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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS1980

LACIE - An application of meteorology for United States and foreign wheat assessment

This paper describes the overall Large Area Crop Inventory Experiment technical approach utilizing the global weather-reporting network and the Landsat satellite to make a quasi-operational application of existing research results, and the accomplishments of this cooperative experiment in utilizing the weather information. Global weather data were utilized in preparing timely yield estimates for selected areas of the U.S. Great Plains, the U.S.S.R. and Canada. Additionally, wheat yield models were developed and pilot tested for Brazil, Australia, India and Argentina. The results of the work show that heading dates for wheat in North America can be predicted with an average absolute error of about 5 days for winter wheat and 4 days for spring wheat. Independent tests of wheat yield models over a 10-year period for the U.S. Great Plains produced a root-mean-square error of 1.12 quintals per hectare (q/ha) while similar tests in the U.S.S.R. produced an error of 1.31 q/ha. Research designed to improve the initial capability is described as is the rationale for further evolution of a capability to monitor global climate and assess its impact on world food supplies.

Hill, J. D.↗
NASA NTRS1981

LACIE and AgRISTARS

Involvement of the USDA in the development and use of remote sensing in support of major departmental missions began in the 1940's with the use of aerial cameras mounted in fixed wing aircraft to obtain photographs of the country's land area. Cooperation with NOAA and NASA in the large area crop inventory experiment (1974 to 1978) and results from the Illinois crop acreage experiment (1977) led to the establishment in 1978 of the AgRISTARS project program, a six-year effect to determine the usefulness, cost, and extent to which aerospace remote sensing data can be integrated into existing or future USDA systems to improve the objectivity, reliability, timeliness, and adequacy of information required to carry out agency missions. The objectives of the eight technical projects of AgRISTARS are summarized.

Moore, B. H.↗
NASA NTRS1979

Accuracy assessment in the Large Area Crop Inventory Experiment

The Accuracy Assessment System (AAS) of the Large Area Crop Inventory Experiment (LACIE) was responsible for determining the accuracy and reliability of LACIE estimates of wheat production, area, and yield, made at regular intervals throughout the crop season, and for investigating the various LACIE error sources, quantifying these errors, and relating them to their causes. Some results of using the AAS during the three years of LACIE are reviewed. As the program culminated, AAS was able not only to meet the goal of obtaining accurate statistical estimates of sampling and classification accuracy, but also the goal of evaluating component labeling errors. Furthermore, the ground-truth data processing matured from collecting data for one crop (small grains) to collecting, quality-checking, and archiving data for all crops in a LACIE small segment.

Houston, A. G.↗
NASA NTRS1980

Global crop forecasting

The needs for and remote sensing means of global crop forecasting are discussed, and key results of the Large Area Crop Inventory Experiment (LACIE) are presented. Current crop production estimates provided by foreign countries are shown often to be inadequate, and the basic elements of crop production forecasts are reviewed. The LACIE project is introduced as a proof-of-concept experiment designed to assimilate remote sensing technology, monitor global wheat production, evaluate key technical problems, modify the technique accordingly and demonstrate the feasibility of a global agricultural monitoring system. The global meteorological data, sampling and aggregation techniques, Landsat data analysis procedures and yield forecast procedures used in the experiment are outlined. Accuracy assessment procedures employed to evaluate LACIE technology performance are presented, and improvements in system efficiency and capacity during the three years of operation are pointed out. Results of LACIE estimates of Soviet, U.S. and Canadian wheat production are presented which demonstrate the feasibility and accuracy of the remote-sensing approach for global food and fiber monitoring.

Macdonald, R. B.↗
DOE OSTI2021

The genotype-phenotype landscape of an allosteric protein

Allostery is a fundamental biophysical mechanism that underlies cellular sensing, signaling, and metabolism. Yet a quantitative understanding of allosteric genotype-phenotype relationships remains elusive. Here, we report the large-scale measurement of the genotype-phenotype landscape for an allosteric protein: the lac repressor from Escherichia coli , LacI. Using a method that combines long-read and short-read DNA sequencing, we quantitatively measure the dose-response curves for nearly 10 5 variants of the LacI genetic sensor. The resulting data provide a quantitative map of the effect of amino acid substitutions on LacI allostery and reveal systematic sequence-structure-function relationships. We find that in many cases, allosteric phenotypes can be quantitatively predicted with additive or neural-network models, but unpredictable changes also occur. For example, we were surprised to discover a new band-stop phenotype that challenges conventional models of allostery and that emerges from combinations of nearly silent amino acid substitutions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Innovative Pathways: Transforming Impact Investments to Working Capital For Early Stage Cleantech Companies: Los Angeles Cleantech Incubator (January 1, 2020 to March 31, 2020)

Project Objectives: The focus for the entirety of the last quarter was on the completion of the pilot loan funding within our portfolio, and the closing out of our DOE-CAP Grant: “Innovative Pathways: Transforming Impact Investments to Working Capital for Early Stage Cleantech Companies.” The fourteenth quarter (Q14) of the program performance was also dedicated toward two main activities: the continued fundraising efforts for a formalized LACI debt fund, as well as finalization of the lending processes for pilot underwriting amongst the LACI Team and with Mission Driven Finance. This quarter marked key successes around the workflows of the DOE-CAP grant, specifically around fund capitalization efforts. Activities during the thirteenth quarter included: 1. Finalization of the DOE-CAP grant activities and work-flows; 2. Due diligence, underwriting and issuance of one (1) loan in Q1 2021 and three (3) in Q4 2020 for technology providers in grant-funded zero emissions mobility & community pilots, in partnership with LACI and local organizations, totaling ten (10) total loans; 3. Development of fundraising and marketing materials, and distribution to 30+ possible funding sources over the course of Q13 & Q14; and 4. Reinvigoration of conversations with Mission Driven Finance, the prospective underwriting partner for key activities and governance documents, and finalization of all loan processing activities once the fund is capitalized

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1975

Earth resources data analysis program, phase 3

Tasks were performed in two areas: (1) systems analysis and (2) algorithmic development. The major effort in the systems analysis task was the development of a recommended approach to the monitoring of resource utilization data for the Large Area Crop Inventory Experiment (LACIE). Other efforts included participation in various studies concerning the LACIE Project Plan, the utility of the GE Image 100, and the specifications for a special purpose processor to be used in the LACIE. In the second task, the major effort was the development of improved algorithms for estimating proportions of unclassified remotely sensed data. Also, work was performed on optimal feature extraction and optimal feature extraction for proportion estimation.

Source record↗
NASA NTRS1979

Accuracy assessment system and operation

The accuracy and reliability of LACIE estimates of wheat production, area, and yield is determined at regular intervals throughout the year by the accuracy assessment subsystem which also investigates the various LACIE error sources, quantifies the errors, and relates then to their causes. Timely feedback of these error evaluations to the LACIE project was the only mechanism by which improvements in the crop estimation system could be made during the short 3 year experiment.

Pitts, D. E.↗
NASA NTRS1979

Linear feature selection with applications

Several ways in which feature selection techniques were used in LACIE are discussed. In all cases, the methods require some a priori information and assumptions; in most, the classification procedure (Bayes optimal) was chosen in advance. The transformations used for dimensionality reduction are linear, that is, the variables in feature space are always linear combinations of the original measurements. Several numerically tractable criteria developed for LACIE, which provide information about the probability of misclassification, are discussed. Recent results on linear feature selection techniques are included. Their use in LACIE is discussed. Related open questions are mentioned.

Decell, H. P., Jr.↗
NASA NTRS1977

Development of techniques for producing static strata maps and development of photointerpretive methods based on multitemporal LANDSAT data

The results and progress of work conducted in support of the Large Area Crop Inventory Experiment (LACIE) are documented. Research was conducted for two tasks. These tasks include: (1) evaluation of the UCB static stratification procedure and modification of that procedure if warranted; and (2) the development of alternative photointerpretive techniques to the present LACIE procedure for the identification and selection of training areas for machine-processing of LACIE segments.

Colwell, R. N.↗