Geoscience And Remote Sensing Society Research Articles

Thermal Analysis of AlainSat-1: A 3U Cubesat for Earth Observation

AlainSat-1 is a remote sensing CubeSat carrying earth observation payloads developed by student teams from three international universities. Planned for launch in 2023 it is a direct result from the collaborative effort between the IEEE Geoscience and Remote Sensing Society (GRSS) and the National Space Science and Technology Center (NSSTC) at UAE University. CubeSats are popular among the research and academic communities as a space platform from which to perform related research and academic work connected to space technologies due to their compact size, shorter development time, and relatively low cost. However, because most CubeSats are built using off-the-shelf components, their capacity to resist the harsh environments of space must be proven. Aside from ensuring that structural criteria are met, thermal analysis is critical for ensuring that components or payloads stay functioning in extreme hot or cold environments. The thermal analysis results of AlainSat-1’s finite element model (FEM) functioning under the projected thermal environment associated to its mission are presented in this study. Preliminary results from the analysis using SIEMENS NX show that temperature measurements are within an acceptable range. However, more modification of the simulated environment and FEM in terms of mesh sizes and radiative and conductive thermal couplings is needed before conclusive results may be obtained. The approved simulated results and parameters will be tested experimentally in a Thermal Vacuum Chamber. In addition, challenges identified throughout the analysis and their remedies are discussed.

The IEEE GRSS IDEA Committee: Championing Diversity in Adversity [Women in GRSS

After more than two years of hard lockdowns and restricted mobility, the whole world carefully returns to normalcy. With this, the IEEE Geoscience and Remote Sensing Society (GRSS) Inspire, Develop, Empower, and Advance (IDEA) Committee took the opportunity to attend two conferences in person, continuing its campaign for inclusivity and diversity.

The Third China International Synthetic Aperture Radar Symposium [Conference Reports

From 2 to 4 November 2022, the third China International Synthetic Aperture Radar (SAR) Symposium (CISS), sponsored by the Shanghai Institute of Satellite Engineering, was successfully held at the Jinjiang Metropolo Hotel Minhang, Shanghai. The CISS is an international academic conference with extensive authority, knowledge, and interaction. The symposium aims to build a high-level and international academic communication platform for scholars and researchers in the SAR field, lead the direction of technology development in the SAR field, and promote technology innovation in related fields. CISS 2022 was technically cosponsored by IEEE and the IEEE Geoscience and Remote Sensing Society (GRSS). More than 180 invited experts and scholars from China, Germany, New Zealand, Poland, and other countries assembled to discuss the latest developments and achievements in SAR-related areas, including hardware systems, processing techniques, advanced applications, and so on. CISS 2022 was held online and offline, and more than 150 participants attended offline live events. Nine experts ( <xref ref-type="fig" rid="fig1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Figure 1</xref> ) gave keynotes during the opening ceremony. During the conference, 72 researchers presented their work in oral form, while 94 reports were presented in poster form.

Letter From the President [President’s Message

Hello and nice to meet you! My name is Mariko Burgin and I am the incoming IEEE Geoscience and Remote Sensing Society (GRSS) president. You can reach me at president@ieee-grss.org and @GRSS_President on Twitter.

Strengthening Connections Within GRSS [President’s Message

I believe the past year has been a very important and transformative one for the IEEE Geoscience and Remote Sensing Society (GRSS). The Society continues to expand its influence in several ways, including Society initiatives, membership growth, journal submissions, and outreach. But perhaps the most important transformation has been the many in-person events we have been able to have in 2022 compared with the previous year. Hence, “Connections” is a theme for this column.

To Travel or Not to Travel: The Hybrid Conference Era [President’s Message

This year it is nice to once again be writing the September message having just returned from the annual IEEE Geoscience and Remote Sensing Society (GRSS) flagship conference, the IEEE International Geoscience and Remote Sensing Symposium (IGARSS). IGARSS was held in Kuala Lumpur, Malaysia, at the Kuala Lumpur Conference Center, where we enjoyed a week of technical sessions held both in person and online as well as a full agenda of GRSS social events, the Student Paper Competition (SPC), the Three Minute Thesis (3MT) competition, and a map design contest organized by the IGARSS Local Organizing Committee.

GRSS Community Engagement [President’s Message

On behalf of the IEEE Geoscience and Remote Sensing Society (GRSS), I would like to invite you to participate in IGARSS 2022, our annual International Geoscience and Remote Sensing Symposium. This year’s symposium will be held in Kuala Lumpur, Malaysia, from 17 to 22 July using a hybrid conference format. The theme for this year’s meeting will focus on “Preserving Our Heritage, Enabling Our Future Through Remote Sensing.” The theme was selected by the local organizing team to emphasize the role that remote sensing can play in understanding our past and creating a better future by identifying the issues that most affect Earth’s environment. Please see <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://igarss2022.org/</uri> for more information.

High-Performance and Disruptive Computing in Remote Sensing: HDCRS—A new Working Group of the GRSS Earth Science Informatics Technical Committee [Technical Committees

The High-Performance and Disruptive Computing in Remote Sensing (HDCRS) Working Group (WG) was recently established under the IEEE Geoscience and Remote Sensing Society (GRSS) Earth Science Informatics (ESI) Technical Committee to connect a community of interdisciplinary researchers in remote sensing (RS) who specialize in advanced computing technologies, parallel programming models, and scalable algorithms. HDCRS focuses on three major research topics in the context of RS: 1) supercomputing and distributed computing, 2) specialized hardware computing, and 3) quantum computing (QC). This article presents these computing technologies as they play a major role for the development of RS applications. The HDCRS disseminates information and knowledge through educational events and publication activities which will also be introduced in this article.

Preparation for Success in 2022 [President’s Message

Looking back to my last letter from 2021, I found that I spent most of it recapping 2021 events but not much time describing preparations for 2022. Therefore, this letter may be a continuation from December. First of all, I would like to welcome our new Administrative Committee (AdCom) members beginning three-year terms starting in 2022: Ronny Haensch, chair of the 2021 IEEE Geoscience and Remote Sensing Society (GRSS) Data Fusion Contest and current GRSS e-newsletter editor; Keely Roth, current GRSS publicity and public relations chair; and Mengdao Xing, who has been very active with the GRSS in China. Also returning for another three-year term are Paul Rosen, chair of GRSS Global Activities, and Alejandro Frery, chair of the GRSS Future Publications Committee. I would also like to thank the AdCom for allowing me to serve a second one-year term as president for 2022.

The Birth of the IEEE Geoscience and Remote Sensing Society in Cameroon: The Quest for a Chapter [Chapters

The IEEE Geoscience and Remote Sensing Society (GRSS) is encouraging the establishment of more African Chapters and more activities in Africa. This led to the initiation of a meeting of the local GRSS Cameroon Chapter, a community that is young and vibrant. On 19 August 2021, the local Cameroon Chapter organized its first webinar, “Achieving Success by Belonging” (see <xref ref-type="fig" rid="fig1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Figure 1</xref> ). The objective of the webinar was to officially launch the activities of the local Cameroon Chapter, raise awareness of benefits of the GRSS to members and nonmembers, and encourage more people to join this incredible Society.

IEEE GRSS Mato Grosso do Sul (Brazil) Student Branch Chapter: 2020 Activities [Chapters

The Federal University of Mato Grosso do Sul (UFMS) IEEE Geoscience and Remote Sensing Society (GRSS) Student Branch Chapter, also known as MS GRSS IEEE Student Chapter, is located in Mato Grosso do Sul State, Brazil. The Chapter represents a partnership of students and researchers from two labs: the Geomatics Lab at UFMS and the Inovisão Lab at Catholic Dom Bosco University (UCDB). The advisors are Prof. José Marcato Junior and Prof. Hemerson Pistori. The 2020 administrative organization is presented in <xref ref-type="fig" rid="fig1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Figure 1</xref> .

2021 IEEE GRSS Turkey Chapter Activities [Chapters

The IEEE Geoscience and Remote Sensing Society (GRSS) Turkey Chapter was established in 2012 to address the increasing number of researchers in the remote sensing field in both academia and industry, organize events and meetings for these researchers in Turkey, and provide a basis for establishing and improving collaboration and cooperation between industry, institutions, and universities in the fields of geoscience and remote sensing. There are currently 23 active Chapter members, including one associate, seven graduate student members, 11 members, and five senior members.

Activities of the GRSS Universidad Distrital Francisco José de Caldas Colombia Student Chapter [Chapters

The IEEE Geoscience and Remote Sensing Society (GRSS) Universidad Distrital Francisco José de Caldas (Bogotá, Colombia) Student Chapter was founded in 2008, but its activities were intermittent. The Chapter was reactivated in 2016, after more than three years of cessation, with the direction of Eric Gutierrez (president) and Stiven Gomez (vice president) and under the advice of Erika Upegui. The GRSS Student Chapter belongs to the Faculty of Engineering, and most of the students are in the Cadastral Engineering and Geodesy undergraduate program. The Chapter’s early chairs were Eric Gutierrez (2016), Laura Martin (2017), Cristian Salas (2018), Michael Rivera (2019), and Sergio Castellanos (2020). The Chapter has 24 participants as follows: 10 members, 10 volunteers, and four support teachers (Andrés Cardenas, Germán Ramirez, Luis Castillo, and Javier Medina).

The IEEE GRSS Brazil Chapter: 2020 Activities [Chapters

The IEEE Geoscience and Remote Sensing Society (GRSS) Brazil Chapter comprises 49 professionals and 57 student members, totaling 106 members in 2020. The following Chapter officers performed services during 2020

CCANet: Class-Constraint Coarse-to-Fine Attentional Deep Network for Subdecimeter Aerial Image Semantic Segmentation

Semantic segmentation is important for the understanding of subdecimeter aerial images. In recent years, deep convolutional neural networks (DCNNs) have been used widely for semantic segmentation in the field of remote sensing. However, because of the highly complex subdecimeter resolution of aerial images, inseparability often occurs among some geographic entities of interest in the spectral domain. In addition, the semantic segmentation methods based on DCNNs mostly obtain context information using extra information within the added receptive field. However, the context information obtained this way is not explicit. We propose a novel class-constraint coarse-to-fine attentional (CCA) deep network, which enables the formation of class information constraints to obtain explicit long-range context information. Further, the performance of subdecimeter aerial image semantic segmentation can be improved, particularly for fine-structured geographic entities. Based on coarse-to-fine technology, we obtained a coarse segmentation result and constructed an image class feature library. We propose the use of the attention mechanism to obtain strong class-constrained features. Consequently, pixels of different geographic entities can adaptively match the corresponding categories in the class feature library. Additionally, we employed a novel loss function, CCA-loss to realize end-to-end training. The experimental results obtained using two popular open benchmarks, International Society for Photogrammetry and Remote Sensing (ISPRS) 2-D semantic labeling Vaihingen data set and Institute of Electrical and Electronics Engineers (IEEE) Geoscience and Remote Sensing Society (GRSS) Data Fusion Contest Zeebrugge data set, validated the effectiveness and superiority of our proposed model. The proposed method achieved state-of-the-art performance on the IEEE GRSS Data Fusion Contest Zeebrugge data set.

GRSS Accomplishments in 2021: Success and Unexpected Turns [President’s Message

In this last message of the year, I think it is important to summarize accomplishments of the Society in 2021 and describe our preparations for success in 2022. By the numbers, our Society continues to grow. We added two student branch Chapters in September with another one expected in November. When this one receives its final approval, the IEEE Geoscience and Remote Sensing Society (GRSS) community will total 70 Chapters, 28 student branch Chapters, and 10 ambassadors engaged with communities in locations where we hope GRSS Chapters will form in the near future. This means that the GRSS community now consists of 98 combined Chapters with membership in the Society surpassing 5,300 members and submissions to our journals surpassing expectations. The numbers confirm continued success for GRSS in 2021, but this year also brought some unexpected twists and turns with high expectations at the beginning to immediately resume in-person meetings.

The Women in Engineering International Leadership Conference [Women in GRSS

As in previous years, the IEEE Geoscience and Remote Sensing Society (GRSS) Inspire, Develop, Empower, Advance (IDEA) Committee spent much of the spring getting prepared to host some exciting events at the International Geoscience and Remote Sensing Symposium (IGARSS). This year was no different, although uncertainty hung in the air as we awaited decisions on whether the largest annual GRSS event would be a hybrid or virtual one. Alas, the COVID-19 Delta variant swept across the globe in what was for many the fifth or sixth wave of coronavirus cases in the global pandemic, and IGARSS moved to all virtual.

IGARSS 2021 High School Program Green in the City [Education

Supported by the IEEE Geoscience and Remote Sensing Society (GRSS) High School and Undergrad Student Outreach Program (HSUSO), the educational chairs of the 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS 2021 developed a remote sensing school project targeting 16- and 17-year-old pupils in the third grade of secondary education in Flanders, Belgium. HSUSO was led by Dr. Linda Bailey Hayden and Dr. Josée Lévesque. The Green in the City project focused on the role of urban green in cities. Using dedicated course materials, including knowledge clips, manuals and tutorials, and data sets for several Belgian cities, the project offered hands-on training in basic remote sensing and geographic information system (GIS) skills. By exploring spectral reflectance properties of different materials, participating students learned how to map urban green from satellite data and analyze the relation between urban green and other environmental and socioeconomic variables at the intra-urban scale. The project reached more than 500 students from 20 schools. Given the success of the project, plans to roll out an international version of the program are in the pipeline.

IEEE PROJECT 4001 – STANDARDS FOR CHARACTERIZATION AND CALIBRATION OF HYPERSPECTRAL IMAGING DEVICES

Abstract. Hyperspectral imaging (HSI) systems have been invaluable tools for over two decades, but there are few authoritative standards that characterize these systems or define the data and metadata they produce. Manufacturers calibrate instruments and report specifications differently and, in some cases, the same term has different definitions among HSI programs.To address these inconsistencies, the Institute of Electrical and Electronics Engineers (IEEE) Geoscience and Remote Sensing Society (GRSS) sponsored Project 4001 (P4001), a Hyperspectral Working Group under the auspices of IEEE’s Standards Association. Since its inception in 2018, the IEEE P4001 Working Group has been working to specify testing and characterization methods for HSI device manufacturers, as well as recommend data structures and terminology for HSI products.P4001 focuses on the ultraviolet through the shortwave infrared spectral range (~250 to 2500 nm) and prioritizes camera technologies that are in widespread use. Many aspects of the standard will have wider applicability with respect to camera technology and wavelength range, and updates will expand the range of technologies and topics covered. Industrial, laboratory and geoscience use cases are informing the development of the standard. Utilization of the P4001 HSI standard will lead to HSI systems with consistent characterization and calibration criteria, as well as interoperable data products with a common lexicon for data and metadata.

Classification of Airborne Laser Scanning Point Cloud Using Point-Based Convolutional Neural Network

In various applications of airborne laser scanning (ALS), the classification of the point cloud is a basic and key step. It requires assigning category labels to each point, such as ground, building or vegetation. Convolutional neural networks have achieved great success in image classification and semantic segmentation, but they cannot be directly applied to point cloud classification because of the disordered and unstructured characteristics of point clouds. In this paper, we design a novel convolution operator to extract local features directly from unstructured points. Based on this convolution operator, we define the convolution layer, construct a convolution neural network to learn multi-level features from the point cloud, and obtain the category label of each point in an end-to-end manner. The proposed method is evaluated on two ALS datasets: the International Society for Photogrammetry and Remote Sensing (ISPRS) Vaihingen 3D Labeling benchmark and the 2019 IEEE Geoscience and Remote Sensing Society (GRSS) Data Fusion Contest (DFC) 3D dataset. The results show that our method achieves state-of-the-art performance for ALS point cloud classification, especially for the larger dataset DFC: we get an overall accuracy of 97.74% and a mean intersection over union (mIoU) of 0.9202, ranking in first place on the contest website.