Journal of Applied Remote Sensing

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

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. 

On the cover: The figure is from "Deep learning in land-use classification and geostatistics in soil pH mapping: a case study at Lakehead University Agricultural Research Station, Thunder Bay, Ontario, Canada" by Valeria Campos Carrillo et al. in Vol. 16, Issue 3.

Calls for Papers
How to Submit a Manuscript

Regular papers: Submissions of regular papers are always welcome.

Review papers: JARS welcomes proposals for review paper topics on an ongoing basis. Review papers receive complimentary open access. Please submit your proposal to JARS@spie.org.

Special section papers: Open calls for papers are listed below. A cover letter indicating that the submission is intended for a particular special section should be included with the paper.

To submit a paper, please prepare the manuscript according to the journal guidelines and use the online submission systemLeaving site. All papers will be peer‐reviewed in accordance with the journal's established policies and procedures. Authors have the choice to publish with open access.

Advanced Infrared Technology and Remote Sensing Applications II
Publication Date
Vol. 18, Issue 2
Submission Deadline
Submissions open 1 May through 30 September 2023.
Guest Editors

Optics Research Center
Mexico
mstrojnik@gmail.com

Hong Kong Polytechnic University
Hong Kong
owen.chen@polyu.edu.hk

Jet Propulsion Laborataory
United States
sarath.d.gunapala@jpl.nasa.gov

Joern Helbert

German Aerospace Institute
Germany
Joern.Helbert@dlr.de

Pontificia Universidad Catolica de Valparaiso
Chile
esteban.vera@pucv.cl

National Institute of Standards and Technology
United States
eric.shirley@nist.gov

Scope

This special section of the Journal of Applied Remote Sensing is based on the 30 th symposium on Infrared Remote Sensing and Instrumentation, which has been held each year during the SPIE Optics+Photonics meeting in San Diego, California. While meeting participants are particularly encouraged to submit their work, this section is open to all contributions. A very-well received special section, arising from the same series of conferences, was published in JARS in 2014, with more than 20 papers. See the Special Section on Infrared Remote Sensing and Instrumentation in Vol. 8. Issue 1.

IR technology and its applications have been growing exponentially within the past decade due to the deployment of novel materials in previously unexplored IR bands, including Visible-Near IR [0.7 mm – 1.1 mm], Near IR [1 mm – 3 mm], and Very-Far IR [15 mm – 100 mm] in addition to the traditional mid-IR [3 mm – 5 mm] and far IR [8 mm – 14 mm] spectral bands. This technological expansion has fueled novel IR applications as related to remote sensing of the Earth, atmosphere, and the skies, either from a mobile platform or from the ground. We are particularly interested in using IR in exploration of planetary systems inside and outside our solar system. In remote sensing, we include also non-contact testing and characterization of art hardware (paints, linens, wood, interpretation of illegible text), planetary exploration, and astronomy. These recent applications have arisen in addition to the traditional uses of IR to optical sensing, analytical studies in chemistry, undetected monitoring in industry, security, and non-destructive non-perturbing testing of materials and structures. While the military has traditionally maintained the lead in the development of novel materials due to research costs, recent applications have incorporated special-purpose experimental and data-processing techniques tailored to probing specific features. Neural networks, machine learning, and artificial intelligence have stepped in to facilitate in-situ decision making.

This section is aimed at scientists, engineers, and practitioners interested in understanding the basic principles of infrared science, including the generation and characterization of IR radiation—its spatial, spectral, and temporal modulation—and propagation through diverse media, including gases, atmospheres, liquids, materials, and dark matter, and finally detection, including spatial, spectral, and temporal demodulation techniques.

Topics of interest include but are not limited to the following areas:

  • Scientific objectives for future remote sensing and planetary missions
  • Scientific results for those missions that have flown
  • Instrument design requirements to meet mission objectives and the resultant design and implementation experiences
  • Sensor technology challenges in meeting instrument requirements
  • Instrument and sensor integration challenges and experiences
  • Planned and required enabling technologies


Papers are solicited on the following and related topics:

REMOTE SENSING FUNDAMENTALS

  • Radiometry and energy throughput
  • Imaging
  • Fundamental limits to IR imaging, including detector quantum noise and background limit
  • Stray light considerations, including analysis, signal-to-noise, and instrument performance limitations
  • Instrument calibration, comparison of predicted and measured results
  • Space environment and radiation effects
  • Calibration and testing
  • Data analysis
  • Standards and characterization of components and materials
  • IR/electro-optical system modeling and simulations
  • Non-contact and non-invasive technique


INSTRUMENT OBSERVATIONAL FACILITIES

  • Planck Observatory
  • James Webb Space Telescope


INSTRUMENTS AND THEIR SCIENTIFIC RETURNS

  • Bolometers
  • Spectrometers
  • Imaging cameras
  • Photometers (multiband)
  • Radiometers
  • Imaging and nonimaging interferometers
  • Microcameras


REMOTE SENSING

  • Earth resource mapping
  • Atmosphere and weather prediction
  • Space exploration
  • Exploration of planets and comets within our solar system
  • Generation of light noise and ground temperature increase in urban and populated environments
  • Remote diagnostics and monitoring in human-unfriendly and disaster environments (nuclear power plants, earthquake, tsunami, and mines)
  • Contamination of natural sources of sweet water and their reclamation
  • Monitoring of forests, their diseases, fuel accumulation, and fire occurrences
  • Monitoring of volcanic activities
  • Natural and human-made fires and their propagation
  • Remote monitoring of humans and animals in quarantine and controlled-access environments
  • Remote calibration
  • Moon reconnaissance
  • Compact satellites
  • Satellite security and monitoring


ENABLING TECHNOLOGIES

  • Sensor design
  • Cold read-out electronics
  • Data processing
  • Infrared materials


INFRARED TELESCOPES FOR EARTH REMOTE SENSING, FOCAL PLANE TECHNOLOGY, AND DETECTION SCHEMES

  • Near-IR detectors
  • IR detectors
  • Mid-IR detectors and sources
  • Far-IR detectors
  • Sub-mm detectors
  • Focal plane layout and architecture
To submit a manuscript for consideration, 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. Peer review will commence immediately upon manuscript submission, with a goal of making a first decision within six weeks of manuscript submission. The special section is opened online once a minimum of four papers have been accepted. Each paper is published as soon as the copyedited and typeset proofs are approved by the author.
Infrared Technology
Frontiers in Image and Signal Processing for Remote Sensing
Publication Date
Vol. 17, Issue 3
Submission Deadline
1 January 2023
Guest Editors
Chi Lin

Dalian University of Technology
Institute of Intelligent Systems
School of Software
Dalian, China
clindut@ieee.org

Chang Wu Yu

Chung Hua University
Department of Computer Science and Information Engineering
Hsinchu, Taiwan
cwyu@chu.edu.tw

Scope

In general, remote sensing acquires information by detecting, analyzing, and monitoring physical characteristics of an area by recording its emitted energy or radiation without having any physical contact with the area or object. Although most satellite data are in image forms, this method of signal processing extracts specific information from remotely sensed data such as waveforms or time series data.

Image processing performs operations or actions on an image to receive an enhanced image form, or to extract some useful information from the image. In this method of signal processing, image is an input and the resulting output may be an image or characteristic features of the respective image. There are some general phases that all types of data have to undergo while using image processing techniques such as pre-processing, image transformation, image classification, enhancement, and analysis. Synthetic aperture radar (SAR) is a unique remote sensing technique with the ability to obtain high-resolution microwave images day and night under all weather conditions. For this reason SAR has been used in various fields, such as digital elevation model  generation, monitoring landslides, flood disasters, and earthquakes, observation of vegetation growth, land and sea traffic monitoring, ocean current monitoring, and identifying oil spills.

However, signal processing deals with mapping or transforming information-bearing signals into another form of resultant signals for the development of some application benefits. This process explains an analog or continuous system if it involves functions representing the input and output signals. Examples of signals include sound pressure, electrocardiogram, radio or television broadcast, and sunspot count. Signal processing has varied applications in consumer-electronics devices like HDTVs, cell phones, and cameras and in transportation, medical services, and the military. In our case of remote sensing, this signal processing technique helps in detecting and analyzing in the fields of astronomy, climate monitoring, and weather forecasting. Hyperspectral remote sensing is an emerging technology in the field of remote sensing that is being investigated by scientists and researchers for detecting manmade materials, terrestrial vegetation, and identification of minerals. In recent times, this area has attracted more attention and contributions from different communities, such as signal processing, image processing, optimization, AI, and ML. Some of the typical signal processing techniques include eliminating or reducing noise to provide clean noise that reflects the original signals from the source. In the case of remote sensing, blurred satellite images need to be processed to obtain clean and undistorted imagery, and extracting indirect quantity from a measured signal also prevails in signal processing.

Topics may include but are not limited to:

  • Image and signal processing in hyperspectral remote sensing
  • Remote sensing data interpretation and analysis
  • Image pre-processing, classification, and enhancement
  • Image and signal detection and recognition
  • Deep learning and ML techniques for image processing using remote sensing
  • Filtering and multiresolution processing in image processing
  • Change detection and analysis with satellite time series
  • Extraction of geometric and semantic information from SAR
  • Supervised and unsupervised classification of remote sensing data
  • Applications of airborne, satellite, UAV, and proximate remote sensing
  • Case studies on remote sensing applications in various fields
To submit a manuscript for consideration, 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. Peer review will commence immediately upon manuscript submission, with a goal of making a first decision within six weeks of manuscript submission. The special section is opened online once a minimum of four papers have been accepted. Each paper is published as soon as the copyedited and typeset proofs are approved by the author.
Image and Signal Processing
Meeting the Challenges of Ecosystem Management using Remote Sensing
Publication Date
Vol. 17, Issue 2
Submission Deadline
Closed
Guest Editors
Manjit Kaur

Gwangju Institute of Science and Technology
Republic of Korea
Manjitkaur@gist.ac.kr

Raman Singh

University of the West of Scotland
United Kingdom
Raman.Singh@uws.ac.uk

Hassène Gritli

University of Carthage
Tunisia
grhass@yahoo.fr

Scope

In recent years, the increase in environmental pollution and climate change problems has created many challenges for the management of ecosystems around the globe. Climate change occurs due to natural hazards and human-made activities that damage the ecosystem through cyclones, tornadoes, and wildfires, and other potential threats. Effective conservation plans are needed for maintaining the best environmental health by obtaining information from ecosystems through remote sensing by analyzing up-to-date geographical data and also finding the optimum spatial relationship between natural resources, human activities, and natural hazards for maintaining a better ecosystem. Such data improves ecosystem management and enhances monitoring of the resources available in the ecosystem. It also could provide preventive solutions to ecosystem threats.

Remote sensing technology with dynamic and integrated measurements of ecosystem health helps to monitor and effectively manage assessment associated with the ecosystem. Tools included for ecosystem monitoring, such as geographical information systems, have potential for mapping within a specific area to visualize spatial and temporal patterns. These data ultimately help improve services and implementation of policies. Remote sensing for ecosystem health includes mainly vigorous health, including green vegetation, bare soil cover, and biochemical properties of vegetation. Remote sensing of the organization consists of species richness and biodiversity, structural train, e.g. tree height.

Despite having potential advantages of remote sensing in maintaining the health of ecosystems around the globe, potential challenges associated with its implementation include mainly special scale issues, transportability of remotely sensed data through sensors, and costly data availability for enhancing quality. In addition, uncertainties in ecosystem health pose potential challenges to remote sensing technology in ecosystem health management. Based on the above, we invite researchers working in ecosystem and remote sensing technology to address the research gap associated with the management of the ecosystem with remote sensing technology and find potential solutions for its implementation.

Topics of interest include but are not limited to:

  • Remote sensing technology in mountain ecosystems
  • Current challenges of incorporating remote sensing technology in ecosystem management
  • Advanced sensing technologies for the management of ecosystem
  • Effective policies for ecosystem management
  • The role of remote sensing technology in environmental studies and modeling
  • Preprocessing and validation issues associated in remote sensing technology for ecological location mapping
  • Remote sensing technology in estimating forest structure
  • Applications of remote sensing in ecosystem management
  • Evaluating carbon stocks using remote sensing technology
  • Achieving smart forest using remote sensing technology
  • Remote sensing technology in tropical forests

To submit a manuscript for consideration, 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. Peer review will commence immediately upon manuscript submission, with a goal of making a first decision within six weeks of manuscript submission. The special section is opened online once a minimum of four papers have been accepted. Each paper is published as soon as the copyedited and typeset proofs are approved by the author.

Ecosystem Management
Digital Mapping in Agriculture: Geospatial Techniques, Satellites, and Methods
Publication Date
Vol. 17, Issue 1
Submission Deadline
Closed
Guest Editors

Indian Institute of Technology
Roorkee, India
pkgiitr@gmail.com

Rahul Dev Garg

Indian Institute of Technology
Roorkee, India
rdgarg@gmail.com

Indian Institute of Remote Sensing
Indian Space Research Organization
Dehradun, India
hari.isro@gmail.com

Scope

Digital mapping in agriculture is usually concerned with determining the state of one (or several)
physical, biological, or geographic parameters in the land, such as soil temperature, soil
moisture, soil organic matter, crop cover, crop type, or crop status, in the geospatial framework.
Recent advances in machine learning classification/regression algorithms and artificial
intelligence, and availability of theme specific sensors, such as for land monitoring, and atmospheric and oceanic studies, and different available databases (soil moisture, temperature,
precipitation, etc.) develop a better understanding in agricultural systems on a global scale to field
specific scale and greatly promoted scientific studies and applications in agriculture. Digital
mapping in agriculture supports development and guides site-specific management strategies to
optimize production on field specific scale and also helps in monitoring food security globally by
providing timely and accurate crop estimation.

Research work in digital agriculture has three categories: (1) diagnostic purposes (crop cover, crop type, phenology mapping, essential agricultural variables and soil parameters mapping, etc.), (2) predictive purposes (development of crop yield forecasting models, etc.), and (3) prescriptive purposes (optimization of nourishment , crop health/ disease identification, optimization of irrigation, etc.). However, the complex and interconnected linkages between soil-landscape parameters under a range of soil and climatic conditions are key open questions for the scientific community. Developing an understanding of the link between above-ground plant growth and productivity under a range of soil and climatic conditions is a demand for agro-ecosystem management. 

This special section will promote the most innovative results coming from research in the field of digital mapping in agriculture. It provides an effective platform for disseminating original and
fundamental research and experience in the rapidly advancing area of digital mapping in
agriculture.

Review and research papers are invited on but not limited to the following topics:

  • Development in observation techniques. Available and planned sensors/satellite system,
    drone-based observations, in-field sensors, and technological aspect in the field of
    multispectral, hyper spectral and thermal imaging sensors dedicated to agriculture
  • Recent in model development. Crop prediction and forecasting models (crop
    specific/generic); indices, fusion of data, and machine learning methods for estimating
    soil physio-chemical properties and crop characteristics, time series
  • Recent in mapping in geospatial framework. The assessment and mapping of crop land,
    crop type, crop health (disease/pest detection/nutrition), rangelands, pasture land, other
    grazing lands, phenology, essential agricultural variables and soil parameters (soil
    organic carbon, nitrogen, soil moisture etc.) and land-degradation processes
  • Development in agricultural management. Soil and climatic conditions for agroecosystem
    management, defining management zones, field-level recommendations,
    decision support systems, expert systems, web applications, mobile applications, remote
    identification and assessment, site-specific crop management, smart systems for
    precision agriculture

To submit a manuscript for consideration, 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. Peer review will commence immediately upon manuscript submission, with a goal of making a first decision within six weeks of manuscript submission. The special section is opened online once a minimum of four papers have been accepted. Each paper is published as soon as the copyedited and typeset proofs are approved by the author.

Digital Mapping
Urban Remote Sensing and Smart Cities
Publication Date
Vol. 17, Issue 1
Submission Deadline
Closed
Guest Editors
Marimuthu Karuppiah

SRM Institute of Science and Engineering
Chennai, India
kmarimuthu@ieee.org

Shehzad Ashraf Chaudhry

Istanbul Gelisim University
Istanbul, Turkey
sashraf@gelisim.edu.tr

Mohammed H. Alsharif

Sejong University
Seoul, Republic of Korea
malsharif@sejong.ac.kr

Scope

Smart cities play an integral part in economic growth. People are increasingly migrating toward smart cities in search of economic growth and better career opportunities. Furthermore, rapid growth of urbanization and the rapid influx of people to cities leads to overpopulation. As a result, urban planning today is confronted with major challenges such as unplanned expansion, water management crisis, traffic congestion, and encroachments in fringe areas.

Smart cities can provide smart solutions for various infrastructural problems during the planning stage of the city. Smart city applications are developed through the fusion of various domains of geoscience and IoT. The primary aim of smart cities is to make better decisions and achieve effective use of resources through data it collects. Smart city applications extract an enormous amount of data and formulate a well-designed data analysis strategy that can aid city officials in better decision making. Additionally, several projects are developed to achieve various smart services, including safer communication, smart homes, smart healthcare, etc. Despite smart city solutions aimed at eliminating systemic inefficiencies, there are concerns that smart cities are detached from existing planning and management methods that are well-established and built upon a decade of practice. Remote sensing is one of the crucial technologies that is employed to extract data and map the region. Additionally, remote sensing can aid real-time supervision of urban pollution, urban planning, and traffic management. With many high-resolution sensors being developed for collecting the information, it is possible to achieve seamless communication within the sensors, thereby aiding the city planners to redistribute the resources efficiently. Furthermore, remote sensing technology can monitor the city’s air quality, weather patterns, traffic conditions, and several parameters. Additionally, various designated sensors assist in disaster assessment and post-disaster management. In contrast, the sensor nodes are prone to error. As a result, there are various concerns about the data reliability of a sensory network. Moreover, today’s digital remote sensing tools do not adequately extract indigenous knowledge of the place. Moreover, sensors are confronted with limited battery life, limited processing speed, and various obstacles in transmission.

This special section aims to address various applications, advantages, disadvantages, and research gaps in urban remote sensing and smart cities. We welcome research works that cover all aspects of remote sensing applications in smart cities more innovatively.

Topics of interest include but are not limited to the following:

  • Smart urban management systems with remote sensing applications
  • New sensors and urban remote sensing
  • Advances in remote sensing for smart sustainable cities
  • Role of remote sensing in management of urban ecology
  • Satellite imagery in urban planning and development
  • Trends in remote sensing for smart agriculture
  • Earth observation and disaster resilience in smart cities with remote sensing
  • Scalable and efficient remote sensing techniques for urban development
  • Remote sensing for innovative smart city applications
  • Spatiotemporal analysis for various smart city applications

To submit a manuscript for consideration, 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. Peer review will commence immediately upon manuscript submission, with a goal of making a first decision within six weeks of manuscript submission. The special section is opened online once a minimum of four papers have been accepted. Each paper is published as soon as the copyedited and typeset proofs are approved by the author.

Remote Sensing for Sustainable Forest Management
Publication Date
Vol. 16, Issue 4
Submission Deadline
Closed
Guest Editors
Ali Ahmadian

University Mediterranea of Reggio Calabria
Reggio Calabria, Italy
ahmadian.hosseini@unirc.it

Valentina E. Balas

Aurel Vlaicu University
Arad, Romania
balas@drbalas.ro


Soheil Salahshour

Bahcesehir University
Istanbul, Turkey
soheil.salahshour@eng.bau.edu.tr


Scope

In the technologically developed world, remote sensing is potentially important for various fields, including engineering, forestry, geology, geography, urban planning, and agriculture. Also, forest inventory and management are rapidly changing due to current economic, environmental, and social policy objectives. Hence, using remote sensing techniques to acquire forest-related information for mapping, monitoring, and other scientific understanding is vital, since the main objective of forest management is productivity and conservation of resources for society’s needs. Implementing advanced remote sensing techniques for many purposes like biophysical parameter estimation, defoliation monitoring, carbon stock management, forest resources distribution mapping, invasive species mapping, and 3D structure measurement will enhance the sustainability of the forest. Moreover, remote sensing also observes climate and environmental changes for predicting and forecasting forest resources more effectively.

For effective forest resources management, new algorithms are being developed in virtual image analysis, which helps in retrieving accurate information from remote sensing. At the same time, advanced remote sensing technologies like airborne laser scanning, terrestrial laser scanning, digital aerial photogrammetry, and very-high-spatial-resolution optical imagery are valuable in analyzing forest inventories. Further, utilizing optical remote sensing technique has some specific challenges due to uncertain weather conditions. Therefore, to overcome this type of uncertain situation, advanced Doppler weather radar can be used along with numerical weather prediction models. Besides, remote sensing methods such as light detection and ranging (LiDAR) gives much more high-resolution images, and Geographic Information System (GIS) provides efficient geospatial information to manage forest inventory. Apart from the above-mentioned remote sensing techniques, recent developments in ground-based sensors also provides detailed information about forest resources, including advanced 3D measurements and community-based monitoring with cost effectiveness. Studies show that deforestation and forest degradation are major causes of greenhouse gas emission, which leads us to create awareness among the general population. As a consequence, certain countries implemented climate change mitigation programs like REDD to reduce emissions from deforestation and forest degradation. Since conserving forest and managing it is very important, integrating remote sensing and its related techniques will be a problem-solving measure for attaining sustainability in forest management.

Specific topics of interest include but are not limited to:

  • Recent advances in remote sensing applications for forest resource management
  • Comparison and evaluation of different remote sensor platforms for assessing forest ecology
  • Efficient real-time image processing for sustainable forestry
  • Remote sensing methods for assessment and monitoring of three-dimensional structure of forest
  • Remote sensing processing techniques in wildfire management
  • Application of remote sensing for tropical deciduous forests
  • Current advances and challenges of remote sensing for ecological balancing
  • Remote sensing techniques for mapping temperate rain forest regions
  • Implementing community-based monitoring for quality and management of natural resources
  • Remote sensing technology-based mitigation programs for deforestation and degradation
  • GIS based effective monitoring system for forest management
  • Remote sensing for monitoring structural and functional forest biodiversity
  • Applications of remote sensing in geoscience
  • LiDAR processing techniques for vegetation characterization

To submit a manuscript for consideration, 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. Peer review will commence immediately upon manuscript submission, with a goal of making a first decision within six weeks of manuscript submission. Special sections are opened online once a minimum of four papers have been accepted. Each paper is published as soon as the copyedited and typeset proofs are approved by the author.

Forest Management
Published Special Sections

Unmanned Systems and Satellites: A Synergy for Added-Value Possibilities (April-June 2022)
Guest Editors: Panagiotis Partsinevelos and Hongbo Su

Coastal Zone Remote Sensing for Environmental Sustainability (January-March 2022)
Guest Editors: Shuisen Chen, Chandrasekar Nainarpandian, and Ayad M. Fadhil Al-Quraishi

Multitemporal Remote Sensing Data Processing and Applications (October-December 2021)
Guest Editors: Liangpei Zhang, Jocelyn Chanussot, Assefa M. Melesse, and Xinghua Li

Satellite Hyperspectral Remote Sensing: Algorithms and Applications (October-December 2021)
Guest Editors: Kun Tan, Xiuping Jia, and Antonio J. Plaza

Satellite Remote Sensing for Disaster Monitoring and Risk Assessment, Management, and Mitigation (July-September 2021)
Guest Editors: Hung Lung Allen Huang and Mitchell Goldberg

Hyperspectral Remote Sensing and Imaging Spectrometer Design (July-September 2021)
Guest Editors: Shen-En Qian, Robert O. Green, and Antonio J. Plaza

Representation Learning and Big Data Analytics for Remote Sensing (July-September 2020)
Guest Editors: Weifeng Liu, Yicong Zhou, Karen Panetta, and Sos Agaian

Instrument Calibration and Product Validation of GOES-R (July-September 2020)
Guest Editors: Xiangqian Wu, Changyong Cao, Satya Kalluri, and Jaime Daniels

Advances in Remote Sensing for Forest Structure and Functions (April-June 2020)
Guest Editors: Lin (Tony) Cao, Yunsheng Wang, and Hao Tang

CubeSats and NanoSats for Remote Sensing (July-September 2019)
Guest Editors: Thomas Pagano and Charles Norton

Advances in Deep Learning for Hyperspectral Image Analysis and Classification (April-June 2019)
Guest Editors: Masoumeh Zareapoor, Jinchang Ren, Huiyu Zhou, and Wankou Yang

Advances in Remote Sensing for Air Quality Management  (October-December 2018)
Guest Editors: Barry Gross, Klaus Schäfer, and Philippe Keckhut

Advances in Agro-Hydrological Remote Sensing for Water Resources Conservation (October-December 2018)
Guest Editors: Antonino Maltese and Christopher M. U. Neale

Optics in Atmospheric Propagation and Adaptive Systems
(October-December 2018)
Guest Editors: Karin U. Stein, Szymon Gladysz, Christian Eisele, Vladimir P. Lukin

Recent Advances in Earth Observation Technologies for Agrometeorology and Agroclimatology (April-June 2018)
Guest Editors: Shi-bo Fang, George P. Petropoulos, and Davide Cammarano

Improved Intercalibration of Earth Observation Data (January-March 2018)
Guest Editors: Craig Coburn and Aaron Gerace

Feature and Deep Learning in Remote Sensing Applications (October-December 2017)
Guest Editors: John E. Ball, Derek T. Anderson, Chee Seng Chan

Recent Advances in Geophysical Sensing of the Ocean: Remote and In Situ Methods (July-September 2017)
Guest Editors: Weilin Hou and Robert Arnone

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

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