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The New Jersey Heritage program surveyed available mapping information on landcover and vegetative communities and found that most commonly used sources, such as local land use maps and aerial photographs, were useful for individual sites, but either varied in their classifications or could not be used over extensive areas. A demonstration project using LANDSAT satellite information for the Great Egg Harbor/Tuckahoe watersheds was initiated with the goals of application (providing an inventory of vegetative communities and land use) flexibility (providing a method of collecting data which can be updated or modified in the future); and efficiency (allowing for an acceptable cost level by having staff undertake the project and avoid the more costly methods from air photo interpretation or on-site surveying. The classification procedure used is described and the spatial distributions of the 10 landcover classes determined are listed.
An irrigation ground water use inventory in Sherburne County, Minnesota, was attempted by indirectly locating irrigation wells by determining the location of irrigated lands. Digital classification of LANDSAT MSS imagery was employed using the IDIMS at Goddard Space Flight Center. Single-date classification proved moderately successful after accurate ground truth data were obtained. A combination of supervised and unsupervised classification was used. Multitemporal analysis using August 10 and May 21, 1978 imagery was also attempted. This unsupervised classification proved most successful in identifying crops and irrigated fields.
High altitude color infrared (CIR) photography was interpreted to provide an 1:24,000 overlay to U.S.G.S. topographic maps. The inventory and analysis of rangeland resources was augmented by the digital analysis of LANDSAT MSS data. Available geology, soils, and precipitation maps were used to sort out areas of confusion on the CIR photography. The map overlay from photo interpretation was also prepared with reference to print maps developed from LANDSAT MSS data. The resulting map overlay has a high degree of interpretive and spatial accuracy. An unacceptable level of confusion between the several sagebrush types in the MSS mapping was largely corrected by introducing ancillary data. Boundaries from geology, soils, and precipitation maps, as well as field observations, were digitized and pixel classes were adjusted according to the location of pixels with particular spectral signatures with respect to such boundaries. The resulting map, with six major cover classes, has an overall accuracy of 89%. Overall accuracy was 74% when these six classes were expanded to 20 classes.
The potential of using LANDSAT satellite imagery to map and inventory pinyon-juniper desert forest types in Douglas and Carson City Counties, Nevada was demonstrated. Specific map and statistical products produced include land cover, mechanical operations capability, big game winter range habitat, fire hazard, and forest harvestability. The Nevada Division of Forestry determined that LANDSAT can produce a reliable and low-cost resource data. Added benefits become apparent when the data are linked to a geographical information system (GIS) containing existing ownership, planning, elevation, slope, and aspect information.
A wide spectrum of technology pertaining to the inventory of crops using LANDSAT without in situ training data is addressed. Methods considered include Bayesian based through-the-season methods, estimation technology based on analytical profile fitting methods, and expert-based computer aided methods. Although the research was conducted using U.S. data, the adaptation of the technology to the Southern Hemisphere, especially Argentina was considered.
The status of a project to inventory state natural resources information systems is summarized. All tasks accomplished are described, and tasks remaining to be completed are outlined.
Data bases and information systems developed and maintained by state agencies to support planning and management of environmental and nutural resources were inventoried for all 50 states, Puerto Rico, and U.S. Virgin Islands. The information obtained is assembled into a computerized data base catalog which is throughly cross-referecence. Retrieval is possible by code, state, data base name, data base acronym, agency, computer, GIS capability, language, specialized software, data category name, geograhic reference, data sources, and level of reliability. The 324 automated data bases identified are described.
A multistage sampling technique, with probability proportional to size, for forest volume inventory using remote sensing data is developed and evaluated. The study area is located in the Southeastern Brazil. The LANDSAT 4 digital data of the study area are used in the first stage for automatic classification of reforested areas. Four classes of pine and eucalypt with different tree volumes are classified utilizing a maximum likelihood classification algorithm. Color infrared aerial photographs are utilized in the second stage of sampling. In the third state (ground level) the time volume of each class is determined. The total time volume of each class is expanded through a statistical procedure taking into account all the three stages of sampling. This procedure results in an accurate time volume estimate with a smaller number of aerial photographs and reduced time in field work.
A multistage sampling technique, with probability proportional to size, is developed for a forest volume inventory using remote sensing data. The LANDSAT data, Panchromatic aerial photographs, and field data are collected. Based on age and homogeneity, pine and eucalyptus classes are identified. Selection of tertiary sampling units is made through aerial photographs to minimize field work. The sampling errors for eucalyptus and pine ranged from 8.34 to 21.89 percent and from 7.18 to 8.60 percent, respectively.
Agriculture, which occupies a vital position in the economy of the State of California, depends crucially on the available water. The California Department of Water Resources (DWR) is, therefore, greatly concerned with the total water requirements for agricultural applications. In view of the limitations of an area-limited, single-date survey system, the DWR has been cooperating with NASA and the University of California in a study of the applicability of Landsat imagery and digital data as an aid in making decisions concerning the management of water resources. Attention is given to a statewide inventory of irrigated land, computer-assisted estimation and mapping of irrigated land, and a crop type analysis using Landsat digital data.
Automated information extraction procedures for analysis of multitemporal Landsat data in non-U.S. crop inventory and monitoring are reviewed. Experiments to develop and evaluate crop area estimation technologies for spring small grains, summer crops, corn, and soybeans are discussed. Previously announced in STAR as N82-32793
This paper describes the development and evaluation of a simulation procedure which produces patterns of Landsat data loss attributable to cloud patterns that are characteristic of a crop region. This simulation procedure is part of a simulation system under development which evaluates the performance of crop inventory system components over a number of years and under a variety of conditions.
A timber inventory of the Eldorado National Forest, located in east-central California, provides an example of the use of a Geographic Information System (GIS) to stratify large areas of land for sampling and the collection of statistical data. The raster-based GIS format of the VICAR/IBIS software system allows simple and rapid tabulation of areas, and facilitates the selection of random locations for ground sampling. Algorithms that simplify the complex spatial pattern of raster-based information, and convert raster format data to strings of coordinate vectors, provide a link to conventional vector-based geographic information systems.
In many military and commercial contexts, complex equipment undergoes scheduled maintenance overhauls at regular intervals during which all failed components are replaced. Failure to have replacements on hand for all failed parts requires emergency measures at premium cost. When reparable parts are highly reliable and expensive, both holding and shortage costs are high. This model determines the reparable parts inventory for a maintenance center under three alternative criteria: (1) maximizing job-completion rate subject to constraint on total holding costs, (2) minimizing total holding costs plus expected job noncompletion costs, and (3) minimizing total holding costs subject to a required minimum job-completion rate. Exact solutions may be obtained using dynamic programming. Approximate solutions, found easily by marginal analysis, have readily computed bounds on possible error. The solution methods for the three formulations are illustrated in a simple example.
As the complexity of the world's agricultural industry increases, more timely and more accurate world-wide agricultural information is required to support production and marketing decisions, policy formulation, and technology development. The Inventory Technology Development Project of the AgRISTARS Program has developed new automated technology that uses data sets acquired by spaceborne remote sensors. Research has emphasized the development of multistage, multisensor sampling and estimation techniques for use in global environments where reliable ground observations are not available. This paper presents research results obtained from data sets acquired by four different sensors: Landsat MSS, Landsat TM, Shuttle-Imaging Radar and environmental satellite (AVHRR).
Primary objectives were to develop remote sensing analysis techniques for extracting forest related information from LANDSAT Multispectral Scanner (MMS) and Thematic Mapper data and to determine the extent to which International Paper Company information needs can be addressed with remote sensing information. The company actively manages 8.4 million acres of forest land. Traditionally, their forest inventories, updated on a three year cycle, are conducted through field surveys and aerial photography. The results reside in a digital forest data base containing 240 descriptive parameteres for individual forest stands. The information in the data base is used to develop seasonal and long range management strategies. Forest stand condition assessements (species composition, age, and density stratification) and identification of silvicultural activities (site preparation, planting, thinning, and harvest) are addressed.
An accurate and simple technique utilizing a low-intensity gamma-ray source floating in a vertical tube, whose configuration is tank geometry and size dependent, is shown to eliminate the disturbing effects of turbulent fluid on enclosed tank liquid inventory measurement. The vertical tube aligns the source with detectors positioned outside of the tank, and collapses the turbulent liquid surface to a true average level. The exit attenuation of the information carrying high energy gamma rays is insensitive to liquid surface tubulence, and sensing probe penetrations are not necessary. It is found that for a half-full tank, 1.0 percent statistical error, and 1-s measuring times, that a 220 C Ce-137 source is required for an 8-ft high tank. Consistent experimental results are found for the dual detector method, and results indicate that the accuracy of the scanning side detector method is dependent on the quality of the collimator and degree of lower level energy discrimination.