Welcome from the Chair
Welcome from the Chair of the 3rd International Electronic Conference on Remote Sensing
22 March to April 2019
22 May to 5 June 2019
It is a great pleasure to welcome you to the 3rd International Electronic Conference on Remote Sensing (ECRS-3). ECRS-3 aims at promoting and facilitating the research and development of remote sensing and serving social and environmental sustainability.
Nowadays, increasing number of remote sensing platforms and sensors can provide more detailed information to measure and monitor changes in the earth’s surface and atmosphere. Remote sensing has been playing a more important role in addressing various global issues related to environmental monitoring, disaster management, national security, agriculture, forestry, natural ecosystems, etc. Related technology can suggest effective and efficient solution for all these issues involved in every aspect from global to nation and nation to individuals. Particularly, with the rapid development of spatial information acquisition system and progress in data transmission and reception system, many new sensors suitable for a large variety of different applications are significantly expanding the boundary of remote sensing discipline. The technical innovations in artificial intelligence, machine learning, and image processing are expected to further promote the analysis and understanding of remote sensing data at the same time. All these boosting things indicate that remote sensing technology is facing a major development opportunity.
ECRS-3 will include the following themes covering the key areas of remote sensing sciences:
- Remote Sensing Data Enhancement
- Remote Sensing Data Understanding
- Deep Learning Based Remote Sensing
- Remote Sensing Data and Code
- New Devices and Platforms for Remote Sensing
We sincerely welcome you to take part in this conference to exchange and share ideas and experiences, discuss the latest developments, and identify future trends for remote sensing techniques and applications in these and related areas. We hope we can move forward the development of remote sensing in theory and application together.
The 3rd International Electronic Conference on Remote Sensing will be held at https://sciforum.net/conference/ecrs-3, the platform developed by MDPI to organize electronic conferences and discussion groups.
Accepted papers will be published in the proceedings of the conference, and selected papers will be considered for publication in Remote Sensing, which is an open access journal publication of MDPI in the field of remote sensing
We are looking forward to receiving your contributions to this scientific event and would like to thank you in advance for your active support.
Dr. Qi Wang
Center for OPTical IMagery Analysis and Learning (OPTIMAL)
Northwestern Polytechnical University, China
Call for papers
e-conferences, virtually anywhere
3rd International Electronic Conference on Remote Sensing
The 3rd International Electronic Conference on Remote Sensing will be held from 22 March to 5 April 2019 in the internet environment. This event will solely be an online proceeding which allows the participation from all over the world with no concerns of travel and related expenditures, while at the same time making rapid and direct exchanges about the latest research findings and novel ideas in remote sensing. All proceedings will be held online at https://sciforum.net/conference/ecrs-3 and in Journal Proceedings.
The conference aims to bring the scientists working in the field onto Remote Sensing Image Processing along the following main themes:
- Remote Sensing Data Enhancement (Session A)
- Remote Sensing Data Understanding (Session B)
- Deep Learning Based Remote Sensing (Session C)
- Remote Sensing Data and Code (Session D)
- New Devices and Platforms for Remote Sensing (Session E)
- Posters: In this session, posters can be presented without an accompanying proceedings paper. Posters will be available online on this website during and after the e-conference. However, will not be added to the proceedings of the conference.
The conference will be completely free of charge—both to attend, and for scholars to upload and present their latest work on the conference platform. There will be a possibility to submit selected papers to the e-conference related Special Issue of the journal Remote Sensing (ISSN 2072-4292; 3.406 (2017); 5-Year Impact Factor: 3.952 (2017); http://www.mdpi.com/journal/remotesensing) with a 20% discount on the APCs. ECRS-3 offers you the opportunity to participate in this international, scholarly conference without having the concern or expenditure of travel — all you need is your computer and access to the Internet. We would like to invite you to “attend” this conference by presenting your latest work. You will be able to present your work in the form of your proceedings paper, optionally you may also contribute a (video) presentation.
Abstracts (in English) should be submitted by 17 December 2018 online at http://www.sciforum.net/login. For accepted abstracts, the proceedings paper can be submitted by 10 February 2019. The conference itself will be held 22 March-5 April 2019.
We hope you will be able to join this exciting event and support us in making it a success. ECRS 2019 is organized and sponsored by MDPI, a scholarly open access publisher based in Basel, Switzerland.
- Deadline for Abstract Submission: 17 December 2018 17 February 2019
- Notification of Acceptance: 20 December 2018 20 February 2019
- Deadline for Submission of Conference Proceedings Papers/Posters: 10 February 2019 10 April 2019
- Conference Open: 22 March- 4 April 2019 22 May-4 June 2019
Paper Submission Guidelines
For information about the procedure for submission, peer-review, revision and acceptance of conference proceedings papers, please refer to the section "Instructions for Authors": https://sciforum.net/conference/ecrs-3/page/instructions.
Dr. Qi Wang
Center for OPTical IMagery Analysis and Learning (OPTIMAL), Northwestern Polytechnical University
Qi Wang received the B.E. degree in automation and Ph.D. degree in pattern recognition and intelligent system from the University of Science and Technology of China (USTC), Hefei, China, in 2005 and 2010 respectively. He was a post-doctor in Xi'an Institute of Optics and Precision Mechanics of CAS from 2011 to 2013. Then he joined in the Center for OPTical IMagery Analysis and Learning (OPTIMAL), Northwestern Polytechnical University, Xi’an, China in 2014, where he is currently a professor. His research interests include remote sensing, computer vision, and machine learning. Qi has published about 80+ papers in top journals and conferences, including T-NNLS、T-GRS、T-CYB、T-CSVT、T-ITS、PR、CVIU、 AAAI、IJCAI、 ICASSP、 ICRA、 ICME and won the IEEE conference best paper award and best paper candidate award. He is a regular reviewer for 40+ distinguished journals and has served as a PC/SPC member for 100+ international conferences and organizing committee member/program co-chair/session chair for many international conferences. He is the assoc
Professor Kevin Tansey
GIS & Remote Sensing Group
Dept. of Geography
University of Leicester, UK
Professor Daniele Riccio
Department of Electrical Engineering and Information Technology
Faculty of Engineering
University of Napoli Federico II, Napoli, Italy
Dr. Francesco Nex
Department of Earth Observation Science (EOS)
ITC Faculty, University of Twente PO Box 217
7500 AE, Enschede, The Netherlands
Department of Earth Observation Science (EOS) ITC Faculty, University of Twente PO Box 217 7500 AE, Enschede, The Netherlands
Instructions for Authors
- Scholars interested in participating with the conference can submit their abstract (about 200-300 words covering the areas of manuscripts for the proceedings issue) online on this website until 17 December 2018.
- The Conference Committee will pre-evaluate, based on the submitted abstract, whether a contribution from the authors of the abstract will be welcome for the 3rd International Electronic Conference on Remote Sensing. All authors will be notified by 20 December 2018 about the acceptance of their abstract.
- If the abstract is accepted for this conference, the author is asked to submit his/her manuscript, optionally along with a PowerPoint and/or video presentation of his/her paper (only PDF), until the submission deadline of 10 February 2019.
- The manuscripts and presentations will be available on https://sciforum.net/conference/ecrs-3 for discussion and rating during the time of the conference 22 March-5 April 2019 and will be published in Journal Proceedings. Accepted papers will be published in the proceedings of the conference itself.
- The Open Access Journal Remote Sensing will publish a Special Issue of the conference proceedings papers. After the conference, the Conference Committee will recommend manuscripts that may be included for publication in this Special Issue of the journal Remote Sensing (the submission to the journal is independent from the conference proceedings and will follow the usual process of the journal, including peer-review, APC, etc.). It means an extended version submitted to Remote Sensing is welcomed after the full paper accepted by the session chair.
Manuscripts for the proceedings issue must have the following organization:
- Full author names
- Affiliations (including full postal address) and authors' e-mail addresses
- Results and Discussion
Manuscripts should be prepared in MS Word or any other word processor and should be converted to the PDF format before submission. The publication format will be PDF. The manuscript should count at least 3 pages (incl. figures, tables and references) and should not exceed 6 pages.
Authors are encouraged to prepare a presentation in PowerPoint or similar software, to be displayed online along with the Manuscript. Slides, if available, will be displayed directly in the website using Sciforum.net's proprietary slides viewer. Slides can be prepared in exactly the same way as for any traditional conference where research results can be presented. Slides should be converted to the PDF format before submission so that our process can easily and automatically convert them for online displaying.
Besides their active participation within the forum, authors are also encouraged to submit video presentations. If you are interested in submitting, please contact the conference organizer at [email protected] to get to know more about the procedure. This is an unique way of presenting your paper and discuss it with peers from all over the world. Make a difference and join us for this project!
Authors that wish to present a poster only, i.e. without proceedings paper, can do so in section H - Posters of this conference. Posters will be available on this conference website during and after the event. Like papers presented on the conference, participants will be able to ask questions and make comments about the posters. Posters that are submitted without paper will not be included in the proceedings of the conference.
Submission: Manuscripts should be submitted online at www.sciforum.net/login by registering and logging in to this website.
- MS Word: Manuscript prepared in MS Word must be converted into a single file before submission. When preparing manuscripts in MS Word, the Electronic Conference on Remote Sensing Microsoft Word template file (see download below) must be used. Please do not insert any graphics (schemes, figures, etc.) into a movable frame which can superimpose the text and make the layout very difficult.
- Accepted File Formats
- Paper Format: A4 paper format, the printing area is 17.5 cm x 26.2 cm. The margins should be 1.75 cm on each side of the paper (top, bottom, left, and right sides).
- Paper Length: The conference proceedings paper should not be longer than 6 pages. The conference manuscript should be as concise as possible.
- Formatting / Style: The paper style of the Journal Remote Sensing should be followed. You may download the template file to prepare your paper. The full titles and the cited papers must be given. Reference numbers should be placed in square brackets [ ], and placed before the punctuation; for example  or [1-3], and all the references should be listed separately and as the last section at the end of the manuscript.
- Authors List and Affiliation Format: Authors' full first and last names must be given. Abbreviated middle name can be added. For papers written by various contributors a corresponding author must be designated. The PubMed/MEDLINE format is used for affiliations: complete street address information including city, zip code, state/province, country, and email address should be added. All authors who contributed significantly to the manuscript (including writing a section) should be listed on the first page of the manuscript, below the title of the article. Other parties, who provided only minor contributions, should be listed under Acknowledgments only. A minor contribution might be a discussion with the author, reading through the draft of the manuscript, or performing English corrections.
- Figures, Schemes and Tables: Authors are encouraged to prepare figures and schemes in color. Full color graphics will be published free of charge. Figure and schemes must be numbered (Figure 1, Scheme I, Figure 2, Scheme II, etc.) and a explanatory title must be added. Tables should be inserted into the main text, and numbers and titles for all tables supplied. All table columns should have an explanatory heading. Please supply legends for all figures, schemes and tables. The legends should be prepared as a separate paragraph of the main text and placed in the main text before a table, a figure or a scheme.
For further enquiries please contact us at [email protected].
It is the authors' responsibility to identify and declare any personal circumstances or interests that may be perceived as inappropriately influencing the representation or interpretation of clinical research. If there is no conflict, please state here "The authors declare no conflict of interest." This should be conveyed in a separate "Conflict of Interest" statement preceding the "Acknowledgments" and "References" sections at the end of the manuscript. Financial support for the study must be fully disclosed under "Acknowledgments" section. It is the authors' responsibility to identify and declare any personal circumstances or interests that may be perceived as inappropriately influencing the representation or interpretation of clinical research. If there is no conflict, please state here "The authors declare no conflict of interest." This should be conveyed in a separate "Conflict of Interest" statement preceding the "Acknowledgments" and "References" sections at the end of the manuscript. Financial support for the study must be fully disclosed under "Acknowledgments" section.Copyright
MDPI, the publisher of the Sciforum.net platform, is an open access publisher. We believe that authors should retain the copyright to their scholarly works. Hence, by submitting a Communication paper to this conference, you retain the copyright of your paper, but you grant MDPI the non-exclusive right to publish this paper online on the Sciforum.net platform. This means you can easily submit your paper to any scientific journal at a later stage and transfer the copyright to its publisher (if required by that publisher).
List of accepted submissions (14)
|NO2 Observations from the Sentinel-5P Tropomi - Turkey||Gordana Kaplan Zehra Yigit Avdan Ugur Avdan||
With the rapid population growth, both urbanization and transportation affect the air pollution, population health, and global warming. A number of air pollutants are released from industrial facilities and other activities and may cause adverse effects on human health and the environment. One of the biggest air pollutant, nitrogen dioxide (NO2), is mainly caused as combustion of fossil fuels, and especially from traffic exhaust gases. Over the years, air pollution has been monitored using satellite remote sensing data. In this study, we investigate the relation of the tropospheric NO2 retrieved from the recently launched Sentinel-5 Precursor, a low earth orbit atmosphere mission, dedicated for monitoring air pollution equipped with a spectrometer Tropomoi (TROPOspheric Monitoring Instrument), and the population density over Turkey. For this purpose, we use the mean value of NO2 collected from July 2018 to January 2019, and the statistic population data from 2017. The results showed significant correlation higher than 0.72 between the population density and the maximum NO2 values. For future studies, we recommend investigating the correlation of different air pollutants with population, and other factors contributing to air and environmental pollution.
|Comparison of Proximal Remote Sensing Devices for Estimating Eggplant response to Root-Knot Nematodes||Alex Silva-Sánchez Julia Buil-Salafranca Andrea Casadesús Cabral Naroa Uriz-Ezcaray Helio García-Mendívil Francisco Sorribas José Araus Adrian Gracia-Romero||
Proximal remote sensing devices are becoming widely applied in field plant research to estimate biochemical (e.g. pigments or nitrogen) or agronomical (e.g. leaf area, biomass or yield) parameters as indicators of stress. Non-invasive characterization of plant responses allows screening larger populations faster than the conventional procedures that, besides being time-consuming, also implies the destruction of material or is subjective (e.g. visual ranking). This study deals with the comparison of a set of remote sensing devices at single-leaf and whole-canopy levels based on their performance in assessing how the eggplant and its yield respond to crafting as a way to tolerate root-knot nematodes. The results showed that whole-canopy measurements, as the Green Area (GA) derived from the RGB images (r=0.706 and p-value=0.001**) or the canopy temperature (r=-0.619 and p-value=0.005**), outperformed the single-leaf measurements, as the leaf chlorophyll content measured by the Dualex (r=0.422 and p-value=0.059) assessing yield. Moreover, other parameters as the time required to measure each sample or the cost of the sensors were taken into account in the discussion. Everything considered, indexes derived from the RGB images have demonstrated their robust potential for the assessment of crop status, being a low-cost alternative to other more expensive and time-consuming devices.
Probability estimation of change maps using spectral similarity
|Hamid Jafarzadeh Mahdi Hasanlou||N/A||
Change detection (CD), which is a process of identifying changes occurred in a geographical area over the time, plays a key role in many applications including assessing natural disasters, monitoring crops, and managing water resources. In the past decades many CD (both binary and multiple) techniques have been proposed. Hence, evaluating and analyzing of probability of changes and interpreting them, is essential task which leads to better management of natural resources and preventing disasters. For this purpose, we adopted an approach to visualize probability of occurring detected changes. Based on this approach, change pixels will be categorized and labeled as probabilities (in percentage). In this paper, the proposed framework consists of the following three steps. Firstly, this research produces binary change maps from methods have been proposed in the literature. Then spectral similarity of pixels is calculated in abundances map (of endmembers) domain. A measurement of spectral similarity identifies the finer spectral differences between the two hyperspectral images (HSIs). Finally, combining binary map and spectral similarity values resulting change multiple probability map. The experimental results show that the method has a good result, and can be widely used in hyperspectral CD applications.
|Evaluating Sentinel-2 Red-Edge Bands for Wetland Classification||Gordana Kaplan Ugur Avdan||
Due to the high spatial heterogeneity and temporal variability, wetlands are one of the most difficult ecosystems to observe using remote sensing data. With the additional Sentinel-2 vegetation red-edge bands, an improvement of the vegetated classes classification is expected. In order to investigate the influence of the Sentinel-2 red-edge bands, in this paper, we use one Sentinel-2 satellite image acquired in the summer period, in August, and we evaluate two classification scenarios over wetland classes. As a study area, the Central Anatolian region in Turkey has been selected. The first scenario excludes the red-edge bands, while in the second scenario are included all red-edge bands in the classification dataset where two different wetland classes, intensive vegetated wetland classes such as swamps and partially decayed vegetated wetland areas such as bogs, have been classified using Support Vector Machines (SVMs) learning classifier. The classes were defined using high-resolution images from Unmanned Aerial Vehicle (UAV) obtained on the same date with the overpass of the Sentinel-2 satellite over the study area. As expected, the results showed significant improvement of the intensive vegetated wetlands, with more than 30% in both user and producer accuracy, while no significant changes have been noticed in the partially decayed vegetated wetlands. For future studies, we recommend evaluating the influence of the Sentinel radar data over wetland areas.
|PolInSAR coherence based decomposition for scattering characterization of urban area||Awinash Singh Shashi Kumar Kavita Jhajharia||N/A||
Polarimetric SAR data based scattering retrieval has been widely used to characterize manmade and natural features. It has been found that PolSAR data has the capability to retrieve scattering information contributed by different features within a small area or single resolution cell. Generally, it has been found that the urban structures are contributing the high double-bounce scattering, but due to closely spaced urban structure, multiple reflections of the SAR waves from the walls of the buildings give the appearance of the volume scattering. The overestimation of volume scattering from urban structure could be reduced by the adoption of interferometric coherence in decomposition modeling. The PolInSAR coherence constitutes the full collection of polarimetric and interferometric information. The urban buildings are considered as permanent scatterers which is usually not affected by the temporal and volume decorrelation. Therefore, they show high coherence magnitudes. The prime focus of this research was the implementation of PolInSAR coherence in the decomposition modeling to minimize the overestimation of volume scattering from the urban structure. This study has used the CoSSC product of the TanDEM-X mission. The PolInSAR data over Dehradun, India were acquired in bistatic mode. All the possible combinations of PolInSAR coherence were generated from TerraSAR-X and TanDEM-X. The Pauli basis based PolInSAR coherence has shown the capability to distinguish different features according to their nature. To find the appropriate coherence for decomposition modeling the optimization was performed on PolInSAR data to select the optimal coherence. The results obtained from PolInSAR coherence based decomposition modeling had shown the dominance of double bounce scattering in the urban area for closely spaced structures also. The study strongly recommends the use of PolInSAR coherence in the decomposition modelling to minimize the ambiguity in the scattering retrieval from an urban area due to close spaced buildings.
Program & Schedule
Deadline for Abstract Submission: 17 December 2018 17 February 2019
Notification of Acceptance: 20 December 2018 20 February 2019 28 February 2019
Deadline for Submission of Conference Proceedings Papers/Posters: 10 February 2019 10 April 2019
Conference Open: 22 March- 4 April 2019 22 May-4 June 2019
A. Remote sensing data enhancement
Professor Vincent Ambrosia, Senior Research Scientist / Adjunct Faculty California State University - Monterey Bay co-located at: NASA-Ames Research Center
B. Remote sensing data understanding
Dr. Igor Savin, V.V. Dokuchaev Soil Science Institute Agrarian-Technological Institute of RUDN University
Professor Daniele Riccio, Department of Electrical Engineering and Information Technology Faculty of Engineering, University of Napoli Federico II, Napoli, Italy
C. Deep learning based remote sensing
Dr. Dimitris Stavrakoudis, PhD Electrical and Computer Engineer Laboratory of Forest Management and Remote Sensing Department of Forestry and Natural Environment Aristotle University of Thessaloniki 59 Mouschounti str., 55134, Thessaloniki, Greece
D. Remote sensing data and code
Professor Gui-Song Xia, State Key Lab. LIESMARS Wuhan University No.129, Luoyu Road, Wuhan 430079, China
E. New Devices and Platforms for Remote Sensing
The remote sensing community today can rely on a multitude of sensors in space and many new ones to come. They cover large parts of the electromagnetic spectrum from optical via thermal to microwave and comprise active and passive sensors. Furthermore, they offer very high-resolution imagery in the decimeter domain up to global coverages with pixel sizes of many square kilometers.
Every year, new missions are announced and launched from international agencies like ESA, NASA, NASDA, national organizations, and private companies. Data may be accessible free of charge or may be purchased, and the same is true for downstream services (e.g., in the framework of the European Copernicus program), national initiatives, or even public apps for mobile phone customers. Nevertheless, many challenges remain, for instance, regarding radiometric quality, revisit and coverage, data latency, etc.
Accordingly, the session on "New Devices and Platforms for Remote Sensing" aims to provide an overview of what new remote sensing sensors and missions are on the horizon; what scientific, public, and commercial customers can expect in the years to come; and how new data from these missions will be made available either via commercial or public access.
Professor Steffen Kuntz, University of Freiburg Albert-Ludwigs-Universität Freiburg Institute of Forest Economy
Professor Ioannis Gitas, Laboratory of Forest Management and Remote Sensing School of Forestry and Natural Environment Aristotle University of Thessaloniki, Greece