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NASA NTRSDate not supplied

Building Capacity to Use Earth Observations for Disaster Risk Reduction and Resilience Applications: A Summary of NASA’s DEVELOP Program and Projects in Central and South America

NASA’s DEVELOP program engages individuals and organizations in 10-week feasibility studies to apply NASA Earth observations (EO) to decision makers’ needs. Since 2018, DEVELOP conducted 21 projects in Central and South America, eight of those in collaboration with Sistema de la Integración Centroamericana (SICA) and its member state partner agencies. These projects addressed a diverse set of community needs across multiple themes, including two focused on disaster risk reduction and resilience using EO for mapping landslide susceptibility in the Dominican Republic and riparian flooding in Guatemala and El Salvador. This poster introduces DEVELOP, its approach to capacity building, key partnerships, and project results highlighting the capabilities of EO for enhanced decision making in the area of reduction of disaster risk and support disaster resilience.

Capacity Building↗
NASA NTRS2021

Southwest Water Resources: Monitoring Surface Water Extents of Remote Stock Ponds in the Southwestern United States Using Earth Observing Systems for Enhanced Water Resources Management

Due to increasingly frequent and severe drought conditions in the southwestern US, land managers and livestock producers need to monitor stock ponds with increasing regularity. The ability to assess stock pond water levels with Earth observing satellite systems would enhance monitoring efforts of partners at the US Forest Service, Arizona Department of Game and Fish, and the Diablo Trust. This study employed Landsat 8 Operational Land Imager (OLI), Sentinel-1 C-band Synthetic Aperture Radar (C-SAR), and Sentinel-2 Multispectral Instrument (MSI) to monitor surface water extent for hundreds of critical stock ponds in Arizona. Using methods adapted from previously developed image processing workflows, this project conducted a time-series analysis to capture seasonal and interannual variations in surface water area between 2013 to 2021. In addition, end users can monitor the surface water extent of stock ponds through the developed Google Earth Engine software tool called Surface Water Identification and Forecasting Tool (SWIFT). SWIFT incorporates the Automated Water Extraction Index, Modified Normalized Difference Water Index, and Tasseled Cap-Wetness Index for optical imagery and the incidence angle, VV and VH polarization bands for Sentinel-1 imagery to detect small water bodies in the study area with an overall accuracy range of 88-93%. These tools will empower our partners to monitor the extents of water in their stock ponds remotely, enabling them to develop data-informed and sustainable management solutions for decades to come.

Rainey Aberle↗
NASA NTRS1992

Shuttle Imaging Radar-C mission operations - Technology test bed for Earth Observing System synthetic aperture radar

The mission operations for the Space Radar Lab (SRL), particularly in the areas of real-time replanning and science activity coordination, are presented. The two main components of SRL are the Shuttle Imaging Radar-C and the X-Band Synthetic Aperture Radar. The Earth Observing System SAR will be a multispectral, multipolarization radar satellite that will provide information over an entire decade, permitting scientists to monitor large-scale changes in the earth's environment over a long period of time.

Trimble, J. P.↗
NASA NTRS2024

Cali Urban Development: Using NASA Earth Observations to Assess Wetlands and Land Reclamation in Cali, Colombia

Recent research has documented the global decline of wetlands, largely attributed to increased urbanization and agriculture. This NASA DEVELOP study partnered with two local environmental entities in Cali, Colombia: The Fundación Dinamizadores Ambientales and the Departamento Administrativo de Gestión del Medio Ambiente. The team utilized Earth observations to evaluate trends in wetland extent, potential, and land cover in Cali between 2002 and 2023. A supervised classifier was generated within Google Earth Engine to create land use analyses of the region using Landsat 5 TM, Landsat 8 OLI, and Landsat 9 OLI-2 imagery. To identify locations of wetland potential within the study area, wetland probability was assessed by inputting PlanetScope, Sentinel-2 MSI, and partner-provided datasets into the Wetland Intrinsic Potential Tool in ArcGIS Pro and R. Data from Sentinel-1 C-SAR, Sentinel 2-MSI, and Suomi-NPP VIIRS were used to evaluate wetland extent using the Wetland Extent 3.0 Tool in3 Python. Overall, results indicated high wetland potential, particularly in the southeast region where agricultural areas were previously wetlands. Outputs also suggest a vast network of riparian wetlands in Cali. This study did not investigate socioeconomic data as it relates to wetlands, which is an avenue for future research. This project supplemented research into links between land use change, wetland extent, and wetland potential, and provided partner organizations with an objective foundation from which they can identify at-risk wetlands and develop community initiatives for management, conservation, and education.

Cali↗
NASA NTRS2005

Lessons Learned in the Livingstone 2 on Earth Observing One Flight Experiment

The Livingstone 2 (L2) model-based diagnosis software is a reusable diagnostic tool for monitoring complex systems. In 2004, L2 was integrated with the JPL Autonomous Sciencecraft Experiment (ASE) and deployed on-board Goddard's Earth Observing One (EO-1) remote sensing satellite, to monitor and diagnose the EO-1 space science instruments and imaging sequence. This paper reports on lessons learned from this flight experiment. The goals for this experiment, including validation of minimum success criteria and of a series of diagnostic scenarios, have all been successfully net. Long-term operations in space are on-going, as a test of the maturity of the system, with L2 performance remaining flawless. L2 has demonstrated the ability to track the state of the system during nominal operations, detect simulated abnormalities in operations and isolate failures to their root cause fault. Specific advances demonstrated include diagnosis of ambiguity groups rather than a single fault candidate; hypothesis revision given new sensor evidence about the state of the system; and the capability to check for faults in a dynamic system without having to wait until the system is quiescent. The major benefits of this advanced health management technology are to increase mission duration and reliability through intelligent fault protection, and robust autonomous operations with reduced dependency on supervisory operations from Earth. The work-load for operators will be reduced by telemetry of processed state-of-health information rather than raw data. The long-term vision is that of making diagnosis available to the onboard planner or executive, allowing autonomy software to re-plan in order to work around known component failures. For a system that is expected to evolve substantially over its lifetime, as for the International Space Station, the model-based approach has definite advantages over rule-based expert systems and limit-checking fault protection systems, as these do not scale well. The model-based approach facilitates reuse of the L2 diagnostic software; only the model of the system to be diagnosed and telemetry monitoring software has to be rebuilt for a new system or expanded for a growing system. The hierarchical L2 model supports modularity and expendability, and as such is suitable solution for integrated system health management as envisioned for systems-of-systems.

Hayden, Sandra C.↗
NASA NTRSDate not supplied

FAIR-ness Assessment of NASA’s Earth Observation System Data and Information System (EOSDIS)

This presentation addresses the challenge of evaluating a multi-disciplinary institutional network of data repositories in operation since 1994 against the relatively recent criteria that constitute FAIR (Findable, Accessible, Interoperable, Reusable) data. NASA’s Earth Observation System Data and Information System (EOSDIS), with its 12 discipline-based Distributed Active Archive Centers (DAACs), preceded the definition and popularization of FAIR by over two decades. An assessment is very useful to describe how well the FAIR principles are met and to identify any improvements needed. In 2020, A “self-assessment” of EOSDIS and DAACs was performed by the ESDIS Project staff and the DAACs from the points of view of human actionability and machine actionability. More recently, a draft of a Science Mission Directorate (SMP) Program Directive (SPD-41a) has been released by NASA Headquarters for comment, where it is recommended that all SMD-funded data should follow the FAIR principles. This presentation is timely to initiate community discussion within the Information Quality Cluster (IQC) of the Earth Science Information Partners (ESIP) and help strategize and develop implementation guidelines for EOSDIS and DAACs to conform to FAIR principles.

Remote sensing↗
NASA NTRSDate not supplied

The Impact of Ice Sheet Surface Representation on Surface Mass Balance in the Goddard Earth Observing System

Surface conditions and their impacts on surface mass balance (SMB) play important roles in ice sheet dynamics and ice sheet interactions with the overlying atmosphere and surrounding ocean. The NASA Global Modeling and Assimilation Office’s (GMAO) Goddard Earth Observing System (GEOS) – an ecosystem of models and reanalyses – represent ice sheet and glacier SMB components, including prognostic surface albedo evolution, fractional snow cover, and snowpack hydrology and meltwater retention. We find the successful representation of ice sheet surface mass balance in MERRA-2, and similar systems, is partly due to compensating biases in surface energy budget. In the atmospheric system, subsequent changes to cloud microphysics and in the longwave radiative transfer model are found to have reduced biases in surface net longwave radiation fluxes while exacerbating surface net shortwave radiation biases, producing erroneously high near-surface temperatures and surface melt in summer months. These issues can be exacerbated by poor experiment initialization and the use of two-moment cloud microphysics within the GEOS ocean-atmosphere coupled system. Here, we document the spatial and temporal extent and causes of these biases in the ice sheet surface energy budget across GEOS systems and implement a range of model improvements to mitigate these issues. We examine the combined impact on these changes on regional energy budget and SMB using both free running and replay experiments (to simulate the impact in reanalyses). Overall, these improvements increase modeled ice sheet surface realism and provide a strong basis for more accurate ice sheet SMB in GMAO’s future reanalyses and forecasting systems.

Lauren C Andrews↗
NASA NTRS2018

Preliminary Evaluation of Influence of Aerosols on the Simulation of Brightness Temperature in the NASA's Goddard Earth Observing System Atmospheric Data Assimilation System

This document reports on preliminary results obtained when studying the impact of aerosols on the calculation of brightness temperature (BT) for satellite infrared (IR) instruments that are currently assimilated in a 3DVAR configuration of Goddard Earth Observing System (GEOS)-atmospheric data assimilation system (ADAS). A set of fifteen aerosol species simulated by the Goddard Chemistry Aerosol Radiation and Transport (GOCART) model is used to evaluate the influence of the aerosol fields on the Community Radiative Transfer Model (CRTM) calculations taking place in the observation operators of the Gridpoint Statistical Interpolation (GSI) analysis system of GEOSADAS. Results indicate that taking aerosols into account in the BT calculation improves the fit to observations over regions with significant amounts of dust. The cooling effect obtained with the aerosol-affected BT leads to a slight warming of the analyzed surface temperature (by about 0:5oK) in the tropical Atlantic ocean (off northwest Africa), whereas the effect on the air temperature aloft is negligible. In addition, this study identifies a few technical issues to be addressed in future work if aerosol-affected BT are to be implemented in reanalysis and operational settings. The computational cost of applying CRTM aerosol absorption and scattering options is too high to justify their use, given the size of the benefits obtained. Furthermore, the differentiation between clouds and aerosols in GSI cloud detection procedures needs satisfactory revision.

3DVAR↗
NASA NTRS1990

The NASA Environment Remote Sensing Analysis Facility (ERSAF) support for Space Shuttle earth observations

It is shown that dedicated premission, real-time, and postmission support for planning, acquiring, and interpreting remotely sensed data of specific sites in terms of illumination geometry, atmospheric transmissivity, and preferred viewing is required in order to acquire the best possible earth-viewing photography for each Shuttle mission. Mission support has resulted in significant advances for the earth observation activities and other experiments carried out by astronauts. Scientific and mission support are described and equipment and capabilities are reviewed. Future advances listed include improvement of existing data bases, expanding access to climatological databases of atmospheric constituents and aerosols, and expanding access to image data such as the DMSP, while Space Station Freedom will require 24-hour operational support.

Helms, David R.↗
NASA NTRS1992

Earth observing system. Output data products and input requirements, version 2.0. Volume 2: Analysis of IDS input requirements

On 18 Jan. 1991, NASA confirmed 29 Inter-Disciplinary Science (IDS) teams, each involving a group of investigators, to conduct interdisciplinary research using data products from Earth Observing System (EOS) instruments. These studies are multi-disciplinary and require output data products from multiple EOS instruments, including both FI and PI instruments. The purpose of this volume is to provide information on output products expected from IDS investigators, required input data, and retrieval algorithms. Also included in this volume is the revised analysis of the 'best' and 'alternative' match data products for IDS input requirements. The original analysis presented in the August 1991 release of the SPSO Report was revised to incorporate the restructuring of the EOS platform. As a result of the reduced EOS payload, some of EOS instruments were deselected and their data products would not be available for IDS research. Information on these data products is also presented.

Lu, Yun-Chi↗
NASA NTRS1976

Program on Earth Observation Data Management Systems (EODMS), appendixes

The needs of state, regional, and local agencies involved in natural resources management in Illinois, Iowa, Minnesota, Missouri, and Wisconsin are investigated to determine the design of satellite remotely sensed derivable information products. It is concluded that an operational Earth Observation Data Management System (EODMS) will be most beneficial if it provides a full range of services - from raw data acquisition to interpretation and dissemination of final information products. Included is a cost and performance analysis of alternative processing centers, and an assessment of the impacts of policy, regulation, and government structure on implementing large scale use of remote sensing technology in this community of users.

Eastwood, L. F., Jr.↗
NASA NTRS1994

Earth observations for the space radar laboratory mission: Report on the student challenge awards project

The Challenge Awards are designed to provide a unique perspective to students gifted in the arts and humanities from which to understand scientific endeavor by giving students an opportunity to participate in an ongoing research project. In the graduate program, seven students who had participated in previous Challenge Awards programs were selected to help develop the tools for Earth observations for the astronauts on the Space Radar Laboratory (SRL) missions. The goal of the Challenge Awards program was to prepare a training manual for the astronauts on the SRL missions. This paper describes the observations to be made by the astronauts on the SRL missions. The emphasis is on the dynamic seasonal features of the Earth's surface and atmosphere which justify the need for more than one flight of the SRL. Complete notebooks of the sites, global seasonal patterns, examples of radar and the Measurement of Air Pollution from Satellites data, and shuttle photographs have been given to each of the SRL crews.

Way, Jobea↗
NASA NTRS2006

Mission Operations of Earth Observing-1 with Onboard Autonomy

Space mission operations are extremely labor and knowledge-intensive and are driven by the ground and flight systems. Inclusion of an autonomy capability can have dramatic effects on mission operations. We describe the past mission operations flow for the Earth Observing-1 (EO-1) spacecraft as well as the more autonomous operations to which we transferred as part of the Autonomous Sciencecraft Experiment (ASE).

hyperspectral images↗
NASA NTRS2015

NASA Earth Observation Systems and Applications for Health and Air Quality

There is a growing body of evidence that the environment can affect human health in ways that are both complex and global in scope. To address some of these complexities, NASA maintains a diverse constellation of Earth observing research satellites, and sponsors research in developing satellite data applications across a wide spectrum of areas. These include environmental health; infectious disease; air quality standards, policies, and regulations; and the impact of climate change on health and air quality in a number of interrelated efforts. The Health and Air Quality Applications fosters the use of observations, modeling systems, forecast development, application integration, and the research to operations transition process to address environmental health effects. NASA has been a primary partner with Federal operational agencies over the past nine years in these areas. This talk presents the background of the Health and Air Quality Applications program, recent accomplishments, and a plan for the future.

Omar, Ali H.↗
NASA NTRS1998

I/O Parallelization for the Goddard Earth Observing System Data Assimilation System (GEOS DAS)

The National Aeronautics and Space Administration (NASA) Data Assimilation Office (DAO) at the Goddard Space Flight Center (GSFC) has developed the GEOS DAS, a data assimilation system that provides production support for NASA missions and will support NASA's Earth Observing System (EOS) in the coming years. The GEOS DAS will be used to provide background fields of meteorological quantities to EOS satellite instrument teams for use in their data algorithms as well as providing assimilated data sets for climate studies on decadal time scales. The DAO has been involved in prototyping parallel implementations of the GEOS DAS for a number of years and is now embarking on an effort to convert the production version from shared-memory parallelism to distributed-memory parallelism using the portable Message-Passing Interface (MPI). The GEOS DAS consists of two main components, an atmospheric General Circulation Model (GCM) and a Physical-space Statistical Analysis System (PSAS). The GCM operates on data that are stored on a regular grid while PSAS works with observational data that are scattered irregularly throughout the atmosphere. As a result, the two components have different data decompositions. The GCM is decomposed horizontally as a checkerboard with all vertical levels of each box existing on the same processing element(PE). The dynamical core of the GCM can also operate on a rotated grid, which requires communication-intensive grid transformations during GCM integration. PSAS groups observations on PEs in a more irregular and dynamic fashion.

Lucchesi, Rob↗
NASA NTRS1999

I/O Parallelization for the Goddard Earth Observing System Data Assimilation System (GEOS DAS)

The National Aeronautics and Space Administration (NASA) Data Assimilation Office (DAO) at the Goddard Space Flight Center (GSFC) has developed the GEOS DAS, a data assimilation system that provides production support for NASA missions and will support NASA's Earth Observing System (EOS) in the coming years. The DAO's support of the EOS project along with the requirement of producing long-term reanalysis datasets with an unvarying system levy a large I/O burden on the future system. The DAO has been involved in prototyping parallel implementations of the GEOS DAS for a number of years and is now converting the production version from shared-memory parallelism to distributed-memory parallelism using the portable Message-Passing Interface (MPI). If the MPI-based GEOS DAS is to meet these production requirements, we must make I/O from the parallel system efficient. We have designed a scheme that allows efficient I/O processing while retaining portability, reducing the need for post-processing, and producing data formats that are required by our users, both internal and external. The first phase of the GEOS DAS Parallel I/O System (GPIOS) will expand upon the common method of gathering global data to a Single PE for output. Instead of using a PE also tasked with primary computation, a number of PEs will be dedicated to I/O and its related tasks. This allows the data transformations and formatting required prior to output to take place asynchronously with respect to the GEOS DAS assimilation cycle, improving performance and generating output data sets in a format convenient for our users. I/O PEs can be added as needed to handle larger data volumes or to meet user file specifications. We will show I/O performance results from a prototype MPI GCM integrated with GPIOS. Phase two of GPIOS development will examine ways of integrating new software technologies to further improve performance and build scalability into the system. The maturing of MPI-IO implementations and other supporting libraries such as parallel HDF should provide performance gains while retaining portability.

Lucchesi, R.↗
NASA NTRS2016

Web Map Apps using NASA's Earth Observing Fleet

Through the miracle of open web mapping services for satellite imagery, a garden of new applications has sprouted to monitor the planet across a variety of domains. The Global Imagery Browse Services (GIBS) provide free and open access to full resolution imagery captured by NASAs Earth observing fleet. Spanning 15+ years and running through as recently as a few hours ago, GIBS aims to provide a general-purpose window into NASA's vast archive of the planet. While the vast nature of this archive can be daunting, many domain-specific applications have been built to meet the needs of their respective communities. This presentation will demonstrate a diverse set of these new applications which can take planetarium visitors into (virtual) orbit, guide fire resource managers to hotspots, help anglers find their next catch, illustrate global air quality patterns to local regulators, and even spur a friendly competition to find clouds which are shaped the most like cats. We hope this garden will continue to grow and will illustrate upcoming upgrades to GIBS which may open new pathways for development. data visualization, web services, open access

data visualization↗