Keynote Speaker

Professor Dr Mengu Cho
Kyushu Institute of Technology (Kyutech), Japan

Biography

Mengu Cho received the B.S. and M.S. degrees from the Department of Aeronautics, University of Tokyo, Tokyo, Japan, in 1985 and 1987, respectively, and the P.hD. degree from the Department of Aero/Astro, Massachusetts Institute of Technology, USA, in 1992. From 1992 to 1995, he was a research associate with Kobe University, Kobe, Japan. From 1995 to 1996, he was a Teaching Associates with International Space University, France. Since 1996, he had been with Kyushu Institute of Technology (KIT), Japan, where he was an Assistant Professor in 1996 and Associate Professor in 1997. Since 2004, He has been a Professor and also the Director of the Laboratory of Spacecraft Environment Interaction Engineering (LaSEINE) of KIT. He has been with the Department of Applied Science for Integrated system engineering since 2010. His research interest includes spacecraft environmental interaction, especially spacecraft charging and nano-satellite reliability. He has authored or co-authored more than 120 papers in peer-reviewed journals.

Abstract

Title: CubeSat Interface Standardization for Fast Delivery and Mass Production

It has been said that the advantage of CubeSat is low-cost and fast-delivery. In fact, many CubeSat projects, however, are taking longer than two years since the project kick-off to the launch. There are various CubeSat component vendors available worldwide. The electrical interfaces from different vendors are often not compatible, even if they follow PC-104 specification. The incompatibility leads to additional time in the satellite development, assembly and integration. It may even require an interface board or harness to absorb the difference, adding extra complexity to the system. Clear definition of the electrical interfaces, such as the connector type and pin assignment help shortening the satellite delivery time. As CubeSat is now entering the era of mass production, simple interface suitable for mass production is also desired.

As CubeSat development and utilization proliferate and space start-ups based on CubeSat manufacturing and applications are born worldwide, international standards to promote the CubeSat sectors are desired. In general, when an industry grows to a certain size, soon some kinds of the standard become necessary to promote the growth further. In the past two years, three new ISO standards related to CubeSats are born, ISO-17770 (CubeSat), ISO-19683 (Testing), ISO/TS-20991 (Requirements). An IAA Study (SG4.18) was also done to define small satellites, leading to the new definition of “Lean Satellite”, which also applies to most of the CubeSat projects. The community who worked on the standard have identified a standard related to the interface is suitable as the next target of standardization. A new project to standardize the CubeSat electrical interface has been started with the funding support of the Japanese government. The project will be led by Kyushu Institute of Technology (Kyutech) based on its heritage of leading the standard activities. In the presentation, the overall project outline including the target and the timelines will be presented.

Professor Sr Dr Mazlan Hashim
Research Institute of Sustainable Environment, Universiti Teknologi Malaysia (UTM)

Biography

Prof. Sr Dr Mazlan Hashim is an expert in remote sensing technology applications within the natural resources management, environmental management, conservation and in mapping various national strategic applications.  His research interest is in the rigorous development and innovation of diverse satellite remote sensing and geospatial applications for natural resources and environmental management, including in tropical ecology and biodiversity.  He has led several national and international collaborative studies as Principal Investigator in remote sensing and geospatial technology applications, with a total accumulative of RM 33.9 million from national, international and contract research grants. He has published his research works in more than 250 indexed publications with h-index of 25, 1832 citations (Web-of-Science) and has 5 patents –granted, filed and disclosed.

He serves as an Editorial Board member for various international journals such as Scientific Reports; International Journal of Digital Earth; International Journal of Image and Data Fusion; International Journal of Geoinformatics; and Malaysian Journal of Remote Sensing & GIS.

He received various awards at both national and international levels for his outstanding R&D&I in the field of geospatial sciences and its applications.  Amongst others, he is one of the recipients of the Eduard Dolezal award 1996 by International Society of Photogrammetry and Remote Sensing (ISPRS), Eco-fellow Frontier award 2003 by Global Research Fund and Ministry of Environment, Japan and Top Research Scientists Malaysia 2016 by Academy of Sciences Malaysia. Conferred as Fellow of Academy of Sciences Malaysia in May 2018.

Currently, Prof Mazlan Hashim is the Senior Director of Research Institute of Sustainable Environment, Universiti Teknologi Malaysia (UTM).  He held several positions as Visiting Professor/Scientist at Arabian Gulf University (2015); Tokyo Metropolitan University, Japan (2011-2019); Univ. of Cambridge, United Kingdom (2010); National Institute for Environmental Studies, Japan (2002- 2004), Peking University, China (1990); and Tohoku University, Japan (1989).

Prof Mazlan Hashim is continuously inspiring young researchers to impactful research, putting scientific findings to actions, humanizing it to benefit related industry and society, apart from contributions to new knowledge. He has successfully supervised as the main supervisor for 16 completed PhD and 36 M. Sc (full research), respectively.

Abstract

Title: Prospects of Earth Observation Systems for Sustainable Development Goals (SDGs)

The United Nations provides 17 Sustainable Development Goals (SDGs), as a new global policy for guiding the method countries together transform and manage their economic, social, and environment. The pattern of people as well as the planet for the next 15 years (2030 agenda). Attaining these goals presents the entire nations and the world-wide policy community through a set of essential development challenges, which are almost generally geographic. Several of these issues impacting on sustainable development could be examined, modelled, and mapped in a geographic context using Earth Observations (EO) as a prospect to SDGs.  Employing the EO technology offer the integrative framework essential for consensus, global collaboration, and evidence-based decision-making. Although, despite the significant advancement in EO systems, there are still gaps such as lacking awareness, comprehending and acceptance, specifically at the level of decision-making, the critical and integrative role of EOs and related technologies. This presentation highlights the role of EOs in contributing to SDGs, as it is not sufficiently been explained by the policy practice of sustainable development or by the EOs professional bodies. The global EOs community has an exclusive opportunity to integrate geospatial information to the global developmental agenda. Precisely in contributing data resources on monitoring and measuring the potentials out of the 17 SDGs, and 169 related targets, via the world-wide indicator framework, which supports the 2030 Agenda on Sustainable Development. In addition, this presentation reviews some case studies of EOs that if used by stakeholders, it will fast track the achievement of the SDGs.

Clara Yono Yatini
Space Science Center, LAPAN, Indonesia

Biography

Yatini received her BS in Bandung Institute of Technology and MS from Tohoku University Japan from the Department of Astronomy, specializing in Solar Physics. She joined the National Institute of Aeronautics and Space (LAPAN) Indonesia since 1990 and began to conduct research on the Solar Physics. She has served as the Head of the Sun and Space Division, and Geo and Space Magnetism Division afterwards. She currently serves as the Director of the Space Science Center. Research on space weather and its impact has been conducted more intensively, and since 2010 along with colleagues at the Space Science Center began to develop a space weather information system named SWIFtS (Space Weather Information and Forecast Services). Recently she regularly participated in the UN meeting as a member of the Indonesian delegation at UNCOPUOS (United Nations Committee on Peaceful Uses of Outer Space).

Abstract

Title: Space Weather Information and Forecast  Services in South East Asia Region

Along with the increased awareness to the impact of space weather towards the space-based technology, the information services regarding space weather, including the forecast, is indispensable. The space weather covering the condition between the Sun and the Earth. The solar activity is a phenomenon that can be predicted to mitigate the impacts. The solar activities that have to be predicted among others are the flare(s) occurrence, coronal mass ejections, and also coronal holes. A few models of solar activities have been developed to give predictions. The condition of magnetosphere can be observed by doing ground-based observation using the magnetometer. These observations can show the index of geomagnetic disturbance which is utilized to give information regarding the interference to the earth magnetic field and the possible impact to the ionosphere. Ionosphere observation uses equipment such as ionosonde, GISTM, etc, are integrated to perceive the condition of the ionosphere and its impacts on HF radio communication and navigation. By combining the observations and the models used, therefore space weather service and forecast facility called SWIFtS has been built. SWIFtS gives information and daily outer space forecast, and has been standardized by ISO 9001-2015.­­­­

Dr Andrew Thomas Hudak
United States Department of Agriculture (USDA) Forest Service, USA

Biography

Andrew Hudak got his B.S. and PhD degrees in Ecology from the University of Minnesota, USA (1990) and the University of Colorado, USA (1999), respectively. In between, he taught secondary school science in the U.S. Peace Corps in Malawi (1990-1992) and travelled. In 1999, he began working for the U.S. Forest Service as a postdoctoral Research Ecologist with the Pacific Northwest Research Station. Since 2001, he has worked as a Research Forester with the Rocky Mountain Research Station. He currently studies biophysical relationships between field and remotely sensed data collected at landscape to regional scales, including upscaling project-level aboveground biomass carbon estimates across the northwestern U.S. from airborne LiDAR and annual Landsat time series, predicting fuel/carbon loads from 3D point cloud metrics at multiple scales, and relating fuel consumption to energy flux and fire effects. He recently completed a project tracking long-term vegetation recovery at 15 wildfires across the U.S. West and interior Alaska. Projects that bridge the scaling gap in both space and time, between field and remote sensing data, such that value is added to both, along with utility for managers, are of greatest interest. He has published more than 200 refereed journal articles with 7,582 citations, h-index of 45 and an i10-index of 97. He received several awards such as award in Technology Transfer Publication in the USFS Rocky Mountain Research Station in 2012 and a Bridge Builder Award in 2010 for collaborative efforts with students and faculty of the University of Idaho, College of Natural Resources.

Abstract

Title: Mapping forest aboveground biomass annually (2000-2016) from Landsat time series

The advent of time series analyses algorithms applied to the historical Landsat image archive has made this the golden age of Landsat data utility. Moreover, the availability on Google Earth Engine of image time series algorithms and radiometrically and geometrically corrected Landsat image stacks, thoroughly cloud-screened at the pixel level, has made big data processing applications available to ordinary users. In this talk, we present results from a regional forest aboveground biomass (AGB) mapping study in the northwestern USA. Because Landsat data are relatively insensitive to canopy structure compared to airborne lidar, our approach was to train predictive Random Forest models from the ground up, using project-level lidar and field plots (N=3,672) contributed by US Forest Service and other land managers. Height and density metrics were calculated from the point cloud data binned within the plot footprints, and associated with the tree biomass calculations also summarized at the plot level, to predict forest AGB with high confidence and map AGB wherever lidar data were available. These landscape-level AGB maps served as training areas for predicting forest AGB synoptically across the northwestern USA; i.e., a stratified random sample of AGB pixels was drawn from these landscape-level forest AGB maps and used to predict AGB from the Landsat time series processed through the LandTrendr algorithm available on Google Earth Engine. LandTrendr predictors included annual tasseled cap indices (and annual delta indices) as well as disturbance metrics such as time since last disturbance. To help overcome the relative insensitivity to canopy structure that limits Landsat data, particularly in high biomass forests, the global forest canopy height product derived from ICESAT/GLAS spaceborne lidar and Shuttle Radar Topography Mission (SRTM) data was included as a predictor. Also included as additional predictors were climate metrics calculated from 30-year (1960-1990) climate normals, to better capture the huge, topographically-driven environmental gradients that exist across the northwestern USA. To verify our AGB maps for carbon monitoring, reporting and verification (MRV), we aggregated the mapped annual biomass predictions to the county level and compare them to annual county-level biomass summarized independently from systematic, field-based, annual inventories conducted by the US Forest Inventory and Analysis (FIA) Program nationally. National-scale forest cover maps generated independently from PALSAR data at 25-m resolution were used to define forested areas for the AGB aggregations. The unbiased AGB estimates based on FIA data were approximately 70% of our own AGB estimates that had been based on a biased sample. Therefore, we applied a simple linear bias correction to the 2000-2016 AGB maps, which have been submitted to the NASA Oak Ridge National Lab (ORNL) Distributed Active Archive Center (DAAC) for public consumption. Our plan for future research is to integrate AGB estimates sampled with ICESAT-2 and GEDI spaceborne lidar systems into our Carbon Monitoring System, which like Landsat data will be globally available.

 

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