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At least 199 records · Page 11

Applicability of ERTS-1 to Montana geology

The author has identified the following significant results. Late autumn imagery provides the advantages of topographic shadow enhancement and low cloud cover. Mapping of rock units was done locally with good results for alluvium, basin fill, volcanics, inclined Paleozoic and Mesozoic beds, and host strata of bentonite beds. Folds, intrusive domes, and even dip directions were mapped where differential erosion was significant. However, mapping was not possible for belt strata, was difficult for granite, and was hindered by conifers compared to grass cover. Expansion of local mapping required geologic control and encountered significant areas unmappable from ERTS imagery. Annotation of lineaments provided much new geologic data. By extrapolating test site comparisons, it is inferred that 27 percent of some 1200 lineaments mapped from western Montana represent unknown faults. The remainder appear to be localized mainly by undiscovered faults and sets of minor faults or joints.

Weidman, R. M.↗

The use of four band multispectral photography to identify forest cover types

Four-band multispectral aerial photography and a color additive viewer were employed to identify forest cover types in Northern Alabama. The multispectral photography utilized the blue, green, red and near-infrared spectral regions and was made with black and white infrared film. On the basis of color differences alone, a differentiation between conifers and hardwoods was possible; however, supplementary information related to forest ecology proved necessary for the differentiation of various species of pines and hardwoods.

Downs, S. W., Jr.↗

Use of manual densitometry in land cover classification

Through use of manual spot densitometry values derived from multitemporal 1:24,000 color infrared aircraft photography, areas as small as one hectare in the Cumberland Plateau in Kentucky were accurately classified into one of eight ground cover groups. If distinguishing between undisturbed and disturbed forest areas is the sole criterion of interest, classification results are highly accurate if based on imagery taken during foliated ground cover conditions. Multiseasonal imagery analysis was superior to single data analysis, and transparencies from prefoliated conditions gave better separation of conifers and hardwoods than did those from foliated conditions.

Jordan, D. C.↗

The application of LANDSAT remote sensing technology to natural resources management. Section 1: Introduction to VICAR - Image classification module. Section 2: Forest resource assessment of Humboldt County.

A teaching module on image classification procedures using the VICAR computer software package was developed to optimize the training benefits for users of the VICAR programs. The field test of the module is discussed. An intensive forest land inventory strategy was developed for Humboldt County. The results indicate that LANDSAT data can be computer classified to yield site specific forest resource information with high accuracy (82%). The "Douglas-fir 80%" category was found to cover approximately 21% of the county and "Mixed Conifer 80%" covering about 13%. The "Redwood 80%" resource category, which represented dense old growth trees as well as large second growth, comprised 4.0% of the total vegetation mosaic. Furthermore, the "Brush" and "Brush-Regeneration" categories were found to be a significant part of the vegetative community, with area estimates of 9.4 and 10.0%.

Fox, L., III↗

Land-cover classification of California using mosaicking and high-speed processing

A land cover classification of Landsat MSS data has been made for the entire state of California. Digital mosaicking of 32 Landsat scenes with registered digital elevation, slope, and aspect was prepared. Stratified unsupervised clustering generated the spectral classes which were identified into 16 categories, mostly forest types, using U-2 CIR photos. A verification using 81 primary sample units resulted in a forest/nonforest accuracy of 80.2% and a commercial conifer and hardwood accuracy of 75.1%. The results are now being used in many projects throughout the state.

Peterson, D. L.↗

Computer classified Landsat data used as a forest stratifier

Results of two forest stratification projects are presented to show that Landsat data, when combined with guided clustering techniques, can provide detailed stratification of forest environment. It is shown that conifer species groupings, vegetative cover classes, and three size classes can be discriminated with accuracies ranging from 83 to 91%.

Fox, L., III↗

Identifying environmental features for land management decisions

Advances in digital processing of LANDSAT imagery and in the interpretation of aerial photography are reported as well as the development of a geographic information system and the acquisition of cartographic equipment. Services to technical specialists and dignitaries are also described. The status of the following studies is discussed: Farmington Bay waterfowl; Sevier River wetland and agriculture; Davis County foothill development; Bear River Range aspen habitat; Wasatch-Cache riparian habitats; irrigated acreage in the Bear River Basin; the Parker Mountain rangeland inventory; and the development of techniques for inventorying aspen and aspen conifer stands. The cooperative project with NASA-Ames to verify LANDSAT digital maps of the forest and range resources on the LaSal Mountains is also considered.

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LANDSAT applications by the Adirondack Park Agency for land cover analyses and forest cover change

The New York State Adirondack Park Agency is using LANDSAT imagery to provide current, consistent parkwide data on forest cover, forest change and other land cover characteristics for the Adirondack Park, an area of 9,375 sq. miles (24,280 sq km). Boundaries of the study area were digitized and the data were enhanced and geographically rectified. A classification scheme was devised which emphasized the basic land cover types of the Park: hardwoods, spruce-fir, pine, wet conifer, brushland, grassland, agricultural areas, exposed earth, urban areas, and water bodies. Cover type classifications for disturbed forest land were also chosen: cut hardwoods, regenerating hardwoods, and cut spruce fir. Field verification of 1978 classification revealed an accurate differentiation of forest types within types and between nonforested/forested areas. The classification accurately detects forest land disturbances; however, it is not always descriptive of the level of disturbance.

Banta, J. S.↗

Development and testing of LANDSAT-assisted procedures for cost-effective forest management

The capability of LANDSAT data to make certain forest management activities on the Clearwater National Forest in Idaho more efficient and/or more effective was examined. One task was designed to evaluate the utility of single-date categorized LANDSAT data as a source of land cover information for use in assessing elk habitat quality. LANDSAT data was used to categorize conifer forest on the basis of the percentage crown closure. This information was used to evaluate elk habitat quality on the basis of the ratio of cover to forage. A preliminary conclusion is that categorized LANDSAT data can be helpful for assessing current elk habitat quality if the relationships between crown closure and hiding cover can be adequately defined. Another task was designed to evaluate the utility of merged two-date LANDSAT data for updating the existing (1972) Clearwater Forest land cover information. LANDSAT data from 1972 and 1981 were merged, and change images were created. These products indicated where major changes were taking place. These areas could then be examined on aerial photography or in the field to further characterize the nature and magnitude of the change. The 1972 land cover information could be subsequently altered in these changed areas, whereas areas with no change would not have to be re-examined.

Colwell, J. E.↗

Development of LANDSAT Derived Forest Cover Information for Integration into Adirondack Park GIS

Based upon observed changes in timber harvest practices partially attributable to forest biomass removable for energy supply purposes, the Adirondack Park Agency began in 1979 a multi-year project to implement a digital geographic information system (GIS). An initial developmental task was an inventory of forest cover information and analysis of forest resource change and availability. While developing the GIS, a pilot project was undertaken to evaluate the usefulness of LANDSAT derived land cover information for this purpose, and to explore the integration of LANDSAT data into the GIS. The prototype LANDSAT analysis project involved: (1) the use of both recent and historic data to derive land cover information for two dates; and (2) comparison of land cover over time to determine quantitative and geographic changes. The "recent data," 1978 full foliage data over portions of four LANDSAT scenes, was classified, using ground truth derived training samples in various forested and non-forested categories. Forested categories include the following: northern hardwoods, pine, spruce-fir, and pine plantation, while nonforested categories include wet-conifer, pasture, grassland, urban, exposed soil, agriculture, and water.

Curran, R. P.↗

Detection of aspen/conifer forest mixes from multitemporal LANDSAT digital data

Aspen, conifer and mixed aspen/conifer forests were mapped for a 15-quadrangle study area in the Utah-Idaho Bear River Range using LANDSAT multispectral scanner (MSS) data. The digital MSS data were utilized to devise quantitative indices which correlate with apparently stable and seral aspen forests. The extent to which a two-date LANDSAT MSS analysis may permit the delineation of different categories of aspen/conifer forest mix was explored. Multitemporal analyses of MSS data led to the identification of early, early to mid, mid to late, and late seral stages of aspen/conifer forest mixing.

Merola, J. A.↗

Use of remote sensing for land use policy formulation

Multispectral scanning, infrared imagery, thematic mapping, and spectroradiometry from LANDSAT, GOES, and ground based instruments are being used to determine conifer distribution, maximum and minimum temperatures, topography, and crop diseases in Michigan's lower Peninsula. Image interpretation and automatic digital processing information from LANDSAT data are employed to classify and map the coniferous forests. Radiant temperature data from GOES were compared to temperature readings from the climatological station network. Digital data from LANDSAT is being used to develop techniques for detecting, monitoring, and modeling land surface change. Improved reflectance signatures through spectroradiometry aided in the detection of viral diseases in blueberry fields and vineyards. Soil survey maps from aerial reconnaissance are included as well as information on education, conferences, and awards.

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The 1984 NASA/ASEE summer faculty fellowship program

The assessment of forest productivity and associated nitrogen flux in a number of conifer ecosystems is described. As a base line study of acid precipitation in the Sierra Nevada, involved is the extraction and integration of a number of data planes describing the terrain, soils, lithology, vegetation cover and structure, and microclimate of the region. The development of automated techniques to extract topographic networks (stream canyons and ridge lines) for use as a landscrape skeleton to organize and integrate data sets into an efficient geographical information system is examined. The software is written in both FORTRAN and C, and is portable to a number of different computer environments with minimal modification.

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Using the solar elevation angle and radiance conversion to normalize forest spectral signatures

A number of spectral signals associated with forest cover were selected in order to test the usefulness of adjustments to Landsat MSS digital count values. The signatures were taken from 26 independent regional land cover inventories in the northeastern US. A regression analysis was conducted which revealed a significant relationship between digital count values and variation in the solar elevation angles in MSS bands four, six, and seven for deciduous forests and in all MSS bands for conifers. When signatures were adjusted for solar elevation angles and MSS sensor calibration differences, the dependence on solar elevation angle was reduced. The adjustments also significantly reduced the variance with Level II forest categories among scenes.

Middleton, E. M.↗

Thematic Mapper simulator research for forest resource mapping in the Clearwater National Forest, Idaho

Per-pixel maximum likelihood digital classification and photo interpretation of Thematic Mapper Simulator (TMS) composited images for a managed conifer forest were used to evaluate both land cover and forest structure characteristics. TMS channels 4, 7, 5 and 3, which were found to be optimal for forest vegetation analysis, used the full range of the Thematic Mapper's spectral capability. Photo interpretation results indicate that a false color composite from TMS channels 4, 7, and 2 provided the highest accuracies; the combination of improved spatial, spectral and radiometric resolution of the Thematic Mapper yielded greater sensitivity to forest structural characteristics.

Brass, J. A.↗

Discrete-object modeling of remotely sensed scenes

Remotely sensed scenes can be modeled as collections of discrete, three-dimensional objects that cast shadows on a background. Approaching scenes from this perspective has led to two related lines of research. First is the geometric/optical modeling of a forest canopy, in which conifers are modeled as cones whose size and spacing vary according to functions established by field measurements. This canopy model is 'L-resolution' in nature - the objects are smaller than the resolution cells of the image and cannot be resolved individually. Second is scene modeling in which image variance is taken as a function of the relationship between the size, shape and spacing of objects and the resolution cell size of the digital image derived from the scene. This modeling is 'H-resolution' in nature - the objects in the scene are assumed to be larger than the resolution cells of the image, and thus can be individually distinguished. Both approaches illustrate the utility of the discrete-object scene model in extracting information from remotely sensed scenes.

Strahler, A. H.↗

Follow-on proposal identifying environmental features for land management decisions

Urban morphology (an examination of spatial fabric and structure), natural ecosystem (investigations emphasizing biophysical processes and patterns), and human ecosystem (emphasizing socio-economic and engineering parameters) were studied. The most critical variable, transpiration, in the ASPCON model, created by Jaynes (1978), describing the hydrology of aspen to conifer succession was studied to improve the accuracy. Transpiration is determined by a canopy transpiration model which estimates consumptive water use (CWU) for specific species and a plant activity index. Also studied was Pinyon-Juniper woodland erosion.

Wright, P. M.↗

Preliminary evaluation of the airborne imaging spectrometer for vegetation analysis in the Klamath National Forest of northeastern California

The experiences and results associated with a project entitled Preliminary Evaluation of the Airborne Imaging Spectrometer for Vegetation Analysis is documented. The primary goal of the project was to provide ground truth, manual interpretation, and computer processing of data from an experimental flight of the Airborne Infrared Spectrometer (AIS) to determine the extent to which high spectral resolution remote sensing could differentiate among plant species, and especially species of conifers, for a naturally vegetated test site. Through the course of the research, JPL acquired AIS imagery of the test areas in the Klamath National Forest, northeastern California, on two overflights of both the Dock Well and Grass Lake transects. Over the next year or so, three generations of data was also received: first overflight, second overflight, and reprocessed second overflight. Two field visits were made: one trip immediately following the first overflight to note snow conditions and temporally-related vegetation states at the time of the sensor overpass; and a second trip about six weeks later, following acquisition of prints of the images from the first AIS overpass.

Strahler, A. H.↗