SEARCH · Engineering Papers
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
The procedure is described which was used to train automatic data processing (ADP) analysts to process ERTS 1 imagery from a 5 nm by 6 nm area in Delisle, Canada, and to estimate wheat acreage using training fields provided by photointerpreters. The exercise also served to evaluate and test current large area crop inventory experiment (LACIE) procedures.
Given the swath table files, the segment set for one country and cloud cover data, the SAGE program determines how many times and under what conditions each segment is accessed by satellites. The program writes a record for each segment on a data file which contains the pertinent acquisition data. The weather data file can also be generated from a NASA supplied tape. The Segment Acquisition Selector Program (SACS) selects data from the segment reference file based upon data input manually and from a crop window file. It writes the extracted data to a data acquisition file and prints two summary reports. The POUT program reads from associated LACIE files and produces printed reports. The major types of reports that can be produced are: (1) Substrate Reference Data Reports, (2) Population Mean, Standard Deviation and Histogram Reports, (3) Histograms of Monte Carlo Statistics Reports, and (4) Frequency of Sample Segment Acquisitions Reports.
A Large Area Crop Inventory Experiment (LACIE) was undertaken to prove out an economically important application of remote sensing from space. The experiment focused upon determination of wheat acreages in the U.S. Great Plains and upon the development and testing of yield models. The results and conclusions are presented.
The Large Area Crop Inventory Experiment (LACIE) is a project designed to demonstrate the applicability of remote sensing technology to monitor globally an important world food crop - wheat. The need for more timely and reliable monitoring of food and fiber supplies is discussed, and the monitoring systems currently utilized are reviewed. The fundamentals involved in assessing the impact of variable weather and economic conditions on wheat acreage, yield, and production are elucidated. The experiment's approach to production monitoring is described, and its status is reviewed. Examples of acreage and yield monitoring in the Soviet Union are used to illustrate the experiment's approach.
The Large Area Crop Inventory Experiment (LACIE) is a 'proof of concept' project designed to demonstrate the applicability of remote sensing technology to the global monitoring of wheat. This paper discusses the need for more timely and reliable monitoring of food and fiber supplies, reviews the monitoring systems currently utilized by the USDA and United Nations Food and Agriculture Organization in the United States and in foreign countries, and elucidates the fundamentals involved in assessing the impact of variable weather and economic conditions on wheat acreage, yield, and production. The experiment's approach to production monitoring is described briefly, and its status is reviewed as of the conclusion of 2 years of successful operation. Examples of acreage and yield monitoring in the Soviet Union are used to illustrate the experiment's approach.
The author has identified the following significant results. The stratification procedure in the new sampling strategy for LACIE included: (1) correlation test results indicating that an agrophysical stratum may be homogeneous with respect to agricultural density, but not with respect to wheat density; and (2) agrophysical unit homogeneity test results indicating that with respect to agricultural density many agrophysical units are not homogeneous, but removal of one or more refined strata from any such current agrophysical unit can make the strata homogeneous. The apportioning procedure results indicated that the current procedure is not performing well and that the apportioned estimates of refined strata wheat area are often unreliable.
A technology assessment of the LACIE data processing and information systems was discussed during the Large Area Crop Inventory Experiment Symposium. Crop inventories of wheat yield in the United States as well as several other nations (such as the U.S.S.R., Canada, etc.) were discussed, along with the methodology involved in acquiring this data.
The author has identified the following significant results. Both the accuracy and efficiency with which LACIE crop survey estimates were made have shown significant improvement in three years. In the U.S. and U.S.S.R. winter wheat regions, the original accuracy goals were met or exceeded, with 90/90 estimates achieved in the United States 1.5 to 2 months before harvest. Additionally, all available accuracy parameters indicate 90/90 estimates for the U.S.S.R. total crop. Key technology problems were identified during phase 2 with spring wheat in the United States and Canada which prevented the attainment of 90/90 accuracies in these regions. Technology solutions developed and tested in phase 3 partly resolved these issues with a significant improvement realized in the accuracy of the spring wheat area estimates.
Tables, charts, and LACIE segments are used to demonstrate the accuracy of estimated crop conditions and yield from 1974 to 1976, and to demonstrate the benefits of meteorological and LANDSAT data. Developments in data acquisition, sampling, and reduction are reviewed. The USDA application test system is highlighted with emphasis on user requirements, technology transfer, data base design, and cost data models for data base operation and management.
The author has identified the following significant results. The green number and brightness scatter plots, channel plots of radiance values, and visual study of the imagery indicate separability between barley and spring wheat/oats during the wheat mid-heading to mid-ripe stages. In the LACIE Phase 3 North Dakota data set, the separation time is more specifically the wheat soft dough stage. At this time, the barley is ripening, and is therefore, less green and brighter than the wheat. Only 4 of the 18 segments studied indicate separation of barley/other spring small grain, even though 11 of the segments have acquisitions covering the wheat soft dough stage. The remaining seven segments had less than 5 percent barley based on ground truth data.
An approximately 2% sampling error was achieved in LACIE by sampling only approximately 2% of the sampling frame. The sample design in the yardstick region for which historical data were available down to a substratum level to support missing data resulting from cloud cover provided the most accurate estimate possible. The implemented strategy provided data of sufficient quality and quantity to support required performance levels and also to satisfy the existing constraints. The allocation scheme appeared to provide the most efficient usage of the available data and gave segment coverage of major producing areas and thus improved the probability of an accurate estimate.
The sampling design in LACIE consisted of two major components, one for wheat acreage estimation and one for wheat yield prediction. The acreage design was basically a classical survey for which the sampling unit was a 5- by 6-nautical mile segment; however, there were complications caused by measurement errors and loss of data. Yield was predicted by sampling meteorological data from weather stations within a region and then using those data as input to previously fitted regression equations. Wheat production was not estimated directly, but was computed by multiplying yield and acreage estimates. The allocation of samples to countries is discussed as well as the allocation and selection of segments in strata/substrata.
Transparent acetate overlays containing agricultural boundaries within each of the LACIE countries were prepared and registered to operational navigation charts (ONC's). Full frame LANDSAT color-infrared images of the same scale as the ONC's (1:1 million) were used to identify agricultural boundaries based on discernible agricultural field patterns. Preliminary steps taken in the preparation of the base map overlay, and the construction of an overlay of the base map physical features are described as well as the construction of the agricultural and nonagricultural delineation overlay.
A sample wheat acreage for a large area is obtained by multiplying its small grains acreage estimate as computed by the classification and mensuration subsystem by the best available ratio of wheat to small grains acreages obtained from historical data. In the United States, as in other countries with detailed historical data, an additional level of aggregation was required because sample allocation was made at the substratum level. The essential features of the estimation procedure for LACIE countries are included along with procedures for estimating wheat acreage in the United States.
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.
The design, implementation, and operational functions of the three phases of LACIE supported the data needs of all other elements of the project and required several types of data in addition to LANDSAT multispectral digital data. The nonelectronic data base consisted of statistical data, printed reports, periodicals, ground observed data received from intensive test sites and operational segments, and full-frame multispectral scanner CIR photographs. The following data were collected for the test sites in the United States and Canada: land use inventories, periodic crop observations, solar radiometer measurements, rainfall, and wheat yield for selected fields.
Techniques implemented to facilitate processing of LANDSAT multispectral data between 1975 and 1978 are described. The data that were handled during the large area crop inventory experiment and the storage mechanisms used for the various types of data are defined. The overall data flow, from the placing of the LANDSAT orders through the actual analysis of the data set, is discussed. An overview is provided of the status and tracking system that was developed and of the data base maintenance and operational task. The archiving of the LACIE data is explained.
The operational requirements and development of a system designed to meet LACIE needs for data to be available at given stations simultaneously, to measure throughput rates, and perform efficiency analyses are described. The final automated status and tracking system (ASATS) is defined and problems encountered during its evolutionary process are discussed.