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International Space Station Earth Observations Working Group

The multilateral Earth Observations Working Group (EOWG) was chartered in May 2012 in order to improve coordination and collaboration of Earth observing payloads, research, and applications on the International Space Station (ISS). The EOWG derives its authority from the ISS Program Science Forum, and a NASA representative serves as a permanent co-chair. A rotating co-chair position can be occupied by any of the international partners, following concurrence by the other partners; a JAXA representative is the current co-chair. Primary functions of the EOWG include, 1) the exchange of information on plans for payloads, from science and application objectives to instrument development, data collection, distribution and research; 2) recognition and facilitation of opportunities for international collaboration in order to optimize benefits from different instruments; and 3) provide a formal ISS Program interface for collection and application of remotely sensed data collected in response to natural disasters through the International Charter, Space and Major Disasters. Recent examples of EOWG activities include coordination of bilateral data sharing protocols between NASA and TsNIIMash for use of crew time and instruments in support of ATV5 reentry imaging activities; discussion of continued use and support of the Nightpod camera mount system by NASA and ESA; and review and revision of international partner contributions on Earth observations to the ISS Program Benefits to Humanity publication.

Stefanov, William L.↗

Onboard Radar Processing Development for Rapid Response Applications

We are developing onboard processor (OBP) technology to streamline data acquisition on-demand and explore the potential of the L-band SAR instrument onboard the proposed DESDynI mission and UAVSAR for rapid response applications. The technology would enable the observation and use of surface change data over rapidly evolving natural hazards, both as an aid to scientific understanding and to provide timely data to agencies responsible for the management and mitigation of natural disasters. We are adapting complex science algorithms for surface water extent to detect flooding, snow/water/ice classification to assist in transportation/ shipping forecasts, and repeat-pass change detection to detect disturbances. We are near completion of the development of a custom FPGA board to meet the specific memory and processing needs of L-band SAR processor algorithms and high speed interfaces to reformat and route raw radar data to/from the FPGA processor board. We have also developed a high fidelity Matlab model of the SAR processor that is modularized and parameterized for ease to prototype various SAR processor algorithms targeted for the FPGA. We will be testing the OBP and rapid response algorithms with UAVSAR data to determine the fidelity of the products.

dual polarized data↗

Use of QuakeSim and UAVSAR for Earthquake Damage Mitigation and Response

Spaceborne, airborne, and modeling and simulation techniques are being applied to earthquake risk assessment and response for mitigation from this natural disaster. QuakeSim is a web-based portal for modeling interseismic strain accumulation using paleoseismic and crustal deformation data. The models are used for understanding strain accumulation and release from earthquakes as well as stress transfer to neighboring faults. Simulations of the fault system can be used for understanding the likelihood and patterns of earthquakes as well as the likelihood of large aftershocks from events. UAVSAR is an airborne L-band InSAR system for collecting crustal deformation data. QuakeSim, UAVSAR, and DESDynI (following launch) can be used for monitoring earthquakes, the associated rupture and damage, and postseismic motions for prediction of aftershock locations.

fault systems↗

The Matsu Wheel: A Cloud-Based Framework for Efficient Analysis and Reanalysis of Earth Satellite Imagery

Project Matsu is a collaboration between the Open Commons Consortium and NASA focused on developing open source technology for cloud-based processing of Earth satellite imagery with practical applications to aid in natural disaster detection and relief. Project Matsu has developed an open source cloud-based infrastructure to process, analyze, and reanalyze large collections of hyperspectral satellite image data using OpenStack, Hadoop, MapReduce and related technologies. We describe a framework for efficient analysis of large amounts of data called the Matsu "Wheel." The Matsu Wheel is currently used to process incoming hyperspectral satellite data produced daily by NASA's Earth Observing-1 (EO-1) satellite. The framework allows batches of analytics, scanning for new data, to be applied to data as it flows in. In the Matsu Wheel, the data only need to be accessed and preprocessed once, regardless of the number or types of analytics, which can easily be slotted into the existing framework. The Matsu Wheel system provides a significantly more efficient use of computational resources over alternative methods when the data are large, have high-volume throughput, may require heavy preprocessing, and are typically used for many types of analysis. We also describe our preliminary Wheel analytics, including an anomaly detector for rare spectral signatures or thermal anomalies in hyperspectral data and a land cover classifier that can be used for water and flood detection. Each of these analytics can generate visual reports accessible via the web for the public and interested decision makers. The result products of the analytics are also made accessible through an Open Geospatial Compliant (OGC)-compliant Web Map Service (WMS) for further distribution. The Matsu Wheel allows many shared data services to be performed together to efficiently use resources for processing hyperspectral satellite image data and other, e.g., large environmental datasets that may be analyzed for many purposes.

Soil Moisture Active Passive (SMAP) Mission Level 4 Surface and Root Zone Soil Moisture (L4_SM) Product Specification Document

This is the Product Specification Document (PSD) for Level 4 Surface and Root Zone Soil Moisture (L4_SM) data for the Science Data System (SDS) of the Soil Moisture Active Passive (SMAP) project. The L4_SM data product provides estimates of land surface conditions based on the assimilation of SMAP observations into a customized version of the NASA Goddard Earth Observing System, Version 5 (GEOS-5) land data assimilation system (LDAS). This document applies to any standard L4_SM data product generated by the SMAP Project. The Soil Moisture Active Passive (SMAP) mission will enhance the accuracy and the resolution of space-based measurements of terrestrial soil moisture and freeze-thaw state. SMAP data products will have a noteworthy impact on multiple relevant and current Earth Science endeavors. These include: Understanding of the processes that link the terrestrial water, the energy and the carbon cycles, Estimations of global water and energy fluxes over the land surfaces, Quantification of the net carbon flux in boreal landscapes Forecast skill of both weather and climate, Predictions and monitoring of natural disasters including floods, landslides and droughts, and Predictions of agricultural productivity. To provide these data, the SMAP mission will deploy a satellite observatory in a near polar, sun synchronous orbit. The observatory will house an L-band radiometer that operates at 1.40 GHz and an L-band radar that operates at 1.26 GHz. The instruments will share a rotating reflector antenna with a 6 meter aperture that scans over a 1000 km swath.

L4-SM↗

Benefits of International Collaboration on the International Space Station

The International Space Station is a valuable platform for research in space, but the benefits are limited if research is only conducted by individual countries. Through the efforts of the ISS Program Science Forum, international science working groups, and interagency cooperation, international collaboration on the ISS has expanded as ISS utilization has matured. Members of science teams benefit from working with counterparts in other countries. Scientists and institutions bring years of experience and specialized expertise to collaborative investigations, leading to new perspectives and approaches to scientific challenges. Combining new ideas and historical results brings synergy and improved peer-reviewed scientific methods and results. World-class research facilities can be expensive and logistically complicated, jeopardizing their full utilization. Experiments that would be prohibitively expensive for a single country can be achieved through contributions of resources from two or more countries, such as crew time, up- and down mass, and experiment hardware. Cooperation also avoids duplication of experiments and hardware among agencies. Biomedical experiments can be completed earlier if astronauts or cosmonauts from multiple agencies participate. Countries responding to natural disasters benefit from ISS imagery assets, even if the country has no space agency of its own. Students around the world participate in ISS educational opportunities, and work with students in other countries, through open curriculum packages and through international competitions. Even experiments conducted by a single country can benefit scientists around the world, through specimen sharing programs and publicly accessible "open data" repositories. For ISS data, these repositories include GeneLab, the Physical Science Informatics System, and different Earth data systems. Scientists can conduct new research using ISS data without having to launch and execute their own experiments. Multilateral collections of research results publications, maintained by the ISS international partnership and accessible via nasa.gov, make ISS results available worldwide, and encourage new users, ideas and research.

Hasbrook, Pete↗

Near Real-Time Flood Monitoring and Impact Assessment Systems

Floods are the costliest natural disaster (United Nations 2004), causing approximately6.8 million deaths in the twentieth century alone (Doocy et al. 2013).Worldwide economic flood damage estimates in 2012 exceed $19 Billion USD(Munich Re 2013). Extended duration floods also pose longer term threats to food security, water, sanitation, hygiene, and community livelihoods, particularly in developing countries (Davies et al. 2014).Projections by the Intergovernmental Panel on Climate Change (IPCC) suggest that precipitation extremes, rainfall intensity, storm intensity, and variability are increasing due to climate change (IPCC 2007). Increasing hydrologic uncertainty will likely lead to unprecedented extreme flood events. As such, there is a vital need to enhance and further develop traditional techniques used to rapidly assessflooding and extend analytical methods to estimate impacted population and infrastructure.

flood↗

Benefits of International Collaboration on the International Space Station

The International Space Station is a valuable platform for research in space, but the benefits are limited if research is only conducted by individual countries. Through the efforts of the ISS Program Science Forum, international science working groups, and interagency cooperation, international collaboration on the ISS has expanded as ISS utilization has matured. Members of science teams benefit from working with counterparts in other countries. Scientists and institutions bring years of experience and specialized expertise to collaborative investigations, leading to new perspectives and approaches to scientific challenges. Combining new ideas and historical results brings synergy and improved peer-reviewed scientific methods and results. World-class research facilities can be expensive and logistically complicated, jeopardizing their full utilization. Experiments that would be prohibitively expensive for a single country can be achieved through contributions of resources from two or more countries, such as crew time, up- and downmass, and experiment hardware. Cooperation also avoids duplication of experiments and hardware among agencies. Biomedical experiments can be completed earlier if astronauts or cosmonauts from multiple agencies participate. Countries responding to natural disasters benefit from ISS imagery assets, even if the country has no space agency of its own. Students around the world participate in ISS educational opportunities, and work with students in other countries, through open curriculum packages and through international competitions. Even experiments conducted by a single country can benefit scientists around the world, through specimen sharing programs and publicly accessible "open data" repositories. For ISS data, these repositories include GeneLab and the Physical Science Informatics System. Scientists can conduct new research using ISS data without having to launch and execute their own experiments. Multilateral collections of research results publications, maintained by the ISS international partnership and accessible via nasa.gov, make ISS results available worldwide, and encourage new users, ideas and research. The paper explores international collaboration history, its evolution and maturation, change of focus during its different phases, and growth of its effectiveness (in accordance with the especially established criteria) in the light of benefits for the entire ISS community. With the International Space Station extended through at least 2024, more crew time becoming available and new facilities arriving on board the ISS, these benefits of international scientific collaboration on the ISS can only increase.

Hasbrook, Pete↗

Benefits of International Collaboration on the International Space Station

The International Space Station is a valuable platform for research in space, but the benefits are limited if research is only conducted by individual countries. Through the e orts of the ISS Program Science Forum, international science working groups, and interagency cooperation, international collaboration on the ISS has expanded as ISS utilization has matured. Members of science teams benefit from working with counterparts in other countries. Scientists and institutions bring years of experience and specialized expertise to collaborative investigations, leading to new perspectives and approaches to scientific challenges. Combining new ideas and historical results brings synergy and improved peer-reviewed scientific methods and results. World-class research facilities can be expensive and logistically complicated, jeopardizing their full utilization. Experiments that would be prohibitively expensive for a single country can be achieved through contributions of resources from two or more countries, such as crew time, up- and downmass, and experiment hardware. Cooperation also avoids duplication of experiments and hardware among agencies. Biomedical experiments can be completed earlier if astronauts or cosmonauts from multiple agencies participate. Countries responding to natural disasters benefit from ISS imagery assets, even if the country has no space agency of its own. Students around the world participate in ISS educational opportunities, and work with students in other countries, through open curriculum packages and through international competitions. Even experiments conducted by a single country can benefit scientists around the world, through specimen sharing programs and publicly accessible \open data" repositories. For ISS data, these repositories include GeneLab, the Physical Science Informatics System, and different Earth science data systems. Scientists can conduct new research using ISS data without having to launch and execute their own experiments. Multilateral collections of research results publications, maintained by the ISS international partnership and accessible via nasa.gov, make ISS results available worldwide, and encourage new users, ideas and research. The paper explores effectiveness of international collaboration in the course of the ISS Program execution. The collaboration history, its evolution and maturation, change of focus during its different phases, and growth of its effectiveness (in accordance with the especially established criteria) are also considered in the paper in the light of benefits for the entire ISS community. With the International Space Station extended through at least 2024, more crew time becoming available and new facilities arriving on board the ISS, these benefits of international scientific collaboration on the ISS can only increase.

Robinson, Julie A.↗

Giovanni in the Cloud: Earth Science Data Exploration in Amazon Web Services

Giovanni is an exploration tool at the NASA Goddard Earth Sciences Data Information Services Center (GES DISC), providing 22 analysis and visualization services for over 1600 Earth Science data variables. Owing to its popularity, Giovanni has experienced a consistent growth in overall demand, with periodic usage spikes attributed to trainings by education organizations, extensive data analysis in response to natural disasters, preparations for science meetings, etc. Furthermore, the new generation of spaceborne sensors and high resolution models have resulted in an exponential growth in data volume with data distributed across the traditional boundaries of data centers. Seamless exploration of data (without users having to worry about data center boundaries) has been a key recommendation of the GES DISC User Working Group. These factors have required new strategies for delivering acceptable performance. The cloud-based Giovanni, built on Amazon Web Services (AWS), evaluates (1) AWS native solutions to provide a scalable, serverless architecture; (2) open standards for data storage in the Cloud; (3) a cost model for operations; and (4) end-user performance. Our preliminary findings indicate that the use of serverless architecture has a potential to significantly reduce development and operational cost of Giovanni. The combination of using AWS managed services, storage of data in open standards, and schema-on-read data access strategy simplifies data access and analytics, in addition to making data more accessible to the end users of Giovanni through popular programming languages.

Giovanni↗

Developing a Remotely Sensed Drought Monitoring Indicator for Morocco

Drought is one of the most serious climatic and natural disasters inflicting serious impacts on the socio-economy of Morocco, which is characterized both by low-average annual rainfall and high irregularity in the spatial distribution and timing of precipitation across the country. This work aims to develop a comprehensive and integrated method for drought monitoring based on remote sensing techniques. The main input parameters are derived monthly from satellite data at the national scale and are then combined to generate a composite drought index presenting different severity classes of drought. The input parameters are: Standardized Precipitation Index calculated from satellite-based precipitation data since 1981 (CHIRPS), anomalies in the day-night difference of Land Surface Temperature as a proxy for soil moisture, Normalized Difference Vegetation Index anomalies from Moderate Resolution Imaging Spectroradiometer (MODIS) data and Evapotranspiration anomalies from surface energy balance modeling. All of these satellite-based indices are being used to monitor vegetation condition, rainfall and land surface temperature. The weighted combination of these input parameters into one composite indicator takes into account the importance of the rainfall-based parameter (SPI). The composite drought index maps were generated during the growing seasons going back to 2003. These maps have been compared to both the historical, in situ precipitation data across Morocco and with the historical yield data across different provinces with information being available since 2000. The maps are disseminated monthly to several main stakeholders' groups including the Ministry of Agriculture and Department of Water in Morocco.

Drought monitoring↗

SERVIR: Connecting Space to Village

From space, we can view our planet in new ways. SERVIR empowers people in developing countries to use that view for gaining knowledge and insights about their environments and adaptation to a changing climate. We work with regional decision-makers to foster use of Earth observation satellite data, GIS, and predictive models for addressing water and land use, natural disasters, agricultural problems, biodiversity, and more. These tools can improve the lives, livelihoods, safety, and future of people in communities around the world.

Limaye, Ashutosh S.↗

SERVIR Connecting Space to Village

From space, we can view our planet in new ways. SERVIR empowers people in developing countries to use that view for gaining knowledge and insights about their environments and adaptation to a changing climate. We work with regional decision-makers to foster use of Earth observation satellite data, GIS, and predictive models for addressing water and land use, natural disasters, agricultural problems, biodiversity, and more. These tools can improve the lives, livelihoods, safety, and future of people in communities around the world.

Puzzi Nicolau, Andrea↗

Earth Science Engagement Through Art and Astronaut Photography

For over five decades of manned spaceflight missions, NASA astronauts have taken extraordinary photographs of Earth's surface and dynamic processes. Humans on board the International Space Station (ISS) have a unique platform to perform Earth observations at various viewing angles, seasons, and times of day. Astronaut photos taken from the ISS comprise a true‐color (RGB) dataset taken with multiple handheld digital cameras and lens types (prior to 2004, film cameras were in use). Earth observations through astronaut photography are an important and unique remote sensing method when monitoring natural disasters, urban growth, and environmental changes. While astronaut imagery can be used for earth science research, there is also an artistic aspect to the photography that fascinates a wide global population. A broader public audience can be introduced to earth science through high resolution, Earth art photos taken from the perspective of an astronaut. The Crew Earth Observations (CEO) Facility within the Earth Science and Remote Sensing Unit at NASA's Johnson Space Center supports the acquisition, analysis, and curation of astronaut photography of Earth's surface and atmosphere. CEO's website, the Gateway to Astronaut Photography of Earth (eol.jsc.nasa.gov), provides free public access to view, search, and download over three million images taken by astronauts throughout all of NASA's crewed spaceflight history, with an emphasis on current ISS imagery. The CEO Facility actively curates a digital collection of exceptional Earth art astronaut photos used for public engagement. Our new Downloadable Earth Art page focuses on broad earth science topics including: mountains, water, clouds, agriculture, as well as an "abstract" category. This continuously‐updated collection is comprised of freely accessible and high‐quality downloadable materials, such as single‐ and dual‐screen digital wallpapers. All Earth Art materials are presented with science‐based information that complements the artistic qualities of the imagery, and facilitate connections between general audiences and earth science from the International Space Station.

Meado, Andrea L.↗

Identifying and Forecasting Potential Biophysical Risk Areas within a Tropical Mangrove Ecosystem Using Multi-Sensor Data

Mangroves are one of the most productive ecosystems known for provisioning of various ecosystem goods and services. They help in sequestering large amounts of carbon, protecting coastline against erosion, and reducing impacts of natural disasters such as hurricanes. Bhitarkanika Wildlife Sanctuary in Odisha harbors the second largest mangrove ecosystem in India. This study used Terra, Landsat and Sentinel-1 satellite data for spatio-temporal monitoring of mangrove forest within Bhitarkanika Wildlife Sanctuary between 2000 and 2016. Three biophysical parameters were used to assess mangrove ecosystem health: leaf chlorophyll (CHL), Leaf Area Index (LAI), and Gross Primary Productivity (GPP). A long-term analysis of meteorological data such as precipitation and temperature was performed to determine an association between these parameters and mangrove biophysical characteristics. The correlation between meteorological parameters and mangrove biophysical characteristics enabled forecasting of mangrove health and productivity for year 2050 by incorporating IPCC projected climate data. A historical analysis of land cover maps was also performed using Landsat 5 and 8 data to determine changes in mangrove area estimates in years 1995, 2004 and 2017. There was a decrease in dense mangrove extent with an increase in open mangroves and agricultural area. Despite conservation efforts, the current extent of dense mangrove is projected to decrease up to 10% by the year 2050. All three biophysical characteristics including GPP, LAI and CHL, are projected to experience a net decrease of 7.7%, 20.83% and 25.96% respectively by 2050 compared to the mean annual value in 2016. This study will help the Forest Department, Government of Odisha in managing and taking appropriate decisions for conserving and sustaining the remaining mangrove forest under the changing climate and developmental activities.

Shanti Shrestha↗

Using GES DISC Data to Study Kilauea Volcano of 2018

Kilauea volcano in Hawaii which erupted in early May 2018 injected massive amount of SO2 and ash into the atmosphere. The lava flow during the eruption destroyed many home and neighborhoods. The SO2 plume during the eruption of Kilauea volcano is analyzed from May to August 2018 using multiple satellite products such as Level 2 TROPspheric Monitoring Instrument (TROPOMI) and Level 3 Ozone Monitoring Instrument (OMI) from the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). GES DISC hosts multi-disciplinary Earth science data sets that can be used to analyze natural disasters, such as the Kilauea volcano. Additionally, GES DISC's Giovanni tool can be used to visualize these data. We acquired OMI through the subsetting function, which is processed by the GES DISC in-house developed backend software Level3/4 Regrider and Subsetter (L34RS) and TROPOMI using OPeNDAP.Data from the OMI OMSO2e product showed elevated levels of SO2 amounts during the eruption between May to August 2018. Similarly, ground-based stations at Hawaii Volcanoes National Park recorded higher SO2 concentrations during the same time period. This study uses wind direction from Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) to analyze the transport and dispersion of SO2 plume and map lava flows from the volcano using thermal images from Visible Infrared Imaging Radiometer Suite (VIIRS). Furthermore, satellite observations combined with socioeconomic and public health data are used to analyze its impact in public health.

KC, Binita↗

Advanced Unmanned Aerial Vehicles for Improved Communications

Reestablishing communication channels is one of the most important yet time-consuming procedures to carry out following a natural disaster. After Hurricane Katrina impacted Louisiana in 2005, more than 60% of networks were still down 3 weeks after the event.1 In 2017, when Hurricane María devastated Puerto Rico, 95% of cellular sites failed island-wide, leaving many civilians disconnected for months.2 One viable approach to this challenge is increasing the capabilities of Unmanned Aerial Vehicles (UAVs), commonly known as drones, which could provide sustained communication outlets in hard-to-access areas while emergency response efforts are underway.

Light, Bailey G.↗

Deepti: Deep-Learning-Based Tropical Cyclone Intensity Estimation System

Tropical cyclones are one of the costliest natural disasters globally because of the wide range of associated hazards. Thus, an accurate diagnostic model for tropical cyclone intensity can save lives and property. There are a number of existing techniques and approaches that diagnose tropical cyclone wind speed using satellite data at a given time with varying success. This paper presents a deep learning-based objective, diagnostic estimate of tropical cyclone intensity from infrared satellite imagery with 13.24 kt Root Mean Squared Error (RMSE). In addition, a visualization portal in a production system is presented that displays deep learning output and contextual information for end users, one of the first of its kind.

Manil Maskey↗