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Landsat 9 Micrometeoroid and Orbital Debris (MMOD) Mission Success Approach

Landsat 9* (L9) is the successor mission to Landsat 8 (L8) previously known as Landsat Data Continuity Mission (LDCM). Both missions are large unmanned remote sensing satellites operating in sunsynchronous polar orbits. As opposed to L8/LDCM, systems engineers for L9 incorporated Micrometeoroid/Orbital Debris (MMOD) protection for small object collisions as part of the L9’s mission success criteria. In other words, the NASA Process for Limiting Orbital Debris (NASA-STD-8719.14A) only calls for analyses of the protection of disposal-critical hardware, but L9 opted to also assess and provide small particle penetration protections for all observatory components including instruments that are not part of the spacecraft components needed for controlled reentry. Systems engineers at Goddard developed a design process to protect against MMOD during the life of Low Earth Orbit (LEO) observatories, and in particular the Landsat 9 Mission. Simply stated, this design process enhanced the effectiveness of existing Multi-Layer Insulation (MLI) to provide the needed protection. The end goal of the design process was to establish a necessary blanket areal density for a given electronics box or instrument wall thickness and a separation between the outer MLI blanket and the structure underneath. The trade space was presented as a set of design curves for different combinations of blanket density, box wall thickness, and separation distance between MLI and structure. An advantage of this process was that it is largely independent of MMOD flux data on a surface-by surface basis. Ultimately, cost savings should result from incorporating small object penetration protection early in the design cycle, rather than adding spot shielding blankets later as needed to meet an overall penetration risk standard (the more traditional approach). The approach and implementation to the L9 Observatory design will be addressed in this paper. *L9 is a joint mission being formulated, implemented, and operated by the National Aeronautics and Space Administration (NASA) and the Department of the Interior’s (DOI) United States Geological Survey (USGS).

Approach↗

High Flying Interns: NASA's Student Airborne Research Program

The NASA Student Airborne Research Program is an annual summer internship for upper-level undergraduate STEM majors. Each summer since 2009, we have competitively selected ~30 undergraduates from colleges and universities across the United States for this unique airborne research experience. In all past summers, students flew onboard a NASA research aircraft where they assisted in the operation of remote sensing and in situ instrumentation to study the Earth, ocean, and atmosphere. Students also participated in field trips where they acquired data to ground-truth and complement the airborne data. After their flights and field trips, students then spent the rest of summer developing individual research projects using the data they collected as well as data from previous year SARP flights, other NASA airborne campaigns, and NASA satellite data. This summer, we adapted the program to be entirely online. Each of the 28 undergraduate students still completed an individual research project using data from previous SARP flights as well as publicly available data from other airborne campaigns, satellites, and/or ground stations. Students were mentored remotely by five university faculty members, five graduate students, and several additional scientists and engineers from NASA. In order to preserve some aspects of the hands-on research experience, we also shipped each student a box of twenty-four Whole Air Sampling canisters identical to what they would have used to collect air samples onboard the NASA aircraft. Instead, each student collected ground samples near their home starting in mid-April through July. The goal of this sampling was to attempt to characterize the impacts of pandemic-related changes in emissions with time across the United States. The results of that ground sampling are being presented in scientific sessions in this meeting. In addition, students also measured PM2.5 and aerosol optical depth from June through August using sensors provided by the Citizen-Enabled Aerosol Measurements for Satellites (CEAMS) at Colorado State University. We will discuss strategies we employed to conduct research online, the unexpected opportunities that arose, and lessons learned.

STEM disciplines↗

Adapting the NASA Student Airborne Research Program (SARP) to a Virtual Experience in Summer 2020

The NASA Student Airborne Research Program is a summer internship for undergraduate seniors majoring in any of the STEM disciplines. Outstanding students are selected from colleges and universities across the United States. Students fly onboard a NASA research aircraft where they assist in the operation of remote sensing and atmospheric chemistry instrumentation to study the Earth, ocean and atmosphere. This presentation discusses the results of the program over the past decade.

STEM discipline↗

Montana Water Resources: Developing a Composite Moisture Index Utilizing NASA Earth Observations for Drought Monitoring in the Missouri River Basin

The Missouri River Basin provides irrigation water for a substantial part of the domestic agricultural sector within the United States. Drought events pose a significant threat to the economic livelihoods of dependent individuals, industries, and ecosystems (e.g. farmers, local tribes, hydroelectric power, wildlife). In 2017 alone, the Missouri River Basin experienced a severe drought that resulted in a $2.6 billion loss to the U.S. Northern Plains. In response to such events, organizations throughout the basin, such as the Montana Climate Office, have dedicated efforts for drought monitoring and communicating relevant information to local stakeholders. In an effort to aid regional decision-making capabilities, the project team partnered with the Montana Climate Office, NOAA National Weather Service (NWS) Missouri Basin River Forecast Center, and NOAA Regional Climate Services, Central Region to create a monthly Composite Moisture Index (CMI) that relies on NASA Earth observations from the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) and the Soil Moisture Active Passive (SMAP) mission. From these satellites, as well as the NOAA NWS National Operational Hydrologic Remote Sensing Center’s Snow Data Assimilation System (SNODAS), our team aggregated climate datasets including soil moisture, snow cover, snow depth, and snow water equivalent to compute a CMI that indicates regional moisture conditions during the winter months. The March CMI values produced over the Missouri River headwater subbasin strongly correlate (r = 0.75) with spring and early summer stream discharge, demonstrating the use of this metric to indicate moisture conditions for the snowmelt and growing seasons.

DEVELOP Project Summary↗

Montana Water Resources: Developing a Composite Moisture Index Utilizing NASA Earth Observations for Drought Monitoring in Montana and the Missouri River Basin

The Missouri River Basin provides irrigation water for a substantial part of the domestic agricultural sector within the United States. Drought events pose a significant threat to economic livelihoods of dependent individuals, industries, and ecosystems (e.g., farmers, local tribes, hydroelectric power, wildlife). In 2017 alone, the Missouri River Basin experienced a severe drought that resulted in a $2.6 billion loss to the U.S. Northern Plains. In response to such events, organizations throughout the basin, such as the Montana Climate Office, have dedicated efforts for drought monitoring and communicating relevant information to local stakeholders. In an effort to aid regional decision-making capabilities, the project team partnered with the Montana Climate Office, NOAA National Weather Service (NWS) Missouri Basin River Forecast Center, and NOAA Regional Climate Services, Central Region to create a monthly Composite Moisture Index (CMI) that relies on NASA Earth observations from the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) and the Soil Moisture Active Passive (SMAP) mission. From these satellites, as well as the NOAA NWS National Operational Hydrologic Remote Sensing Center Snow Data Assimilation System (SNODAS), our team aggregated climate datasets including soil moisture, snow cover, snow depth, and snow water equivalent to compute a CMI that indicates regional moisture conditions during the winter months. The March CMI values produced over the Missouri River headwater subbasin strongly correlate (r = 0.75) with spring and early summer stream discharge, demonstrating the use of this metric to indicate moisture conditions for the snowmelt and growing seasons.

DEVELOP Tech Paper↗

Montana Water Resources II: Enhancing a Moisture Index for Drought and Flood Monitoring in the Missouri River Basin

The Missouri River Basin is a major global breadbasket, containing large amounts of agricultural land. Recent devastating weather events have motivated regional organizations to dedicate efforts to drought and flood monitoring and early warning systems. The DEVELOP team partnered with the following organizations: Montana Climate Office, NOAA National Weather Service (NWS) Missouri Basin River Forecast Center, NOAA Regional Climate Services of the Central Region, NOAA Physical Sciences Laboratory, and the US Army Corps of Engineers' Missouri River Basin Water Management Division. The team collaborated with the partners in their efforts to monitor flood and drought by enhancing a composite moisture index (CMI) for the Missouri River Basin. The CMI leverages NASA Earth observations to derive snow cover data from the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) mission and snow water equivalent and snowdepth datasets from the NOAA NWS National Operational Hydrologic Remote Sensing Center’s Snow Data Assimilation System (SNODAS). Building upon this framework, the team added groundwater storage data from the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On missions, soil moisture data from Soil Moisture Active Passive (SMAP), and United States Geological Survey in situ streamflow data to the CMI. To test the tool’s validity, the team compared the CMI results to historically extreme dry and extreme wet years, March 2017 and March 2019, respectively. The CMI accurately reflects both 2017 and 2019 climate conditions in the Missouri River Basin. The refined CMI enhances the understanding of antecedent soil moisture conditions and improves flood and drought forecasting in the Missouri River Basin before the growing season.

Chloe Schneider↗

Assessment of Dust Size Retrievals Based on AERONET: A Case Study of Radiative Closure From Visible-Near-Infrared to Thermal Infrared

Super-coarse dust particles (diameters >10 μm) are evidenced to be more abundant in the atmosphere than model estimates and contribute significantly to the dust climate impacts. Since super-coarse dust accounts for less dust extinction in the visible-to-near-infrared (VIS-NIR) than in the thermal infrared (TIR) spectral regime, they are suspected to be underestimated by remote sensing instruments operates only in VIS-NIR, including Aerosol Robotic Networks (AERONET), a widely used data set for dust model validation. In this study, we perform a radiative closure assessment using the AERONET-retrieved size distribution in comparison with the collocated Atmospheric Infrared Sounder (AIRS) TIR observations with comprehensive uncertainty analysis. The consistently warm bias in the comparisons suggests a potential underestimation of super-coarse dust in the AERONET retrievals due to the limited VIS-NIR sensitivity. An extra super-coarse mode included in the AERONET-retrieved size distribution helps improve the TIR closure without deteriorating the retrieval accuracy in the VIS-NIR.

thermal infrared (TIR)↗

The University of Kansas Applied Sensing Program: An operational perspective

The Kansas applied remote sensing (KARS) program conducts demonstration projects and applied research on remote sensing techniques which enable local, regional, state and federal agency personnel to better utilize available satellite and airborne remote sensing systems. As liason with Kansas agencies for the Earth Resources Laboratory (ERL), Kansas demonstration project, KARS coordinated interagency communication, field data collection, hands-on training, and follow-on technical assistance and worked with Kansas agency personnel in evaluating land cover maps provided by ERL. Short courses are being conducted to provide training in state-of-the-art remote sensing technology for university faculty, state personnel, and persons from private industry and federal government. Topics are listed which were considered in intensive five-day courses covering the acquisition, interpretation, and application of information derived through remote sensing with specific training and hands-on experience in image interpretation and the analysis of LANDSAT data are listed.

Martinko, E. A.↗

Region-based modeling algorithms for remotely-sensed data

Five algorithms being developed for performing region-based modeling operations on classified remotely-sensed images are described. The first algorithm converts images from standard grid structure into topological grid structure, while the remaining algorithms act upon topologically grid-structured images to perform region-based relabelling, overlaying, distance searching, and neighborhood scanning operations. The use of precomputed topological information, through the use of topological grid structure, makes region-based algorithms highly accessible to earth scientists.

Goldberg, M.↗

SPOT satellite family: Past, present, and future of the operations in the mission and control center

SPOT sun-synchronous remote sensing satellites are operated by CNES since February 1986. Today, the SPOT mission and control center (CCM) operates SPOT1, SPOT2, and is ready to operate SPOT3. During these seven years, the way to operate changed and the CCM, initially designed for the control of one satellite, has been modified and upgraded to support these new operating modes. All these events have shown the performances and the limits of the system. A new generation of satellite (SPOT4) will continue the remote sensing mission during the second half of the 90's. Its design takes into account the experience of the first generation and supports several improvements. A new generation of control center (CMP) has been developed and improves the efficiency, quality, and reliability of the operations. The CMP is designed for operating two satellites at the same time during launching, in-orbit testing, and operating phases. It supports several automatic procedures and improves data retrieval and reporting.

Philippe, Pacholczyk↗

Remotely Operating a Fourier Transform Spectrometer for Atmospheric Remote Sensing

This paper describes how the MkIV instrument was adapted for remote operation from the Barcroft site, where the harsh winter conditions make access difficult. Some of the main technical challenges will be discussed including, (i) operation from solar panels and batteries, (ii) cooling the detectors with LN2, (iii) instrument control and monitoring over a cellular phone, and (iv) data storage, processing and analysis. Finally, MkIV spectra measured from Barcroft and compared with those measured from JPL to highlight the advantages of the higher altitude site.

Blavier, J.-F.↗

The Texas Remote Sensing Training Project

The project was designed to train federal, state and regional agency managers, scientists and engineers. A one-week seminar was designed and implemented to build vocabulary, introduce technical subject areas and give students enough training to allow them to relate remote sensing technology to operational agency projects. The seminar was designed to perform the dual function of conveying enough remote sensing information to be of value as a stand-alone and preparing students for detailed pattern recognition training. The LARSYS III portion of the training project was executed exactly as designed in the LARSYS training materials package; the LARSYS package did not contain a LANDSAT training module. Two LANDSAT training modules were developed using Texas LANDSAT data. One module contained central Texas data and the second module contained coastal zone data.

Wells, J. B.↗

Two-Dimensional Synthetic-Aperture Radiometer

A two-dimensional synthetic-aperture radiometer, now undergoing development, serves as a test bed for demonstrating the potential of aperture synthesis for remote sensing of the Earth, particularly for measuring spatial distributions of soil moisture and ocean-surface salinity. The goal is to use the technology for remote sensing aboard a spacecraft in orbit, but the basic principles of design and operation are applicable to remote sensing from aboard an aircraft, and the prototype of the system under development is designed for operation aboard an aircraft. In aperture synthesis, one utilizes several small antennas in combination with a signal processing in order to obtain resolution that otherwise would require the use of an antenna with a larger aperture (and, hence, potentially more difficult to deploy in space). The principle upon which this system is based is similar to that of Earth-rotation aperture synthesis employed in radio astronomy. In this technology the coherent products (correlations) of signals from pairs of antennas are obtained at different antenna-pair spacings (baselines). The correlation for each baseline yields a sample point in a Fourier transform of the brightness-temperature map of the scene. An image of the scene itself is then reconstructed by inverting the sampled transform. The predecessor of the present two-dimensional synthetic-aperture radiometer is a one-dimensional one, named the Electrically Scanned Thinned Array Radiometer (ESTAR). Operating in the L band, the ESTAR employs aperture synthesis in the cross-track dimension only, while using a conventional antenna for resolution in the along-track dimension. The two-dimensional instrument also operates in the L band to be precise, at a frequency of 1.413 GHz in the frequency band restricted for passive use (no transmission) only. The L band was chosen because (1) the L band represents the long-wavelength end of the remote- sensing spectrum, where the problem of achieving adequate spatial resolution is most critical and (2) imaging airborne instruments that operate in this wavelength range and have adequate spatial resolution are difficult to build and will be needed in future experiments to validate approaches for remote sensing of soil moisture and ocean salinity. The two-dimensional instrument includes a rectangular array of patch antennas arranged in the form of a cross. The ESTAR uses analog correlation for one dimension, whereas the two-dimensional instrument uses digital correlation. In two dimensions, many more correlation pairs are needed and low-power digital correlators suitable for application in spaceborne remote sensing will help enable this technology. The two-dimensional instrument is dual-polarized and, with modification, capable of operating in a polarimetric mode. A flight test of the instrument took place in June 2003 and it participated in soil moisture experiments during the summers of 2003 and 2004.

LeVine, David M.↗

Geography program, design, structure and operational strategy

The geography program is designed to move systematically toward a capability to increase remote sensing data into operational systems for monitoring land use and related environmental change. The problems of environmental imbalance arising from rapid urbanization and other dramatic changes in land use are considered. These overall problems translate into working level problems of establishing the validity of various sensor-data combinations that will best obtain the regional land use and environmental information. The goal, to better understand, predict, and assist policy makers to regulate urban and regional land use changes resulting from population growth and technological advancement, is put forth.

Alexander, R. H.↗

Operational considerations for the application of remotely sensed forest data from LANDSAT or other airborne platforms

Research in the application of remotely sensed data from LANDSAT or other airborne platforms to the efficient management of a large timber based forest industry was divided into three phases: (1) establishment of a photo/ground sample correlation, (2) investigation of techniques for multi-spectral digital analysis, and (3) development of a semi-automated multi-level sampling system. To properly verify results, three distinct test areas were selected: (1) Jacksonville Mill Region, Lower Coastal Plain, Flatwoods, (2) Pensacola Mill Region, Middle Coastal Plain, and (3) Mississippi Mill Region, Middle Coastal Plain. The following conclusions were reached: (1) the probability of establishing an information base suitable for management requirements through a photo/ground double sampling procedure, alleviating the ground sampling effort, is encouraging, (2) known classification techniques must be investigated to ascertain the level of precision possible in separating the many densities involved, and (3) the multi-level approach must be related to an information system that is executable and feasible.

Baker, G. R.↗

Sense and Avoid Safety Analysis for Remotely Operated Unmanned Aircraft in the National Airspace System. Version 5

This document describes a method to demonstrate that a UAS, operating in the NAS, can avoid collisions with an equivalent level of safety compared to a manned aircraft. The method is based on the calculation of a collision probability for a UAS , the calculation of a collision probability for a base line manned aircraft, and the calculation of a risk ratio given by: Risk Ratio = P(collision_UAS)/P(collision_manned). A UAS will achieve an equivalent level of safety for collision risk if the Risk Ratio is less than or equal to one. Calculation of the probability of collision for UAS and manned aircraft is accomplished through event/fault trees.

Carreno, Victor↗