Snow water equivalent (SWE) measurements are crucial for efficiently managing the effects of snow on the environment and human activities. The limitations of providing global snow water equivalent data required to address essential hydrological science questions from existing satellite sensors could potentially be overcome by the emergence of commercial small-satellite platforms, like CubeSats. This research develops a snow observing framework that considers high-resolution observations in critical areas and operational tasking requests from commercial small-satellite platforms by analyzing historical SWE data from the ERA5-Land reanalysis data set. The study finds that going from 4 to 12 satellites in a constellation, not only increases the maximum SWE data observed by 170 mm/hr, but it also does it in a more cost-effective way, increasing the cost only 35%.

Small space-borne sensors are power constrained, limiting the time a primary sensor is on to collect observations and severely impacting a space mission’s scientific value. This study develops and quantitatively evaluates two sensor strategies (collaborative and land policies) that schedule when a sensor should turn on to observe convective storms, integrating the NASA GEOS-5 Nature Run data set into a simulation. The simulation runs for six months and evaluates the observation representativeness of the two strategies. The results show that the collaboration strategy represents precipitation observation 158 times better than the land strategy. The same analysis methodology can be applied to compare future policy alternatives for small satellite missions.

The New Observation Strategies Testbed (NOS-T) provides a computational platform to test, evaluate, and mature enabling technology for new Earth-observing mission concepts. NOS-T is built on an event-driven architecture where information can be shared among user-developed applications in real time via notifications of changes in state. This paper describes how a NOS-T test campaign can be developed to explore mission architectures for observing wildfires. The scenario requires four applications to model fire ignitions, a constellation of satellites for detecting fires, ground stations for receiving reports of detected fires, and a visual “scoreboard” to provide face validity and communicate observing scenarios. Test case execution results measure the distributions of fire detection and reporting time for alternative mission architectures.

We discuss the long-term evolution of an initiative being led by NASA's Earth Science Technology Office (ESTO) known as the “New Observing Strategy” [1] and describe a recent implementation of NOS in support of a virtual scientific field campaign. NOS represents a revolutionary change in the design and execution of Earth Science missions, replacing the monolithic “single satellite” approach with loosely coordinated or disaggregated, multi-platform observatories that have the potential for significant enhancement to scientific return. During late 2021 and early 2022, ES TO launched a pathfinder demonstration of NOS, in which observations of flooding events triggered by heavy rain over wildfire burn scars were intelligently targeted for collection by a numerical prediction system. The resulting “optimized” set of observations were used for characterizing deficiencies inherent in the accurate modeling of the debris flow runoff, which can result in deadly, fast-moving landslides.

A new observing strategy for floods was demonstrated and evaluated in a testbed environment. The strategy coordinates several observing platforms, including in situ and space based, to observe a flood from multiple vantage points and dynamically target predicted flood events with highresolution observations. The coordinated observations were assimilated back into the model to continuously improve forecasts and future observation selection. The demonstration shows the potential for coordinated, model-driven observing strategies and the feasibility of the NOS Testbed for demonstrating and evaluating new observing strategies.

The New Observing Strategies Testbed prototypes and evaluates new information systems technology for distributed space missions. This paper discusses the rationale and design of an event-driven architecture to integrate and orchestrate component system models. An example application case based on the FireSat mission describes environment, spacecraft, ground station, and adjudication applications orchestrated by a testbed manager. Test run results quantify key performance measures like the latency between fire ignition and detection to evaluate observing system strategies.

This work presents a methodology for evaluating remote sensing system concepts in a representative environment. A precipitation measurement mission concept evaluation is used as an application case. The simulation model leverages the NASA GEOS-5 atmospheric model to generate natural spatial and temporal distributions of key convective system variables, Candidate system concepts are simulated over a one-year period with observations determined by sensor parameters, the position of the spacecraft relative to the GEOS-5 grid points, and the nature variable values at the observation time. Concepts are evaluated by the representativeness of the collected data relative to the distributions of the selected nature variables over the simulation period. Results show that spacecraft in sun-synchronous orbits (SSO) with a 0130/1330 hours equator crossing and those with a 60° inclination orbit collect data that are most representative of precipitation and wind respectively.

Achieving new observing strategies at global and local scales must overcome engineering challenges related to decentralized control of mission elements and their models. This paper introduces concepts of co-simulation and service-oriented architectures to orchestrate individual simulation components to evaluate new mission architectures. A prototype software platform identifies essential simulation services to model the environment, mission elements, mission operations, and visualization. An example application case evaluates the detection latency for wildfire events for existing mission elements and a proposed constellation of small satellites.

Earth observing systems are undergoing an architectural transformation to perform novel scientific campaigns by dynamically composing assets from government and commercial partners. Correspondingly, campaign-level engineering methods and tools must accommodate greater degrees of decentralized control and independence. This paper reviews advances provided by semantic web technology and distributed simulation to highlight some of the challenges in modeling Earth observing systems of systems. A campaign simulation framework organizes the contextual, structural, and behavioral features necessary to model Earth observing systems from a system of systems perspective. Finally, a multi-actor value framework considers interactive negotiation of non-commensurate preferences by participating entities.

While there is growing interest in implementing future NASA Earth Science missions as Distributed Spacecraft Missions (DSMs), there are currently very few tools available to help in the design of DSMs. The objective of our project is to provide a framework that facilitates DSM Pre-Phase A investigations and optimizes DSM designs with respect to a-priori Science goals. Our Trade-space Analysis Tool for Constellations (TAT-C) enables the investigation of questions such as: “Which type of constellations should be chosen? How many spacecraft should be included in the constellation? Which design has the best cost/risk value?”. This paper provides a description of the TAT-C tool and its components.

Systems engineering activities provide an opportunity for pre-college students to engage in sophisticated engineering design practices beyond commonly-accepted limits of their capability. This research qualitatively investigates how pre-college students engaged in a systems engineering activity using LEGO EV3 robotics with three learning objectives: 1) a system can be decomposed into subsystems, 2) designers coordinate activities by communicating requirements and interfaces, and 3) testing reveals problems and changes propagate to other components. The analysis was based on methods of qualitative content analysis and employed video data produced by students to describe their robot designs as well as video data collected by the researchers. While students did not use the language of systems engineering, examples show students productively engaging in systems engineering methods that relate to each learning objective. Results suggest pre-college students are capable of understanding and implementing basic systems engineering concepts representing a more sophisticated approach to engineering design.

When computer-based tools are used for analysis of complex systems, the design of user interactions and interfaces becomes an essential part of development that determines the overall quality. The objective of this study is to investigate the processes and results of user interactions with integrated analysis tools to synthesize design implications for future tool development. In this study, two space exploration logistics tools are compared in a controlled user experiment. Through a comparative usability analysis, this study evaluated user performance and perception to provide design implications for future integrated analysis tools. For a comprehensive evaluation, multiple methods were used for data collection, including observation, questionnaire and interview. In addition to a result-oriented performance analysis, a process-oriented approach was used for analyzing patterns in user behaviors and errors. Results are presented with reference to the related features embedded in the interfaces of the two tools. Based on the comparative results, synthesized design insights for hierarchical structure, model transparency, automation, and visualization and feedback are discussed for integrated analysis tools in general.