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NASA NTRS2022

How to Build a Rover: An Overview of the Mars 2020 Mission’s Vehicle System Testbed

While NASA’s Mars rover Perseverance continues to make groundbreaking achievements on the Red Planet, its twin is hard at work here on Earth. The Operational Perseverance Twin for the Integration of Mechanisms and Instruments Sent to Mars, or OPTIMISM, is the Mars 2020 Vehicle System Testbed (VSTB) rover operated by NASA Jet Propulsion Laboratory (JPL) in Pasadena, California. OPTIMISM’s home is the JPL Mars Yard; an outdoor field with red soil that simulates the terrain encountered by Perseverance. The VSTB is a full-scale engineering model of the flight rover, serving a number of functions to ensure mission operations can continue smoothly and on schedule. The VSTB possesses instrumentation, computers, mechanisms, cameras, and a Mobility subsystem that are nearly identical to its extraterrestrial twin. Its high fidelity allows the rover to be a highly effective tool to fully test system functionality and performance prior to commanding the flight rover. The early stages of building OPTIMISM began a few months prior to Perseverance departing JPL for Cape Canaveral, FL in early 2020. Electrical integration of the flight system avionics, and compatibility checkouts of the electrical ground support equipment ensured that the foundation of the electrical system was operational and in place. Next, the internal harnessing was installed and compatibility checks of the rover instrumentation and mechanisms were performed to confirm the system was prepared for full buildup. Finally, mechanical assembly of the rover chassis with its external components completed the integration of the system before it was moved to the Mars Yard for its initial phase of testing to perform verification & validation (V&V) of the Mobility subsystem requirements. By the time Perseverance landed at Jezero Crater in February 2021, the first phase of VSTB operations was underway. Surface guidance, navigation, and control (SGNC) testing for the Mobility subsystem ensured functionality and performance requirements were met for various capabilities such as visual odometry (VO), mapping, and automatic navigation (AutoNav). Subsequent integration of the robotic arm (RA) onto the VSTB enabled the V&V campaign for surface sampling operations (SSO) to commence. As the mission’s engineering operations (EO) have gotten underway, the VSTB has been utilized for an array of purposes including troubleshooting software anomalies, and performing dry-runs for first time activities (FTAs) prior to sending the commands to Perseverance. OPTIMISM will continue to serve mission critical functions as long as Perseverance is roving the Red Planet.

Rojas, Jose Trujillo↗

NASA NTRS1983

Multifrequency measurements of the effects of soil moisture, soil texture, and surface roughness

An experiment on remote sensing of soil moisture content was conducted over bare fields with microwave radiometers at the frequencies of 1.4, 5, and 10.7 GHz, during July-September of 1981. Three bare fields with different surface roughnesses and soil textures were prepared for the experiment. The experimental results show that the effect of surface roughness is to increase the soil's brightness temperature and to reduce the slope of regression between brightness temperature and moisture content. The slopes of regression for soils with different textures are found to be comparable and the effect of soil texture is reflected in the difference of regression line intercepts at brightness-temperature axis. Measurements on wet smooth bare fields give lower brightness temperatures at 5 than at 1.4 GHz. This phenomenon is not expected from current radiative transfer theory, using laboratory measurements of the relationship between permittivity and moisture content for different soil-water mixtures at frequencies of not greater than 5 GHz.

Wang, J. R.↗

NASA NTRS2014

Comparison of SMOS and SMAP Soil Moisture Retrieval Approaches Using Tower-based Radiometer Data over a Vineyard Field

The objective of this study was to compare several approaches to soil moisture (SM) retrieval using L-band microwave radiometry. The comparison was based on a brightness temperature (TB) data set acquired since 2010 by the L-band radiometer ELBARA-II over a vineyard field at the Valencia Anchor Station (VAS) site. ELBARA-II, provided by the European Space Agency (ESA) within the scientific program of the SMOS (Soil Moisture and Ocean Salinity) mission, measures multiangular TB data at horizontal and vertical polarization for a range of incidence angles (30-60). Based on a three year data set (2010-2012), several SM retrieval approaches developed for spaceborne missions including AMSR-E (Advanced Microwave Scanning Radiometer for EOS), SMAP (Soil Moisture Active Passive) and SMOS were compared. The approaches include: the Single Channel Algorithm (SCA) for horizontal (SCA-H) and vertical (SCA-V) polarizations, the Dual Channel Algorithm (DCA), the Land Parameter Retrieval Model (LPRM) and two simplified approaches based on statistical regressions (referred to as 'Mattar' and 'Saleh'). Time series of vegetation indices required for three of the algorithms (SCA-H, SCA-V and Mattar) were obtained from MODIS observations. The SM retrievals were evaluated against reference SM values estimated from a multiangular 2-Parameter inversion approach. The results obtained with the current base line algorithms developed for SMAP (SCA-H and -V) are in very good agreement with the reference SM data set derived from the multi-angular observations (R2 around 0.90, RMSE varying between 0.035 and 0.056 m3m3 for several retrieval configurations). This result showed that, provided the relationship between vegetation optical depth and a remotely-sensed vegetation index can be calibrated, the SCA algorithms can provide results very close to those obtained from multi-angular observations in this study area. The approaches based on statistical regressions provided similar results and the best accuracy was obtained with the Saleh methods based on either bi-angular or bipolarization observations (R2 around 0.93, RMSE around 0.035 m3m3). The LPRM and DCA algorithms were found to be slightly less successful in retrieving the 'reference' SM time series (R2 around 0.75, RMSE around 0.055 m3m3). However, the two above approaches have the great advantage of not requiring any model calibrations previous to the SM retrievals.

Soil Moisture↗

DOE OSTI2023

Contrasting geochemical and fungal controls on decomposition of lignin and soil carbon at continental scale

Lignin is an abundant and complex plant polymer that may limit litter decomposition, yet lignin is sometimes a minor constituent of soil organic carbon (SOC). Accounting for diversity in soil characteristics might reconcile this apparent contradiction. Tracking decomposition of a lignin/litter mixture and SOC across different North American mineral soils using lab and field incubations, here we show that cumulative lignin decomposition varies 18-fold among soils and is strongly correlated with bulk litter decomposition, but not SOC decomposition. Climate legacy predicts decomposition in the lab, and impacts of nitrogen availability are minor compared with geochemical and microbial properties. Lignin decomposition increases with some metals and fungal taxa, whereas SOC decomposition decreases with metals and is weakly related with fungi. Decoupling of lignin and SOC decomposition and their contrasting biogeochemical drivers indicate that lignin is not necessarily a bottleneck for SOC decomposition and can explain variable contributions of lignin to SOC among ecosystems.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1973

The comparative evaluation of ERTS-1 imagery for resource inventory in land use planning

The author has identified the following significant results. Multidiscipline team interpretation and mapping of resources for Crook County is nearly complete on 1:250,000 scale enlargements of ERTS-1 imagery. Maps of geology, landforms, soils and vegetation-land use are being interpreted to show limitations, suitabilities and geologic hazards for land use planning. Mapping of lineaments and structures from ERTS-1 imagery has shown a number of features not previously mapped in Oregon. A timber inventory of Ochoco National Forest has been made. Inventory of forest clear-cutting practices has been successfully demonstrated with ERTS-1 color composites. Soil tonal differences in fallow fields shown on ERTS-1 correspond with major soil boundaries in loess-mantled terrain. A digital classification system used for discriminating natural vegetation and geologic materials classes has been successful in separation of most major classes around Newberry Cauldera, Mt. Washington and Big Summit Prairie. Computer routines are available for correction of scanner data variations; and for matching scales and coordinates between digital and photographic imagery. Methods of Diazo film color printing of computer classifications and elevation-slope perspective plots with computer are being developed.

Simonson, G. H.↗

NASA NTRS1983

Evaluation of Landsat Thematic Mapper for vegetated alluvium soils information

Landsat Thematic Mapper data acquired over Mississippi County, Arkansas, on August 22, 1982, were evaluated whether TM provides information that could be used for soil association maps and if soil properties (variability within vegetated fields) can be detected with the new bands on TM. It was found that TM data - especially the mid-IR and thermal bands - show the capability for separating vegetated soil landscapes on a broad basis. Analysis at the field level with a crop growing indicates that TM, with its additional and narrower bands and improved spatial resolution is influenced by within-field variability due to soils.

Thompson, D. R.↗

NASA NTRS1979

Analysis of surface moisture variations within large field sites

A statistical analysis was made on ground soils to define the general relationship and ranges of values of the field moisture relative to both the variance and coefficient of variation for a given test site and depth increment. The results of the variability study show that: (1) moisture variations within any given large field area are inherent and can either be controlled nor reduced; (2) neither a single value of the standard deviation nor coefficient of variation uniquely define the variability over the complete range of mean field moisture contents examined; and (3) using an upper bound standard deviation parameter clearly defines the maximum range of anticipated moisture variability. 87 percent of all large field moisture content standard deviations were less than 3 percent while about 96 percent of all the computed values had an upper bound of sigma=4 percent for these intensively sampled fields. The limit of accuracy curves of mean soil moisture measurements for large field sites relative to the required number of samples were determined.

Bell, K. R.↗

NASA NTRS1982

Multifrequency remote sensing of soil moisture

Multifrequency sensor data collected at Guymon, Oklahoma and Dalhart, Texas using NASA's C-130 aircraft were used to determine which of the all-weather microwave sensors demonstrated the highest correlation to surface soil moisture over optimal bare soil conditions, and to develop and test techniques which use visible/infrared sensors to compensate for the vegetation effect in this sensor's response to soil moisture. The L-band passive microwave radiometer was found to be the most suitable single sensor system to estimate soil moisture over bare fields. In comparison to other active and passive microwave sensors the L-band radiometer (1) was influenced least by ranges in surface roughness; (2) demonstrated the most sensitivity to soil moisture differences in terms of the range of return from the full range of soil moisture; and (3) was less sensitive to errors in measurement in relation to the range of sensor response. L-band emissivity related more strongly to soil moisture when moisture was expressed as percent of field capacity. The perpendicular vegetation index as determined from the visible/infrared sensors was useful as a measure of the vegetation effect on the L-band radiometer response to soil moisture.

Theis, S. W.↗

DOE OSTI2021

An Automatic Processing Framework for In Situ Determination of Ecohydrological Root Water Content by Ground-Penetrating Radar

This report concerns Root water content (RWC) as a vital component in water flux in soil-plant-atmosphere continuum. Knowledge of RWC helps to better understand the root function and the soil-root interaction and improves water cycle modeling. However, due to the lack of appropriate methods, field monitoring of RWC is seriously constrained. In this study, we used ground-penetrating radar (GPR), a common geophysical technique, to characterize RWC of coarse roots noninvasively. An automatic GPR data processing framework was proposed to (1) identify hyperbolic root reflections and locate roots in GPR images and (2) extract waveform parameters from the reflected wave of identified roots. These waveform parameters were then used to establish an empirical model and a semiempirical model to determine RWC. We validated the developed models using GPR root data at three antenna center frequencies (500 MHz, 900 MHz, and 2 GHz) that were produced from simulation experiments (with RWC ranging from 70% to 150%) and field experiments in sandy soils (with RWC ranging from 66% to 144%). Our results show that both the empirical and the semiempirical models achieved a good performance in estimating RWC with similar accuracy, i.e., the prediction error [root-mean-square error (RMSE)] was less than 8% for the simulation data and 12% for the field data. For both models, the accuracy of RWC estimation was the highest when applied to 2-GHz data. This study renders a new opportunity to determine RWC under field conditions that enhances the application of GPR for root study and the understanding and modeling of ecohydrology in the rhizosphere.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1983

Comparison of multispectral remote-sensing techniques for monitoring subsurface drain conditions

The following multispectral remote-sensing techniques were compared to determine the most suitable method for routinely monitoring agricultural subsurface drain conditions: airborne scanning, covering the visible through thermal-infrared (IR) portions of the spectrum; color-IR photography; and natural-color photography. Color-IR photography was determined to be the best approach, from the standpoint of both cost and information content. Aerial monitoring of drain conditions for early warning of tile malfunction appears practical. With careful selection of season and rain-induced soil-moisture conditions, extensive regional surveys are possible. Certain locations, such as the Imperial Valley, Calif., are precluded from regional monitoring because of year-round crop rotations and soil stratification conditions. Here, farms with similar crops could time local coverage for bare-field and saturated-soil conditions.

Goettelman, R. C.↗

NASA NTRS1992

Sources of nitric oxide and nitrous oxide following wetting of dry soil

A study is presented which is aimed at distinguishing among autotrophic nitrification, denitrification, and abiological processes as sources of NO and N2O production following wetting of dry soil. To distinguish among these processes, combinations of treatments in laboratory incubations of soil were used which included varying soil water content, autoclaving, C2H2 inhibition, and NO2(-) addition. Biological sources of NO and N2O commenced within minutes of wetting dry soil. Acetylene inhibition revealed that emissions of NO were dependent on nitrification, although a combination of NO2(-) production by nitrifiers and abiological reduction of NO2(-) to NO is also possible. NO emissions exceeded N2O emissions, and nitrification was the dominant source of both gases when soil water was below field capacity. It is concluded that NO emissions appear to be more important when good soil aeration favors nitrification, whereas N2O emissions appear more important when elevated soil water favors denitrification.

Davidson, Eric A.↗

NASA NTRS2009

An Evaluation of Soil Moisture Retrievals Using Aircraft and Satellite Passive Microwave Observations during SMEX02

The Soil Moisture Experiments conducted in Iowa in the summer of 2002 (SMEX02) had many remote sensing instruments that were used to study the spatial and temporal variability of soil moisture. The sensors used in this paper (a subset of the suite of sensors) are the AQUA satellite-based AMSR-E (Advanced Microwave Scanning Radiometer- Earth Observing System) and the aircraft-based PSR (Polarimetric Scanning Radiometer). The SMEX02 design focused on the collection of near simultaneous brightness temperature observations from each of these instruments and in situ soil moisture measurements at field- and domain- scale. This methodology provided a basis for a quantitative analysis of the soil moisture remote sensing potential of each instrument using in situ comparisons and retrieved soil moisture estimates through the application of a radiative transfer model. To this end, the two sensors are compared with respect to their estimation of soil moisture.

Bolten, John D.↗

NASA NTRS1984

Utilization of active microwave roughness measurements to improve passive microwave soil moisture estimates over bare soils

Multisensor aircraft data were used to establish the potential of the active microwave sensor response to be used to compensate for roughness in the passive microwave sensor's response to soil moisture. Only bare fields were used. It is found that the L-band radiometer's capability to estimate soil moisture significantly improves when surface roughness is accounted for with the scatterometers.

Theis, S. W.↗

NASA NTRS1986

Utilization of active microwave roughness measurements to improve passive microwave soil moisture estimates over bare soils

Theis, S. W.↗

NASA NTRS1981

Evaluation of HCMM data for assessing soil moisture and water table depth

Data were analyzed for variations in eastern South Dakota. Soil moisture in the 0-4 cm layer could be estimated with 1-mm soil temperatures throughout the growing season of a rainfed barley crop (% cover ranging from 30% to 90%) with an r squared = 0.81. Empirical equations were developed to reduce the effect of canopy cover when radiometrically estimating the 1-mm soil temperature, r squared = 0.88. The corrective equations were applied to an aircraft simulation of HCMM data for a diversity of crop types and land cover conditions to estimate the 0-4 cm soil moisture. The average difference between observed and measured soil moisture was 1.6% of field capacity. HCMM data were used to estimate the soil moisture for four dates with an r squared = 0.55 after correction for crop conditions. Location of shallow alluvial aquifers could be accomplished with HCMM predawn data. After correction of HCMM day data for vegetation differences, equations were developed for predicting water table depths within the aquifer (r=0.8).

Moore, D. G.↗

DOE OSTI2025

Plant Characteristics, Porewater, Gas Flux, and Soil Biogeochemistry at Council Road Site Mile Marker 71, Seward Peninsula, Alaska, 2023

Data collected at Council, AK (64°51’35.0”N 163°41’59.1”W) during a summer campaign in 2023. Water data consists of soil porewater collected by centrifuging soil cores and also by field collection with porewater samplers (rhizons). Gas data consists of CO2, CH4 and N2O surface soil fluxes measured with a portable FTIR analyzer. Plant and root data consists of biomass, root length, diameter and mass. Soil data consists of total C and N. Air, water and soil samples span two main locations: a thermokarst wetland and an upland tussock. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).This dataset was generated to broadly address the following research question: how will climate change (i.e., thawing permafrost, landscape change) alter the ecosystem flux (sink versus source) of important greenhouse gases such as CO2, CH4 and N2O?Description of the contents of this data package: This dataset contains 5 different individual .csv files containing plant, soil, water and gas data. No software is needed to utilize them. PFTCover: Plant functional type ground cover in 1x1 meter plots. SoilCores: Solidphase and porewater phase soil biogeochemical variablesPlantData: Above and belowground plant traits. GasFlux: Surface plant-soil gas measurementsFieldPorewater: Field collected porewater biogeochemical variables

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1982

Microwave remote sensing of soil moisture, volume 1

Multifrequency sensor data from NASA's C-130 aircraft were used to determine which of the all weather microwave sensors demonstrated the highest correlation to surface soil moisture over optimal bare soil conditions, and to develop and test techniques which use visible/infrared sensors to compensate for the vegetation effect in this sensor's response to soil moisture. The L-band passive microwave radiometer was found to be the most suitable single sensor system to estimate soil moisture over bare fields. The perpendicular vegetation index (PVI) as determined from the visible/infrared sensors was useful as a measure of the vegetation effect on the L-band radiometer response to soil moisture. A linear equation was developed to estimate percent field capacity as a function of L-band emissivity and the vegetation index. The prediction algorithm improves the estimation of moisture significantly over predictions from L-band emissivity alone.

Mcfarland, M. J.↗

NASA NTRS1989

Microwave remote sensing and radar polarization signatures of natural fields

Theoretical models developed for simulation of microwave remote sensing of the Earth surface from airborne/spaceborne sensors are described. Theoretical model calculations were performed and the results were compared with data of field measurements. Data studied included polarimetric images at the frequencies of P band, L band, and C band, acquired with airborne polarimeters over a agricultural field test site. Radar polarization signatures from bare soil surfaces and from tree covered fields were obtained from the data. The models developed in this report include: (1) Small perturbation model of wave scatterings from randomly rough surfaces, (2) Physical optics model, (3) Geometrical optics model, and (4) Electromagnetic wave scattering from dielectric cylinders of finite lengths, which replace the trees and branches in the modeling of tree covered field. Additionally, a three-layer emissivity model for passive sensing of a vegetation covered soil surface is also developed. The effects of surface roughness, soil moisture contents, and tree parameters on the polarization signatures were investigated.

Mo, Tsan↗