECO) and improved ECO (iECO). Recently, feature and deep learning (FaDL) has made its way into numerous remote sensing applications, which includes analysis using sensors such as synthetic aperture radar (SAR), light detection and ranging (LiDAR), hyperspectral imaging, etc. These sensors provide heterogeneous data and they represent different regions of the electromagnetic spectrum. While FaDL has seen success in applications where large amounts of diverse data exist, FaDL in remote sensing is plagued by spectral, spatial, and temporal dimensionality, and usually has few training samples available due to the high cost of providing labeled data. In addition, most FaDL tools have a large number of parameters to estimate, and they take substantial hardware and time to train and test, which is often not realistic for many remotely sensed applications due to cost or time reasons.

The Journal of Applied Remote Sensing (JARS) will publish a special section on feature and deep learning applied to remote sensing applications. The scope includes, but is not limited to:

  • Remote sensing applications: agriculture, automated target detection, autonomy, change detection, disaster assessment, environmental sensing, forestry, hydrology, land cover classification, soil analysis, ocean sensing, urban analysis/planning, water resource analysis, and water control assessment.
  • Sensors: multi/hyperspectral, LiDAR, radar, synthetic aperture radar, automotive radar, stereo cameras, infrared (thermal), and sonar.
  • Multimodality: multisensor fusion at different stages in the data-processing lifetime.
  • FaDL challenges in remote sensing: limited training data, high spectral dimensionality, multisensor fusion, multiresolution data, and robust performance due to factors such as degradation effects like dust, rain, fog, etc.

Both application and theoretical papers are welcome. To submit to this special section, prepare the paper according to JARS guidelines (https://spie.org/AuthorGuidelines) and submit via the online submission system (https://jars.msubmit.net). A cover letter indicating that the submission is intended for this special section should be included. Papers will be peer-reviewed in accordance with the journal's established policies and procedures.

Manuscripts are due 30 April 2017.

Top


Improved Intercalibration of Earth Observation Data

Guest Editors:

Craig A. Coburn
University of Lethbridge
Alberta Terrestrial Imaging Centre
Department of Geography
Lethbridge, Alberta, Canada
E-mail: craig.coburn@uleth.ca

Aaron Gerace
Rochester Institute of Technology
Chester F. Carlson Center for Imaging Science
Digital Imaging and Remote Sensing Laboratory
Rochester, New York, United States
E-mail: gerace@cis.rit.edu

Call for papers: The last 20 years has witnessed a tremendous expansion in the Earth observation ecosystem. There are many new space-borne imaging systems being deployed to serve the ever-evolving needs of the remote sensing community. These new systems are being developed to address a wide range of environmental problems, often with a dedicated application for each sensor. The ability to combine data from several different sensing systems is essential to ensuring that all users of remotely sensed data have reliable, calibrated, and intercalibrated images to suit their needs (past, present, and future).

Vicarious calibration using pseudo-invariant calibration sites (PICS) provides an independent and traceable link between preflight and postlaunch calibration efforts. The objective of this technique is to provide a series of well-characterized ground-based measurements in conjunction with atmospheric measurements and image data to allow image comparison on a common radiometric scale. These procedures have been in use for almost 30 years and have been successful at calibrating airborne and spaceborne systems. The models used to compute the top of atmosphere spectral radiance or reflectance require a measure of surface material properties [e.g., bidirectional reflectance distribution function (BRDF)], atmospheric conditions, and sensor properties. Detailed estimates of these parameters are limited by the lack of field instruments for many Earth targets, yet are essential to develop a very high quality radiometric correction. Recent efforts have been made to provide a more detailed suite of surface, sensor, and atmospheric measurements that would allow the intercalibration of measurements in time, space, spectral, and for different view angles.

The Algodones Dunes system in California, United States, has been identified as a potentially attractive calibration site for U.S. spaceborne assets due to proximity, size, and pseudo-invariant nature. As such, a field campaign was conducted at this site in March 2015 to develop a better understanding of some of the key parameters that will likely impact calibration fidelity when utilizing this location, e.g., the BRDF of sand.

The Journal of Applied Remote Sensing will publish a special section focusing on intercalibration methods and outcomes. We invite you to submit manuscripts focused on site identification and characterization of the relevant parameters that impact the intercalibration process. We are particularly interested in field campaigns that identify and characterize potential calibration sites for a range of materials and spectral channels. The topics may include, but are not limited to, the following:

  • BRDF characterization of "pseudo-invariant" sites.
  • Assessing the impact of atmospheric effects on intercalibration.
  • Assessing the impact of varying sensor effects on intercalibration.
  • Assessing the impact of temporal effects, (i.e., lag time between platforms), on intercalibration.

To submit a manuscript for consideration in the special section, please prepare the manuscript according to the journal guidelines and submit the paper via the online submission system https://jars.msubmit.net. A cover letter indicating that the submission is intended for this special section should be included with the paper. Papers will be peer-reviewed in accordance with the journal's established policies and procedures.

Please do not hesitate to contact us if you have any questions about this special section.

Submissions due 1 June 2017.

Top


brome grass

Remote Sensing Assessment of Invasive Species Dynamics under Policy and Climate Change Impacts

Guest Editors:

Dong Yan
South Dakota State University
Geospatial Sciences Center of Excellence
1021 Medary Avenue
Wecota Hall 220, Box 506B
Brookings, South Dakota 57007, United States
E-mail: dong.yan@sdstate.edu

E. Raymond Hunt, Jr.
USDA-ARS Hydrology and Remote Sensing Laboratory
Building 007, Room 104, BARC-West
Beltsville, Maryland 20705-2350, United States
E-mail: Raymond.Hunt@ars.usda.gov

Maria J. Ferreira dos Santos
Utrecht University
Faculty of Geosciences
Copernicus Institute of Sustainable Development, Environmental Sciences Group
Heidelberglaan 2, 3584 CS Utrecht, Room 1101B
P.O. Box 80115, 3508 TC
Utrecht, The Netherlands
E-mail: M.J.FerreiraDosSantos@uu.nl

Call for Papers: The environmental and economic consequences of biological invasions are a global concern. Invasive species can have profound influences on resident ecosystems by causing changes in fundamental ecosystem properties such as nutrient cycling, species composition, and fire regime. Changes in management policies and climate can affect those consequences by imposing different impacts on invasive and native species simultaneously. Understanding the geomorphological, environmental, and ecological factors governing species distributions and population growth of invasive species may offer novel insights into the colonization dynamics and spread of invasive taxa in response to policy and climate changes.

Facing these research needs, this special section aims to present recent advances regarding the approaches and applications of using remotely sensed data and image processing technologies to facilitate complex feature extractions and to address the population dynamics of invasive species driven by policy and climate changes. The open access to multidecadal remote sensing products derived from Earth-observation missions such as the USGS Landsat and the NASA Moderate-Resolution Imaging Spectroradiometer (MODIS) provide the opportunity to further support modeling the responses of invasive species to policy and climate changes, the results of which can help predict the dynamics of invasive species under future policies and climate change scenarios. The synergistic use of high-quality remotely sensed datasets covering a wide range of spectral, spatial, and temporal resolutions will further deepen the knowledge regarding the impacts of policy and climate changes on invasive species control.

The Journal of Applied Remote Sensing will publish a special section focusing on the remote sensing assessment of invasive species dynamics under policy and climate change impacts. We invite you to make submissions related to novel approaches and applications of investigating how invasive species respond to policy and climate changes, and the associated impacts. The topics of interest may include, but are not limited to, the following:

Novel approaches to characterize invasive species dynamics:

  • Change detection using fused multisource remote sensing data, solar-induced fluorescence, thermal infrared, microwave, and lidar data
  • Multiscale and multifaceted monitoring using webcam images and eddy covariance measurements

Novel remote sensing applications to assess the responses and consequences of invasive species dynamics:

  • Examination of how the dynamics of invasive species affect fire regime and carbon storage due to changes in policy or climate
  • Investigation of how invasive species respond to vegetation conservation programs or urbanizations
  • Exploration of how invasive species respond to extreme weather events such as droughts and floods
  • Synergistic integration between socioeconomic data and remotely sensed data for systems analysis with sociotechnical approaches

To submit a manuscript for consideration, please prepare the manuscript according to the journal guidelines (http://spie.org/AuthorGuidelines) and submit the paper via the online submission system (https://jars.msubmit.net). A cover letter indicating that the submission is intended for this special section should be included with the paper. Papers will be peer-reviewed in accordance with the journal's established policies and procedures.

Please do not hesitate to contact us if you have any questions about this special section.

Manuscripts due 1 May 2017.

Top


Published Special Sections:

Remote Sensing for Investigating the Coupled Biogeophysical and Biogeochemical Process of Harmful Algal Blooms (January-March 2017)
Guest Editors: Alan Weidemann and Ni-Bin Chang

Sparsity-Driven High Dimensional Remote Sensing Image Processing and Analysis (October-December 2016)
Guest Editors: Xin Huang, Paolo Gamba, and Bormin Huang

Advances in Remote Sensing for Renewable Energy Development: Challenges and Perspectives (2015)
Guest Editors: Yuyu Zhou, Lalit Kumar, and Warren Mabee

Onboard Compression and Processing for Space Data Systems (2015)
Guest Editors: Enrico Magli and Raffaele Vitulli

Management and Analytics of Remotely Sensed Big Data (2015)
Guest Editors: Liangpei Zhang, Qian (Jenny) Du, and Mihai Datcu

Remote Sensing and Sensor Networks for Promoting Agro-Geoinformatics (2014 and 2015)
Guest Editors: Liping Di and Zhengwei Yang

High-Performance Computing in Applied Remote Sensing: Part 3 (2014)
Guest Editors: Bormin Huang, Jiaji Wu, and Yang-Lang Chang

Airborne Hyperspectral Remote Sensing of Urban Environments (2014)
Guest Editors: Qian (Jenny) Du and Paolo Gamba

Progress in Snow Remote Sensing (2014)
Guest Editors: Hongjie Xie, Chunlin Huang, and Tiangang Liang

Advances in Infrared Remote Sensing and Instrumentation (2014)
Guest Editors: Marija Strojnik and Gonzalo Paez

Earth Observation for Global Environmental Change (2014)
Guest Editor: Huadong Guo

Advances in Onboard Payload Data Compression (2013)
Guest Editors: Enrico Magli and Raffaele Vitulli

Advances in Remote Sensing Applications for Locust Habitat Monitoring and Management (2013)
Guest Editors: Ramesh Sivanpillai and Alexandre V. Latchininsky

High-Performance Computing in Applied Remote Sensing: Part 2 (2012)
Guest Editors: Bormin Huang and Antonio Plaza

Advances in Remote Sensing for Monitoring Global Environmental Changes (2012)
Guest Editors: Yuyu Zhou, Qihao Weng, Ni-Bin Chang

High-Performance Computing in Applied Remote Sensing: Part 1 (2011)
Guest Editors: Bormin Huang and Antonio Plaza

Satellite Data Compression (2010)
Guest Editor: Bormin Huang

Remote Sensing for Coupled Natural Systems and Built Environments (2010)
Guest Editor: Ni-Bin Chang 

Remote Sensing Applications to Wildland Fire Research in the Eastern United States: Selected Papers from the 2007 EastFIRE Conference - Part 2 (2009)
Guest Editors: John J. Qu and Stephen D. Ambrose

Remote Sensing of the Wenchuan Earthquake (2009)
Guest Editor: Huadong Guo

Remote Sensing Applications to Wildland Fire Research in the Eastern United States: Selected Papers from the 2007 EastFIRE Conference (2008)
Guest Editors: John J. Qu and Stephen D. Ambrose

Aquatic Remote Sensing Applications in Environmental Monitoring and Management (2007)
Guest Editors: Vittorio E. Brando and Stuart Phinn


Author Tools

General Guidelines for Authors
Open Access