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NASA NTRS1990

Bidirectional measurements of surface reflectance for view angle corrections of oblique imagery

An apparatus for acquiring bidirectional reflectance-factor data was constructed and used over four surface types. Data sets were obtained over a headed wheat canopy, bare soil having several different roughness conditions, playa (dry lake bed), and gypsum sand. Results are presented in terms of relative bidirectional reflectance factors (BRFs) as a function of view angle at a number of solar zenith angles, nadir BRFs as a function of solar zenith angles, and, for wheat, vegetation indices as related to view and solar zenith angles. The wheat canopy exhibited the largest BRF changes with view angle. BRFs for the red and the NIR bands measured over wheat did not have the same relationship with view angle. NIR/Red ratios calculated from nadir BRFs changed by nearly a factor of 2 when the solar zenith angle changed from 20 to 50 degs. BRF versus view angle relationships were similar for soils having smooth and intermediate rough surfaces but were considerably different for the roughest surface. Nadir BRF versus solar-zenith angle relationships were distinctly different for the three soil roughness levels. Of the various surfaces, BRFs for gypsum sand changed the least with view angle (10 percent at 30 degs).

Jackson, R. D.↗

NASA NTRS1996

Ethylene Production by Plants in a Closed Environment

Ethylene production by 20-sq m stands of wheat, soybean, lettuce and potato was monitored throughout growth and development in NASA's Controlled Ecological Life Support System (CELSS) Biomass Production Chamber. Chamber ethylene concentrations rose during periods of rapid growth for all four species, reaching 120 parts per billion (ppb) for wheat, 60 ppb for soybean, and 40 to 50 ppb for lettuce and potato. Following this, ethylene concentrations declined during seed fill and maturation (wheat and soybean), or remained relatively constant (potato). Lettuce plants were harvested during rapid growth and peak ethylene production. The highest ethylene production rates (unadjusted for chamber leakage) ranged from 0.04 to 0.06 ml/sq m/day during rapid growth of lettuce and wheat stands, or approximately 0.8 to 1.1 ml/g fresh weight/h. Results suggest that ethylene production by plants is a normal event coupled to periods of rapid metabolic activity, and that ethylene removal or control measures should be considered for growing crops in a tightly closed CELSS.

Wheeler, R. M.↗

NASA NTRS2003

Method for the control of NOx emissions in long-range space travel

The wheat straw, an inedible biomass that can be continuously produced in a space vehicle has been used to produce activated carbon for effective control of NOx emissions from the incineration of wastes. The optimal carbonization temperature of wheat straw was found to be around 600 degrees C when a burnoff of 67% was observed. The BET surface area of the activated carbon produced from the wheat straw reached as high as 300 m2/g. The presence of oxygen in flue gas is essential for effective adsorption of NO by activated carbon. On the contrary, water vapor inhibits the adsorption efficiency of NO. Consequently, water vapor in flue gas should be removed by drying agents before adsorption to ensure high NO adsorption efficiency. All of the NO in the flue gas was removed for more than 2 h by the activated carbons when 10% oxygen was present and the ratio of carbon weight to the flue gas flow rate (W/F) was 30 g min/L, with a contact time of 10.2 s. All of NO was reduced to N2 by the activated carbon at 450 degrees C with a W/F ratio of 15 g min/L and a contact time of 5.1 s. Reduction of the adsorbed NO also regenerated the activated carbon, and the regenerated activated carbon exhibited an improved NO adsorption efficiency. However, the reduction of the adsorbed NO resulted in a loss of carbon which was determined to be about 0.99% of the activated carbon per cycle of regeneration. The sufficiency of the amount of wheat straw in providing the activated carbon based on a six-person crew, such as the mission planned for Mars, has been determined. This novel approach for the control of NOx emissions is sustainable in a closed system such as the case in space travel. It is simple to operate and is functional under microgravity environment.

NASA Discipline Life Support Systems↗

NASA NTRS2000

Pythium invasion of plant-based life support systems: biological control and sources

Invasion of plant-based life support systems by plant pathogens could cause plant disease and disruption of life support capability. Root rot caused by the fungus, Pythium, was observed during tests of prototype plant growth systems containing wheat at the Kennedy Space Center (KSC). We conducted experiments to determine if the presence of complex microbial communities in the plant root zone (rhizosphere) resisted invasion by the Pythium species isolated from the wheat root. Rhizosphere inocula of different complexity (as assayed by community-level physiological profile: CLPP) were developed using a dilution/extinction approach, followed by growth in hydroponic rhizosphere. Pythium growth on wheat roots and concomitant decreases in plant growth were inversely related to the complexity of the inocula during 20-day experiments in static hydroponic systems. Pythium was found on the seeds of several different wheat cultivars used in controlled environmental studies, but it is unclear if the seed-borne fungal strain(s) were identical to the pathogenic strain recovered from the KSC studies. Attempts to control pathogens and their effects in hydroponic life support systems should include early inoculation with complex microbial communities, which is consistent with ecological theory.

NASA Discipline Life Support Systems↗

NASA NTRS1998

Six-month space greenhouse experiments--a step to creation of future biological life support systems

SVET Space Greenhouse (SG)--the first automated facility for growing of higher plants in microgravity was designed in the eighty years to be used for the future BLSS. The first successful experiment with vegetables was carried out in 1990 on the MIR Space Station (SS). The experiments in SVET SG were resumed in 1995, when an American Gas Exchange Measurement System (GEMS) was added. A three-month wheat experiment was carried out as part of MIR-SHUTTLE'95 program. SVET-2 SG Bulgarian equipment of a new generation with optimised characteristics was developed (financed by NASA). The new SVET-GEMS equipment was launched on board the MIR SS and a successful six-month experiments for growing up of two crops of wheat were conducted in 1996 - 97 as part of MIR-NASA-3 program. The first of these "Greenhouse" experiments (123 days) with the goal to grow wheat through a complete life cycle is described. Nearly 300 heads developed but no seeds were produced. A second crop of wheat was planted and after 42 days the plants were frozen for biochemical investigations. The main environmental parameters during the six-month experiments in SVET (substrate moisture and lighting period) are given. The results and the contribution to BLSS are discussed.

long duration↗

NASA NTRS1996

Volatile organic compounds detected in the atmosphere of NASA's Biomass Production Chamber

Atmospheres of enclosed environments in which 20 m2 stands of wheat, potato, and lettuce were grown were characterized and quantified by gas chromatography-mass spectrometry. A large number (in excess of 90) of volatile organic compounds (VOCs) were identified in the chambers. Twenty eight VOC's were assumed to be of biogenic origin for these were not found in the chamber atmosphere when air samples were analyzed in the absence of plants. Some of the compounds found were unique to a single crop. For example, only 35% of the biogenic compounds detected in the wheat atmosphere were unique to wheat, while 36% were unique to potato and 26% were unique to lettuce. The number of compounds detected in the wheat (20 compounds) atmosphere was greater than that of potato (11) and lettuce (15) and concentration levels of biogenic and non-biogenic VOC's were similar.

NASA Discipline Number 61-20↗

NASA NTRS2006

Closure of Regenerative Life Support Systems: Results of the Lunar-Mars Life Support Test Project

Future long duration human exploration missions away from Earth will require closed-loop regenerative life support systems to reduce launch mass, reduce dependency on resupply and increase the level of mission self sufficiency. Such systems may be based on the integration of biological and physiocochemical processes to produce potable water, breathable atmosphere and nutritious food from metabolic and other mission wastes. Over the period 1995 to 1998 a series of ground-based tests were conducted at the National Aeronautics and Space Administration, Johnson Space Center, to evaluate the performance of advanced closed-loop life support technologies with real human metabolic and hygiene loads. Named the Lunar-Mars Life Support Test Project (LMLSTP), four integrated human tests were conducted with increasing duration, complexity and closure. The first test, LMLSTP Phase I, was designed to demonstrate the ability of higher plants to revitalize cabin atmosphere. A single crew member spent 15 days within an atmospherically closed chamber containing 11.2 square meters of actively growing wheat. Atmospheric carbon dioxide and oxygen levels were maintained by control of the rate of photosynthesis through manipulation of light intensity or the availability of carbon dioxide and included integrated physicochemical systems. During the second and third tests, LMLSTP Phases II & IIa, four crew members spent 30 days and 60 days, respectively, in a larger sealed chamber. Advanced physicochemical life support hardware was used to regenerate the atmosphere and produce potable water from wastewater. Air revitalization was accomplished by using a molecular sieve and a Sabatier processor for carbon dioxide absorption and reduction, respectively, with oxygen generation performed by water hydrolysis. Production of potable water from wastewater included urine treatment (vapor compression distillation), primary treatment (ultrafiltration/reverse osmosis and multi-filtration) and post processing. For the Phase II test the water recovery rate ranged from 95 to 98%, depending on the processor. LMLSTP Phase III, the fourth test of the series, had a duration of 91 days and included four crew members. The test demonstrated an integration of physicochemical and biological technologies for air revitalization, water recovery and waste processing. Wheat supplemented the physicochemical air revitalization systems by providing approximately 25% of the oxygen required for the 4-person crew. The water recovery system included immobilized cell and trickling filter bioreactors for primary water treatment, reverse osmosis and air evaporation systems for secondary water treatment, followed by post processing. The 8 day initial supply of water was recycled through the chamber and crew 10 times over the course of the test. Grain from the wheat together with fresh lettuce from a small growth chamber within the crew chamber provided supplementation to the stored food system, but at a level less than 5% of the crew s caloric requirement. An incinerator was used to demonstrate mineralization of the crew s solid waste, with the combustion products (mainly carbon dioxide) returned to the wheat for conversion to oxygen.

Barta, Daniel↗

NASA NTRS2018

Soil Organic Carbon and Nitrogen Feedbacks on Crop Yields Under Climate Change

A critical omission from climate change impact studies on crop yield is the interaction between soil organic carbon (SOC), nitrogen (N) availability, and carbon dioxide (CO2). We used a multimodel ensemble to predict the effects of SOC and N under different scenarios of temperatures and CO2 concentrations on maize (Zea mays L.) and wheat (Triticum aestivum L.) yield in eight sites across the world. We found that including feedbacks from SOC and N losses due to increased temperatures would reduce yields by 13% in wheat and 19% in maize for a 3°C rise temperature with no adaptation practices. These losses correspond to an additional 4.5% (+3°C) when compared to crop yield reductions attributed to temperature increase alone. Future CO2 increase to 540 ppm would partially compensate losses by 80% for both maize and wheat at +3°C, and by 35% for wheat and 20% for maize at +6°C, relative to the baseline CO2 scenario.

Basso, B.↗

NASA NTRS2021

USA Crop Yield Estimation with MODIS NDVI: Are Remotely Sensed Models Better Than Simple Trend Analyses?

Crop yield forecasting is performed monthly during the growing season by the United States Department of Agriculture’s National Agricultural Statistics Service. The underpinnings are long-established probability surveys reliant on farmers’ feedback in parallel with biophysical measurements. Over the last decade though, satellite imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) has been used to corroborate the survey information. This is facilitated through the Global Inventory Modeling and Mapping Studies/Global Agricultural Monitoring system, which provides open access to pertinent real-time normalized difference vegetation index (NDVI) data. Hence, two relatively straightforward MODIS-based modeling methods are employed operationally. The first model constitutes mid-season timing based on the maximum peak NDVI value, while the second is reflective of late-season timing by integrating accumulated NDVI over a threshold value. Corn model results nationally show the peak NDVI method provides a R^(2) of 0.88 and a coefficient of variation (CV) of 3.5%. The accumulated method, using an optimally derived 0.58 NDVI threshold, improves the performance to 0.93 and 2.7%, respectively. Both these models outperform simple trend analysis, which is 0.48 and 7.4%, correspondingly. For soybeans the R^(2) results of the peak NDVI model are 0.62, and 0.73 for the accumulated using a 0.56 threshold. CVs are 6.8% and 5.7%, respectively. Spring wheat’s R2performance with the accumulated NDVI model is 0.60 but just 0.40 with peak NDVI. The soybean and spring wheat models perform similarly to trend analysis. Winter wheat and upland cotton show poor model performance, regardless of method. Ultimately, corn yield forecasting derived from MODIS imagery is robust, and there are circumstances when forecasts for soybeans and spring wheat have merit too.

crop yield↗

NASA NTRS2018

Remote Sensing of Evapotranspiration over the Central Arizona Irrigation and Drainage District, USA

Knowledge of baseline water use for irrigated crops in the U.S. Southwest is important for understanding how much water is consumed under normal farm management and to help manage scarce resources. Remote sensing of evapotranspiration (ET) is an effective way to gain that knowledge: multispectral data can provide synoptic and time-repetitive estimates of crop-specific water use, and could be especially useful for this arid region because of dominantly clear skies and minimal precipitation. Although multiple remote sensing ET approaches have been developed and tested, there is not consensus on which of them should be preferred because there are still few intercomparison studies within this environment. To help build the experience needed to gain consensus, a remote sensing study using three ET models was conducted over the Central Arizona Irrigation and Drainage District (CAIDD). Aggregated ET was assessed for 137 wheat plots (winter/spring crop), 183 cotton plots (summer crop), and 225 alfalfa plots (year-round). The employed models were the Satellite-Based Energy Balance for Mapping Evapotranspiration with Internalized Calibration (METRIC), the Two Source Energy Balance (TSEB), and Vegetation Index ET for the US Southwest (VISW). Remote sensing data were principally Landsat 5, supplemented by Landsat 7, MODIS Terra, MODIS Aqua, and ASTER. Using district-wide model averages, seasonal use (excluding surface evaporation) was 742 mm (millimeters) for wheat, 983 mm for cotton, and 1427 mm for alfalfa. All three models produced similar daily ET for wheat, with 6-8 mm per day mid-season. Model estimates diverged for cotton and alfalfa sites. Considering ET over cotton, TSEB estimates were 9.5 mm per day, METRIC 6 mm per day, and VISW 8 mm per day. For alfalfa, the ET values from TSEB were 8.0 mm per day, METRIC 5 mm per day, and VISW 6 mm per day. Lack of local validation information unfortunately made it impossible to rank model performance. However, by averaging results from all of them, ET model outliers could be identified. They ranged from minus 10 percent to plus 18 percent, values that represent expected ET modeling discrepancies. Relative to the model average, standardized ET-estimators - potential ET (ET (sub 0)), FAO-56 ET, and USDA-SW gravimetric-ET - showed still greater deviations, up to 35 percent of annual crop water use for summer and year-round crops, suggesting that remote sensing of actual ET could lead to significantly improved estimates of crop water use. Results from this study highlight the need for conducting multi-model experiments during summer-months over sites with independent ground validation.

Alfalfa↗

NASA NTRS2022

Global Gridded Crop Models Underestimate Yield Responses to Droughts and Heatwaves

Extreme events can lead to crop yield declines, resulting in financial losses and threats to food security, and the frequency and intensity of such events is projected to increase. As global gridded crop models (GGCMs) are commonly used to assess climate change impacts on agricultural yields, there is a need to understand whether these models are able to reproduce the observed yield declines. We evaluated 13 GGCMs from the Inter-Sectoral Impact Model Intercomparison Project and compared observed and simulated impact of past droughts and heatwaves on yields for four crops (maize, rice, soy, wheat). We found that most models detect but underestimate the impact of droughts and heatwaves on yield. Specifically, the drought signal was detected by 12 of 13 models for maize and all models for wheat, while the heat signal was detected by eleven models for maize and six models for wheat. To investigate whether the difference between simulated and observed yield declines is due to a misrepresentation of simulated exposure to heat or water scarcity (i.e. misrepresentation of growing season), we analysed the relationship between average discrepancies between observed and simulated yield losses, and average simulated exposure to extreme weather conditions across all crop models. We found a positive correlation between simulated exposure to heat and model performance for heatwaves, but found no correlation for droughts. This suggests that there is a systematic underestimation of yield responses to heat and drought and not only a misrepresentation of exposure. Assuming that performance for the past indicates models' capacity to project future yield impacts, models likely underestimate future yield decline from climate change. High-quality temporally and spatially resolved observational data on growing seasons will be highly valuable to further improve crop models' capacity to adequately respond to extreme weather events.

extreme events↗

NASA NTRS1970

Analysis of remote sensing data for evaluation of vegetation resources

Research has centered around: (1) completion of a study on the use of remote sensing techniques as an aid to multiple use management; (2) determination of the information transfer at various image resolution levels for wildland areas; and (3) determination of the value of small scale multiband, multidate photography for the analysis of vegetation resources. In addition, a substantial effort was made to upgrade the automatic image classification and spectral signature acquisition capabilities of the laboratory. It was found that: (1) Remote sensing techniques should be useful in multiple use management to provide a first-cut analysis of an area. (2) Imagery with 400-500 feet ground resolvable distance (GRD), such as that expected from ERTS-1, should allow discriminations to be made between woody vegetation, grassland, and water bodies with approximately 80% accuracy. (3) Barley and wheat acreages in Maricopa County, Arizona could be estimated with acceptable accuracies using small scale multiband, multidate photography. Sampling errors for acreages of wheat, barley, small grains (wheat and barley combined), and all cropland were 13%, 11%, 8% and 3% respectively.

Source record↗

NASA NTRS1973

Kansas environmental and resource study: A Great Plains model

The author has identified the following significant results. Improvement in the land use classification accuracy of ERTS-1 MSS multi-images over Kansas can be made using two distances between neighboring grey tone N-tuples instead of one distance. Much more information is contained texturally than spectrally on the Kansas image. Ground truth measurements indicate that reflectance ratios of the 545 and 655 nm wavebands provide an index of plant development and possibly physiological stress. Preliminary analysis of MSS 4 and 5 channels substantiate the ground truth interpretation. Results of the land use mapping experiment indicate that ERTS-1 imagery has major potential in regionalization. The ways in which land is utilized within these regions may then be studied more effectively than if no adequate regionalization is available. A model for estimating wheat yield per acre has been applied to acreage estimates derived from ERTS-1 imagery to project the 1973 wheat yields for a ten county area in southwest Kansas. The results are within 3% of the preharvest estimates for the same area prepared by the USDA. Visual identification of winter wheat is readily achieved by using a temporal sequence of images. Identification can be improve by stratifying the project area into subregions having more or less homogeneous agricultural practices and crop mixes.

Haralick, R. M.↗

NASA NTRS1974

Statistical theory and methodology for remote sensing data analysis

A model is developed for the evaluation of acreages (proportions) of different crop-types over a geographical area using a classification approach and methods for estimating the crop acreages are given. In estimating the acreages of a specific croptype such as wheat, it is suggested to treat the problem as a two-crop problem: wheat vs. nonwheat, since this simplifies the estimation problem considerably. The error analysis and the sample size problem is investigated for the two-crop approach. Certain numerical results for sample sizes are given for a JSC-ERTS-1 data example on wheat identification performance in Hill County, Montana and Burke County, North Dakota. Lastly, for a large area crop acreages inventory a sampling scheme is suggested for acquiring sample data and the problem of crop acreage estimation and the error analysis is discussed.

Odell, P. L.↗

NASA NTRS1974

The value of improved (ERS) information based on domestic distribution effects of U.S. agriculture crops

The value of improving information for forecasting future crop harvests was investigated. Emphasis was placed upon establishing practical evaluation procedures firmly based in economic theory. The analysis was applied to the case of U.S. domestic wheat consumption. Estimates for a cost of storage function and a demand function for wheat were calculated. A model of market determinations of wheat inventories was developed for inventory adjustment. The carry-over horizon is computed by the solution of a nonlinear programming problem, and related variables such as spot and future price at each stage are determined. The model is adaptable to other markets. Results are shown to depend critically on the accuracy of current and proposed measurement techniques. The quantitative results are presented parametrically, in terms of various possible values of current and future accuracies.

Bradford, D. F.↗

NASA NTRS1975

The use of ERTS-1 multispectral imagery for crop identification in a semi-arid climate

Crop identification using multispectral satellite imagery and multivariate pattern recognition was used to identify wheat accurately in Greeley County, Kansas. A classification accuracy of 97 percent was found for wheat and the wheat estimate in hectares was within 5 percent of the USDA's Statistical Reporting Service estimate for 1973. The multispectral response of cotton and sorghum in Texas was not unique enough to distinguish between them nor to separate them from other cultivated crops.

Stockton, J. G.↗

NASA NTRS1976

Large Area Crop Inventory Experiment (LACIE). Phase 1: Evaluation report

It appears that the Large Area Crop Inventory Experiment over the Great Plains, can with a reasonable expectation, be a satisfactory component of a 90/90 production estimator. The area estimator produced more accurate area estimates for the total winter wheat region than for the mixed spring and winter wheat region of the northern Great Plains. The accuracy does appear to degrade somewhat in regions of marginal agriculture where there are small fields and abundant confusion crops. However, it would appear that these regions tend also to be marginal with respect to wheat production and thus increased area estimation errors do not greatly influence the overall production estimation accuracy in the United States. The loss of segments resulting from cloud cover appears to be a random phenomenon that introduces no significant bias into the estimates. This loss does increase the variance of the estimates.

Source record↗

NASA NTRS1976

Large Area Crop Inventory Experiment (LACIE). Results of LACIE integrated drought analysis (Southern U.S. Great Plains drought 1975-76)

The development and intensification of the drought in the United States southern Great Plains was monitored during the initial growing period of the 1975-76 winter wheat crop. Because of the severity of the drought conditions, a drought analysis plan was developed and implemented beginning on March 8, 1976. Sample segments and full-frame imagery were used at 9-day intervals to identify the drought area and quantify the effects on the wheat acreage. Yield model simulations were run to extrapolate the effects of the drought on yield estimates at harvest, assuming 10 and 90 percent of normal rainfall for subsequent months and 30-day forecast. A survey of LANDSAT data for improvement of distribution of rainfall patterns in the drought area was done for April and yield models run for drought affected crop reporting districts. Special aggregations were performed by the Crop Assessment Subsystem on the drought area to evaluate the utility of remote sensing to monitor the effect of the drought on wheat area, yield, and production.

Thompson, D. R.↗