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NASA NTRS2018

Remote Sensing Based Yield Monitoring: Application to Winter Wheat in United States and Ukraine

Accurate and timely crop yield forecasts are critical for making informed agricultural policies and investments, as well as increasing market efficiency and stability. Earth observation data from space can contribute to agricultural monitoring, including crop yield assessment and forecasting. In this study, we present a new crop yield model based on the Difference Vegetation Index (DVI) extracted from Moderate Resolution Imaging Spectroradiometer (MODIS) data at 1 km resolution and the un-mixing of DVI at coarse resolution to a pure wheat signal (100 percent of wheat within the pixel). The model was applied to estimate the national and subnational winter wheat yield in the United States and Ukraine from 2001 to 2017. The model at the subnational level shows very good performance for both countries with a coefficient of determination higher than 0.7 and a root mean square error (RMSE) of lower than 0.6 t/ha (tonnes per hectare) (15-18 percent). At the national level for the United States (US) and Ukraine the model provides a strong coefficient of determination of 0.81 and 0.86, respectively, which demonstrates good performance at this scale. The model was also able to capture low winter wheat yields during years with extreme weather events, for example 2002 in US and 2003 in Ukraine. The RMSE of the model for the US at the national scale is 0.11 t/ha (3.7 percent) while for Ukraine it is 0.27 t/ha (8.4 percent).

DVI↗
NASA NTRS2023

The Extreme 2016 Wheat Failure in France

France suffered in 2016 the most extreme wheat yield decline in recent history, with some districts losing 55% yield. To attribute causes, we combined the largest coherent detailed wheat field experimental dataset with statistical and crop model techniques, climate information and yield physiology. The 2016 yield was composed of up to 40% fewer grains that were up to 30% lighter than expected across eight research stations in France. The flowering stage was affected by prolonged cloud cover and heavy rainfall when 31% of the loss in grain yield was incurred from reduced solar radiation and 19% from floret damage. Grain filling was also affected as 26% of grain yield loss was caused by soil anoxia, 11% by fungal foliar diseases and 10% by ear blight. Compounding climate effects caused the extreme yield decline. The likelihood of these compound factors recurring under future climate change is estimated to change with a higher frequency of extremely low wheat yields.

Extreme weather↗
NASA NTRS1977

Remote sensing-aided systems for snow qualification, evapotranspiration estimation, and their application in hydrologic models

The design of general remote sensing-aided methodologies was studied to provide the estimates of several important inputs to water yield forecast models. These input parameters are snow area extent, snow water content, and evapotranspiration. The study area is Feather River Watershed (780,000 hectares), Northern California. The general approach involved a stepwise sequence of identification of the required information, sample design, measurement/estimation, and evaluation of results. All the relevent and available information types needed in the estimation process are being defined. These include Landsat, meteorological satellite, and aircraft imagery, topographic and geologic data, ground truth data, and climatic data from ground stations. A cost-effective multistage sampling approach was employed in quantification of all the required parameters. The physical and statistical models for both snow quantification and evapotranspiration estimation was developed. These models use the information obtained by aerial and ground data through appropriate statistical sampling design.

Korram, S.↗
NASA NTRS1979

Development of LACIE CCEA-1 weather/wheat yield models

The advantages and disadvantages of the casual (phenological, dynamic, physiological), statistical regression, and analog approaches to modeling for grain yield are examined. Given LACIE's primary goal of estimating wheat production for the large areas of eight major wheat-growing regions, the statistical regression approach of correlating historical yield and climate data offered the Center for Climatic and Environmental Assessment the greatest potential return within the constraints of time and data sources. The basic equation for the first generation wheat-yield model is given. Topics discussed include truncation, trend variable, selection of weather variables, episodic events, strata selection, operational data flow, weighting, and model results.

Strommen, N. D.↗
NASA NTRS2010

Salience Assignment for Multiple-Instance Data and Its Application to Crop Yield Prediction

An algorithm was developed to generate crop yield predictions from orbital remote sensing observations, by analyzing thousands of pixels per county and the associated historical crop yield data for those counties. The algorithm determines which pixels contain which crop. Since each known yield value is associated with thousands of individual pixels, this is a multiple instance learning problem. Because individual crop growth is related to the resulting yield, this relationship has been leveraged to identify pixels that are individually related to corn, wheat, cotton, and soybean yield. Those that have the strongest relationship to a given crop s yield values are most likely to contain fields with that crop. Remote sensing time series data (a new observation every 8 days) was examined for each pixel, which contains information for that pixel s growth curve, peak greenness, and other relevant features. An alternating-projection (AP) technique was used to first estimate the "salience" of each pixel, with respect to the given target (crop yield), and then those estimates were used to build a regression model that relates input data (remote sensing observations) to the target. This is achieved by constructing an exemplar for each crop in each county that is a weighted average of all the pixels within the county; the pixels are weighted according to the salience values. The new regression model estimate then informs the next estimate of the salience values. By iterating between these two steps, the algorithm converges to a stable estimate of both the salience of each pixel and the regression model. The salience values indicate which pixels are most relevant to each crop under consideration.

Wagstaff, Kiri L.↗
NASA NTRS2006

Utilizing Calibrated GPS Reflected Signals to Estimate Soil Reflectivity and Dielectric Constant: Results from SMEX02

Extensive reflected GPS data was collected using a GPS reflectometer installed on an HC130 aircraft during the Soil Moisture Experiment 2002 (SMEX02) near Ames, Iowa. At the same time, widespread surface truth data was acquired in the form of point soil moisture profiles, areal sampling of near-surface soil moisture, total green biomass and precipitation history, among others. Previously, there have been no reported efforts to calibrate reflected GPS data sets acquired over land. This paper reports the results of two approaches to calibration of the data that yield consistent results. It is shown that estimating the strength of the reflected signals by either (1) assuming an approximately specular surface reflection or (2) inferring the surface slope probability density and associated normalization constants give essentially the same results for the conditions encountered in SMEX02. The corrected data is converted to surface reflectivity and then to dielectric constant as a test of the calibration approaches. Utilizing the extensive in-situ soil moisture related data this paper also presents the results of comparing the GPS-inferred relative dielectric constant with the Wang-Schmugge model frequently used to relate volume moisture content to dielectric constant. It is shown that the calibrated GPS reflectivity estimates follow the expected dependence of permittivity with volume moisture, but with the following qualification: The soil moisture value governing the reflectivity appears to come from only the top 1-2 centimeters of soil, a result consistent with results found for other microwave techniques operating at L-band. Nevertheless, the experimentally derived dielectric constant is generally lower than predicted. Possible explanations are presented to explain this result.

Katzberg, Stephen J.↗
NASA NTRS1984

A robust pseudo-inverse spectral filter applied to the Earth Radiation Budget Experiment (ERBE) scanning channels

Computer simulations of a least squares estimator operating on the ERBE scanning channels are discussed. The estimator is designed to minimize the errors produced by nonideal spectral response to spectrally varying and uncertain radiant input. The three ERBE scanning channels cover a shortwave band a longwave band and a ""total'' band from which the pseudo inverse spectral filter estimates the radiance components in the shortwave band and a longwave band. The radiance estimator draws on instantaneous field of view (IFOV) scene type information supplied by another algorithm of the ERBE software, and on a priori probabilistic models of the responses of the scanning channels to the IFOV scene types for given Sun scene spacecraft geometry. It is found that the pseudoinverse spectral filter is stable, tolerant of errors in scene identification and in channel response modeling, and, in the absence of such errors, yields minimum variance and essentially unbiased radiance estimates.

Avis, L. M.↗
NASA NTRS2009

New Nd-142 Evidence for a Non-Chondritic Composition of the Moon

The coupled Sm-147,146-Nd-143,142 systematics of lunar samples has been extensively studied for estimating the timescale of lunar differentiation. The published datasets yield consistent ages for Nd isotopic closure within the lunar mantle of approx.200 Myr after CAI formation. Although this time constraint is consistent with estimates derived from Hf-W chronometry of the Moon (>60 Myr after CAI formation), there is debate as to whether this age has chronological significance. Furthermore, there are discrepancies regarding the Nd isotope composition of the bulk Moon. Rankenburg et al. obtained a epsilon Nd-142 vs. Sm-147/Nd-144 correlation for lunar samples passing though the chondritic reference value (Sm-147/Nd-144 = 0.1967, epsilon Nd-142 = -0.21), suggesting that the Moon has a chondritic bulk composition. In contrast, the other datasets define a correlation line that passes approx.10-20 ppm above, suggesting that the Moon has a superchondritic Sm-147/Nd-144 (approx.0.206), close to that of the early depleted Earth (EDM). We present new Sm-Nd data for a high-Ti mare basalt (70135), two low-Ti mare basalt (LAP 02205 and MIL 05035) and a KREEPy low-Ti mare basalt (NWA 2977). These data are used to evaluate the significance of the Sm-Nd systematics for constraining the timescale of lunar differentiation and the bulk Nd isotope composition of the Moon.

Nyquist, L.↗
NASA NTRS1991

Cumulative frequency distribution of past species extinctions

Analysis of Sepkoski's compendium of the time ranges of 30,000+ taxa yields a mean duration of 28.4 ma for genera of fossil invertebrates. This converts to an average extinction rate of 3.5 percent per million years or about one percent every 286,000 years. Using survivorship techniques, these estimates can be converted to the species level, yielding a Phanerozoic average of one percent species extinction every 40,000 years. Variation in extinction rates through time is far greater than the null expectation of a homogeneous birth-death model and this reflects the well-known episodicity of extinction ranging from a few large mass extinctions to so-called background extinction. The observed variation in rates can be used to construct a cumulative frequency distribution of extinction intensity, and this distribution, in the form of a kill curve for species, shows the expected waiting times between extinction events of a given intensity. The kill curve is an average description of the extinction events of a given intensity. The kill curve is an average description of the extinction record and does not imply any cause or causes of extinction. The kill curve shows, among other things, that only about five percent of total species extinctions in the Phanerozoic were involved in the five largest mass extinctions. The other 95 percent were distributed among large and small events not normally called mass extinctions. As an exploration of the possibly absurd proposition that most past extinctions were produced by the effects of large-body impact, the kill curve for species was mapped on the comparable distribution for comet and asteroid impacts. The result is a curve predicting the species kill for a given size of impacting object (expressed as crater size). The results are reasonable in that impacts producing craters less than 30 km (diameter) cause negligible extinction but those producing craters 100-150 km (diameter) cause extinction of species in the range of 45-60 percent.

Raup, D. M.↗
NASA NTRS2015

Simulated Impacts of Climate Change on Water Use and Yield of Irrigated Sugarcane in South Africa

Reliable predictions of climate change impacts on water use, irrigation requirements and yields of irrigated sugarcane in South Africa (a water-scarce country) are necessary to plan adaptation strategies. Although previous work has been done in this regard, methodologies and results vary considerably. The objectives were (1) to estimate likely impacts of climate change on sugarcane yields, water use and irrigation demand at three irrigated sugarcane production sites in South Africa (Malelane, Pongola and La Mercy) for current (1980-2010) and future (2070-2100) climate scenarios, using an approach based on the Agricultural Model Inter-comparison and Improvement Project (AgMIP) protocols; and (2) to assess the suitability of this methodology for investigating climate change impacts on sugarcane production. Future climate datasets were generated using the Delta downscaling method and three Global Circulation Models (GCMs) assuming atmospheric CO2 concentration [CO2] of 734 ppm(A2 emissions scenario). Yield and water use were simulated using the DSSAT-Canegro v4.5 model. Irrigated cane yields are expected to increase at all three sites (between 11 and 14%), primarily due to increased interception of radiation as a result of accelerated canopy development. Evapotranspiration and irrigation requirements increased by 11% due to increased canopy cover and evaporative demand. Sucrose yields are expected to decline because of increased consumption of photo-assimilate for structural growth and maintenance respiration. Crop responses in canopy development and yield formation differed markedly between the crop cycles investigated. Possible agronomic implications of these results include reduced weed control costs due to shortened periods of partial canopy, a need for improved efficiency of irrigation to counter increased demands, and adjustments to ripening and harvest practices to counter decreased cane quality and optimize productivity. Although the Delta climate data downscaling method is considered robust, accurate and easily-understood, it does not change the future number of rain-days per month. The impacts of this and other climate data simplifications ought to be explored in future work. Shortcomings of the DSSAT-Canegro model include the simulated responses of phenological development, photosynthesis and respiration processes to high temperatures, and the disconnect between simulated biomass accumulation and expansive growth. Proposed methodology refinements should improve the reliability of predicted climate change impacts on sugarcane yield.

Climate change↗
NASA NTRS2013

Constraints on the Composition and Evolution of the Lunar Crust from Meteorite NWA 3163

The lunar meteorite NWA 3163 (paired with NWA 4881, 4483) is a ferroan, feldspathic granulitic breccia characterized by pigeonite, augite, olivine, maskelynite and accessory Tichromite, ilmenite and troilite. Bulk rock geochemical signatures indicate the lack of a KREEP- derived component (Eu/Eu* = 3.47), consistent with previously studied lunar granulites and anorthosites. Bulk rock chondrite-normalized signatures are however distinct from the anorthosites and granulites sampled by Apollo missions and are relatively REE-depleted. In-situ analyses of maskelynite reveal little variation in anorthite content (average An% is 96.9 +/- 1.6, 2 sigma). Olivine is relatively ferroan and exhibits very little variation in forsterite content with mean Fo% of 57.7 +/- 2.0 (2 sigma). The majority of pyroxene is low-Ca pigeonite (En57Fs33Wo10). Augite (En46Fs21Wo33) is less common, comprising approximately 10% of analyzed pyroxene. Two pyroxene thermometry on co-existing orthopyroxene and augite yield an equilibrium temperature of 1070C which is in reasonable agreement with temperatures of 1096C estimated from pigeonite compositions. Rb-Sr isotopic systematics of separated fractions yield an average measured Sr-87/Sr-87 of 0.699282+/-0.000007 (2 sigma). Sr model ages are calculated using a modern day Sr-87/Sr-86 Basaltic Achondrite Best Initial (BABI) value of 0.70475, from an initial BABI value Sr-87/Sr-86 of 0.69891 and a corresponding Rb-87/Sr-97 of 0.08716. The Sr model Thermomechanical analysis (TMA) age, which represents the time of separation of a melt from a source reservoir having chondritic evolution, is 4.56+/-0.1 Ga. A Sr model T(sub RD) age, which is a Rb depletion age and assumes no contribution from Rb in the sample in the calculation, yields 4.34+/-0.1 Ga (i.e. a minimum age). The Ar-Ar dating of paired meteorite NWA 4881 reveals an age of c. 2 Ga, likely representing the last thermal event this meteorite experienced. An older Ar-40/Ar-39 age of c. 3.5 Ga may record the thermal event which produced the granulitic texture. Additional chronological constraints will be provided by Sm-Nd systematics. Ferroan Anorthosites like NWA 3163 have been interpreted to represent direct lunar magma ocean (LMO) crystallization products. If this is the case, trace element concentrations in NWA 3163 primary mineral phases should be in equilibrium with residual LMO liquids present during crystallization of those phases. Results from petrogenetic modeling suggest that the NWA 3163 protolith did not form from crystallization of an initially LREE depleted LMO but rather require an initially chondritic LMO with early garnet crystallization. Furthermore, a two-stage crystallization model where plagioclase crystalized prior to pyroxene (93% vs. 99.5% of LMO crystallization) is implied.

McLeod, C. L.↗
NASA NTRS2021

Evaluation of High Mountain Asia-Land Data Assimilation System (Version 1) from 2003 to 2016, Part I: A Hyper-Resolution Terrestrial Modeling System

This first paper of the two-part series focuses on demonstrating the accuracy of a hyper-resolution, offline terrestrial modeling system used for the High Mountain Asia (HMA) region. To this end, this study systematically evaluates four sets of model simulations at point scale, basin scale, and domain scale obtained from different spatial resolutions including 0.01° (∼1-km) and 0.25° (∼25-km). The assessment is conducted via comparisons against ground-based observations and satellite-derived reference products. The key variables of interest include surface net shortwave radiation, surface net longwave radiation, skin temperature, near-surface soil temperature, snow depth, snow water equivalent, and total runoff. In the evaluation against ground-based measurements, the superiority of the 0.01° estimates are mostly demonstrated across relatively complex terrain. Specifically, hyper-resolution modeling improves the skill in meteorological forcing estimates (except precipitation) by 9% relative to coarse-resolution estimates. The model forced by downscaled forcings in its entirety yields the highest skill in model output states as well as precipitation, which improves the skill obtained by coarse-resolution estimates by 7%. These findings, on one hand, corroborate the importance of employing the hyper-resolution versus coarse-resolution modeling in areas characterized by complex terrain. On the other hand, by evaluating four sets of model simulations forced with different precipitation products, this study emphasizes the importance of accurate hyper-resolution precipitation products to drive model simulations.

Yuan Xue↗
NASA NTRS2007

Simulation Studies of Forest Structure using 3D Lidar and Radar Models

The use of lidars and radars to measure forest structure attributes such as height and biomass are being considered for future Earth Observation missions. Large footprint lidar makes a direct measurement of the heights of scatterers in the illuminated footprint and can yield information about the vertical profile of the canopy. Synthetic Aperture Radar (SAR) is known to sense the canopy volume, especially at longer wavelengths and is useful for estimating biomass. Interferometric SAR (InSAR) has been shown to yield forest canopy height information. For example, the height of scattering phase retrieved from InSAR data is considered to be correlated with the three height and the spatial structure of the forest stand. There is much interest in exploiting these technologies separately and together to get important information for carbon cycle and ecosystem science. More detailed information of the electromagnetic radiation interactions within forest canopies is needed. And backscattering models can be of much utility here. As part of a NASA funded project to explore data fusion, a three-dimensional (3D) coherent radar backscattering model and a 3D lidar backscatter models were used to investigate the use of large footprint lidar, SAR and InSAR for characterizing realistic forest scenes. For this paper, we use stem maps and other forest measurements to develop a realistic spatial structure of a spruce-hemlock forest canopy found in Maine, USA. The radar and lidar models used measurements of the 3D forest scene as input and simulated the coherent radar backscattering signature and 1064nm energy backscatter, respectively. The relationships of backscatter derived forest structure were compared with field measurements. In addition, we also had detailed airborne lidar (Laser Imaging Vegetation Sensor, LVIS) data available over the stem map sites that was used to study the accuracies of tree height derived from modeled SAR backscatter and the scattering phase center retrieved from the simulated InSAR data will be compared with the height indices, or other structure parameters derived from the lidar data. These results will address the possible synergies between lidar and radar in data in terms of forest structural information.

Sun, Guoqing↗
NASA NTRS2013

Optimized tuner selection for engine performance estimation

A methodology for minimizing the error in on-line Kalman filter-based aircraft engine performance estimation applications is presented. This technique specifically addresses the underdetermined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multi-variable iterative search routine which seeks to minimize the theoretical mean-squared estimation error. Theoretical Kalman filter estimation error bias and variance values are derived at steady-state operating conditions, and the tuner selection routine is applied to minimize these values. The new methodology yields an improvement in on-line engine performance estimation accuracy.

Simon, Donald L.↗
NASA NTRS1999

Sonic Boom Prediction and Minimization of the Douglas Reference OPT5 Configuration

Conventional CFD methods and grids do not yield adequate resolution of the complex shock flow pattern generated by a real aircraft geometry. As a result, a unique grid topology and supersonic flow solver was developed at Northrop Grumman based on the characteristic behavior of supersonic wave patterns emanating from the aircraft. Using this approach, it was possible to compute flow fields with adequate resolution several body lengths below the aircraft. In this region, three-dimensional effects are diminished and conventional two-dimensional modified linear theory (MLT) can be applied to estimate ground pressure signatures or sonic booms. To accommodate real aircraft geometries and alleviate the burdensome grid generation task, an implicit marching multi-block, multi-grid finite-volume Euler code was developed as the basis for the sonic boom prediction methodology. The Thomas two-dimensional extrapolation method is built into the Euler code so that ground signatures can be obtained quickly and efficiently with minimum computational effort suitable to the aircraft design environment. The loudness levels of these signatures can then be determined using a NASA generated noise code. Since the Euler code is a three-dimensional flow field solver, the complete circumferential region below the aircraft is computed. The extrapolation of all this field data from a cylinder of constant radius leads to the definition of the entire boom corridor occurring directly below and off to the side of the aircraft's flight path yielding an estimate for the entire noise "annoyance" corridor in miles as well as its magnitude. An automated multidisciplinary sonic boom design optimization software system was developed during the latter part of HSR Phase 1. Using this system, it was found that sonic boom signatures could be reduced through optimization of a variety of geometric aircraft parameters. This system uses a gradient based nonlinear optimizer as the driver in conjunction with a computationally efficient Euler CFD solver (NIIM3DSB) for computing the three-dimensional near-field characteristics of the aircraft. The intent of the design system is to identify and optimize geometric design variables that have a beneficial impact on the ground sonic boom. The system uses a simple wave drag data format to specify the aircraft geometry. The geometry is internally enhanced and analytic methods are used to generate marching grids suitable for the multi-block Euler solver. The Thomas extrapolation method is integrated into this system, and hence, the aircraft's centerline ground sonic boom signature is also automatically computed for a specified cruise altitude and yields the parameters necessary to evaluate the design function. The entire design system has been automated since the gradient based optimization software requires many flow analyses in order to obtain the required sensitivity derivatives for each design variable in order to converge on an optimal solution. Hence, once the problem is defined which includes defining the objective function and geometric and aerodynamic constraints, the system will automatically regenerate the perturbed geometry, the necessary grids, the Euler solution, and finally the ground sonic boom signature at the request of the optimizer.

Siclari, Michael J.↗
NASA NTRS1974

Kansas environmental and resource study: A Great Plains model. Extraction of agricultural statistics from ERTS-1 data of Kansas

The author has identified the following significant results. Wheat area, yield, and production statistics as derived from satellite image analysis, combined with a weather model, are presented for a ten county area in southwest Kansas. The data (representing the 1972-73 crop year) are compared for accuracy against both the USDA August estimate and its final (official) tabulation. The area estimates from imagery for both dryland and irrigated winter wheat were within 5% of the official figures for the same area, and predated them by almost one year. Yield on dryland wheat was estimated by the Thompson weather model to within 0.1% of the observed yield. A combined irrigated and dryland wheat production estimate for the ten county area was completed in July, 1973 and was within 1% of the production reported by USDA in February, 1974.

Morain, S. A.↗
NASA NTRS1991

A comparison of microwave techniques for measuring rainfall

The purpose of this paper is to evaluate within a common framework a large number of techniques for nearly instantaneous microwave measurements of rainfall and to determine the range of rainfall rates best suited to the various techniques and estimators. The physical basis of a technique as transformed by measurement imperfections of real instruments determines the ultimate performance capability of any microwave rain estimator. While many of the defects of the measurement process apply to all techniques, the physics behind each estimator differs. A method is presented for objectively evaluating the physical bases of the techniques and for quantifying estimator performance for perfect instruments. These results are then tempered by standard measurement errors to yield more realistic results. Analysis demonstrates that, in general, the minimization of rainfall estimate errors over a wide range of rainfall rates requires the simultaneous application of more than one microwave rainfall measurement technique.

Jameson, A. R.↗
NASA NTRS1971

Noncommunting observables in quantum detection and estimation theory

In quantum detection theory the optimum detection operators must commute; admitting simultaneous approximate measurement of noncommuting observables cannot yield a lower Bayes cost. The lower bounds on mean square errors of parameter estimates predicted by the quantum-mechanical Cramer-Rao inequality can also not be reduced by such means.

Helstrom, C. W.↗