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Results for “vegetation signatures”

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.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1987

Radar polarization signatures of vegetated areas

A simple model is presented for the prediction of the full polarization signature of vegetation resembling tall grass. This polarization signature can be used to detect the presence of vegetation even in those cases in which the vegetation layers are comparatively thin. Also presented is a model which predicts the polarization dependence of different tree types. Attention is given to the cases of pine and deciduous forest model predictions; both types of forest can be expected to contain terms representing the scatter from the ground, as well as forward, double reflections from the ground and limbs/trunk.

Van Zyl, Jakob J.↗
NASA NTRS1991

Analysis of polarimetric SAR signatures of vegetated areas

Several techniques to quantitatively analyze the information in the polarimetric signature are discussed, including: (1) a shape (texture) parameter; (2) fractional polarization; (3) the phase difference signature; and (4) the correlation coefficient. These techniques are applied to airborne synthetic aperture radar imagery collected over several different vegetation communities, including a mangrove swamp, a mixed-age loblolly pine forest, and a flooded bald cypress forest.

French, Nancy H. F.↗
NASA NTRS2008

Discovering the Ancient Maya from Space

The Pet6n region of northern Guatemala contains some of the most significant Mayan archeological sites in Latin America. It was in this region that the Maya civilization began, flourished, and abruptly disappeared. Remote sensing technology is helping to locate and map ancient Maya sites that are threatened today by accelerating deforestation and looting. Thematic Mapper, IKONOS, and QuickBird satellite, and airborne STAR-3i and AIRSAR radar data, combined with Global Positioning System (GPS) technology, are successfully detecting ancient Maya features such as sites, roadways, canals, and water reservoirs. Satellite imagery is also being used to map the bajos, which are seasonally flooded swamps that cover over 40% of the land surface. Through the use of various airborne and satellite sensor systems we have been able to detect and map ancient causeways, temples, reservoirs, and land forms, and locate these features on the ground through GPS technology. Recently, we have discovered that there is a strong relationship between a tropical forest vegetation signature in satellite imagery and the location of archeological sites. We believe that the use of limestone and lime plasters in ancient Maya construction affects the moisture, nutrition, and plant species of the surface vegetation. We have mapped these vegetation signatures in the imagery and verified through field survey that they are indicative of archeological sites. Through the use of remote sensing and GIS technology it is possible to identify unrecorded archeological features in a dense tropical forest environment and monitor these cultural features for their protection.

Sever, T. L.↗
NASA NTRS2007

Discovering the Ancient Maya From Space

The Peten region of northern Guatemala contains some of the most significant Mayan archeological sites in Latin America. It was in this region that the Maya civilization began, flourished, and abruptly disappeared. Remote sensing technology is helping to locate and map ancient Maya sites that are threatened today by accelerating deforestation and looting. Thematic Mapper, IKONOS, and QuickBird satellite, and airborne STAR-3i and AIRSAR radar data, combined with Global Positioning System (GPS) technology, are successfully detecting ancient Maya features such as sites, roadways, canals, and water reservoirs. Satellite imagery is also being used to map the bajos, which are seasonally flooded swamps that cover over 40% of the land surface. Through the use of various airborne and satellite sensor systems we have been able to detect and map ancient causeways, temples, reservoirs, and land forms, and locate these features on the ground through GPS technology. Recently, we have discovered that there is a strong relationship between a tropical forest vegetation signature in satellite imagery and the location of archeological sites. We believe that the use o f limestone and lime plasters in ancient Maya construction affects the moisture, nutrition, and plant species of the surface vegetation. We have mapped these vegetation signatures in the imagery and verified through field survey that they are indicative of archeological sites. Through the use of remote sensing and GIS technology it is possible to identify unrecorded archeological features in a dense tropical forest environment and monitor these cultural features for their protection.

Sever, T. L.↗
NASA NTRS1973

Textural signatures for wetland vegetation

This investigation indicates that unique textural signatures do exist for specific wetland communities at certain times in the growing season. When photographs with the proper resolution are obtained, the textural features can identify the spectral features of the vegetation community seen with lower resolution mapping data. The development of a matrix of optimum textural signatures is the goal of this research. Seasonal variations of spectral and textural features are particularly important when performing a vegetations analysis of fresh water marshes. This matrix will aid in flight planning, since expected seasonal variations and resolution requirements can be established prior to a given flight mission.

Whitman, R. I.↗
NASA NTRS1983

Optimal Landsat transforms for forest applications

Eleven transformations of data from four Landsat MSS channels were investigated to find if any of the transforms accentuated the separability of natural vegetation classes in regions of varying topographical relief. Attention was given to the divergence analysis and classification accuracy of information content of the eleven transforms and four channels. A useful scaling function was observed with the second eigenvector being the denominator in the divergence values obtained. The second eigenvector was found to reduce the effects of shadowing and differential illumination of vegetation signatures, thereby enhancing the divergence values. The highest accuracies in crop identification were provided by the averages of channels 4, 6, and 7 divided by the second eigenvector.

Logan, T. L.↗
NASA NTRS1991

Separation of vegetation and rock signatures in Thematic Mapper and polarimetric SAR images

A technique for separating classes of surface roughness and vegetation in semiarid regions using polarimetric synthetic aperture radar (SAR) and Thematic Mapper data is developed. Polarimetric SAR data may be used to separate areas with less than 10 percent vegetation cover where one suite of model inversions may be applicable for derivation of surface roughness. In more vegetated regions, visible/near-infrared data provide a mechanism for determining the relative contribution of vegetation to multiple scattering in the SAR data. Thus, the synergistic use of the two data sets provides a more complete characterization of surface units and cover. This result is critical when trying to monitor dielectric constant variations related to changes in moisture content of soil and vegetation cover in arid to semiarid regions. A strategy for automating a procedure for measurement of surface roughness is proposed.

Evans, Diane L.↗
NASA NTRS1978

Landsat spectral signatures - Studies with soil associations and vegetation

The effect of soils and vegetation upon Landsat spectral properties was investigated for a 12,950 hectare area. Six soil associations used for corn, small grains, and grass were analyzed for two dates during the 1974 growing season. Landsat scenes for April 19 and June 30 were studied to separate categories of agricultural land use and to assess the influence of soil association on the spectral signatures of vegetation and bare ground. The April 19 data were useful to separate cropland from grassland and to locate areas of open water. The June 30 data showed that soil associations could not consistently be separated within the data of a single vegetative type; however, the results showed that soils did influence all vegetative spectral reflectances to some degree. Because soils did influence vegetative spectral reflectance, a generalized training set containing data points from each of the six soil associations was used to separate four categories of agricultural land use in the 12,950 hectare test area. An accuracy of about 94% was obtained.

Westin, F. C.↗
NASA NTRS1980

Automatically classifying Earth features from orbit

Solid state circuit classifies satellite imagery by spectral signature of vegetation, bare land, water, clouds, or snow. Circuit can be used to sort and separate specific imagery by signature so that only useful data is transmitted to earth. Device saves time and costs involved in manual separation of data.

Holstrom, R. L.↗
NASA NTRS1975

Multiseasonal-multispectral remote sensing of phenological change for natural vegetation inventory

The author has identified the following significant results. Variations in phenological development among plant species was noted, as well as the tendency for the seasonal appearance of some vegetation types to be dominated by the appearance of one or a few similarly developing species. Most of the common plants in the study area could be characterized by temporal aspects of their phenological development. There was a strong similarity among the spectral signatures of vegetation types in which the spectral return was dominated by green plant material. When the soil background dominated the spectral return from a vegetation stand, then the spectral radiance and the vegetation physiognomy were apparently related. When the deciduous shrubs lost their leaves, their spectral signature altered with a slight decrease of radiance in the visible wavelengths and a strong decrease in the near infrared. As the foliage of perennial grasses cured from August to November, its apparent green radiance remained unchanged, red radiance increased over 50 percent, and near infrared radiance decreased approximately 30 percent. A reflective mineral surface exhibited high radiance levels in all four bands, thus providing a marked contrast to the absorption characteristics of vegetation canopies.

Schrumpf, B. J.↗
NASA NTRS1979

Signature evaluation of natural targets using high spectral resolution techniques

The concept of 'spectral signature' identification has been applied to LANDSAT and other broad-band multi-spectral scanner data to classify various materials on the earth's surface. A large amount of the spectral information available is invisible, however, to the broad-band sensors. Although the natural targets of interest in remote sensing do not exhibit fine line features such as those associated with gaseous media, there is significant information to be extracted from smoothly varying spectral reflection functions of most natural targets. Subtle variations observed recently in the high resolution 'spectral signatures' of vegetation targets, in particular, promise to open new avenues of application using higher spectral and radiometric resolution techniques. This research was accomplished using a 500-band spectroradiometer system specially adapted to rapid airborne operations

Collins, W.↗
NASA NTRS1984

Basic principles, methodology, and applications of remote sensing in agriculture

The basic principles of remote sensing applied to agriculture and the methods used in data analysis are described. Emphasis is placed on the importance of developing a methodology that may help crop forecast, basic concepts of spectral signatures of vegetation, the methodology of the LANDSAT data utilization in agriculture, and the remote sensing program application of INPE (Institute for Space Research) in agriculture.

Moreira, M. A.↗
NASA NTRS1993

AIRSAR views of aerolian terrain

The Stovepipe Wells Dune Field provides a unique opportunity to observe several dune forms in one scene. These forms include reverse dunes, star dunes, transverse, and linear dunes. A sand mantle surrounds the dune field and can also be observed in the radar image. Dune types were discriminated best in co-polarized channels. Three major wind directions are responsible for the various dune forms. Winds from the north and south are responsible for the reverse dunes, winds from north for the transverse dunes, and the north - south and westerly winds for the star dunes. The winds also reflect the topographic configuration of this part of Death Valley. Vegetation over the dunes was most pronounced in the cross-polarized images. Lancaster et al. (1992) find that cross-polarized images are most useful in differentiating active from inactive dunes. This is because the vegetation backscatter signature is present over inactive dunes. Future studies should include multiple look and incidence angles to determine if the dune forms can still be seen at other angles.

Blumberg, Dan G.↗
NASA NTRS1994

Analysis of AOTF Hyperspectral Imagery

This paper reports results from an analysis of polarimetric hyperspectral imagery collected using a prototype acousto-optic tunable filter (AOTF) instrument in an outdoor environment. Spectra, derivative spectra, and polarization spectra in the image cube form were studied. The issue concerns spectral and polarization signatures of vegetation, contributions due to aerosol, and man-made object detection. The result illustrates potentials of the technology for a variety of remote sensing applications.

acousto-optic↗
NASA NTRS1974

A study to explore the use of orbital remote sensing to determine native arid plant distribution

The author has identified the following significant results. It is possible to determine, from ERTS imagery, native arid plant distribution. Using techniques of multispectral masking and extensive fieldwork, three native vegetation communities were defined and mapped in the Avra Valley study area. A map was made of the Yuma area with the aid of ground truth correlations between areas of desert pavement visible on ERTS images and unique vegetation types. With the exception of the Yuma soil-vegetation correlation phenomena, only very gross differentiations of desert vegetation communities can be made from ERTS data. Vegetation communities with obvious vegetation density differences such as saguaro-paloverde, creosote bush, and riparian vegetation can be separated on the Avra Valley imagery while more similar communities such as creosote bush and saltbush could not be differentiated. It is suggested that large differences in vegetation density are needed before the signatures of two different vegetation types can be differentiated on ERTS imagery. This is due to the relatively insignificant contribution of vegetation to the total radiometric signature of a given desert scene. Where more detailed information concerning the vegetation of arid regions is required, large scale imagery is appropriate.

Mcginnies, W. G.↗
NASA NTRS1980

The evaluation of 3cm-wavelength radar for mapping surface deposits in the Bristol Lake/Granite Mountain area, Mojave Desert, California

Surface deposits in the Bristol Lake/Granite Mountains area, Mojave Desert, California were mapped using high resolution 3 cm wavelength radar images. The surface deposits range from silt to boulders in size and were separated into six radar-rock units on the basis of radar return signatures (brightness and texture) and geomorphic expression. Field reconnaissance of the six units showed that the brightness of the radar signatures on the images correlates with the surface roughness of each unit. Two major radar signatures anomalies were noted during the study. A dark radar signature for the large sand ridges in the Kelso Dunes area and a distinct northwest trending contrast boundary between bright and dark radar signatures in the Bristol Dry Lake area. Field reconnaissance of the two areas indicated that near surface moisture may be the cause of dark signatures. Dune areas with little to no vegetation produce a dark signature, whereas areas with sparse to moderate vegetation produce an intermediate to dark signature.

Sugiura, R.↗
NASA NTRS1980

Experimental application of LANDSAT to geobotanical prospecting of serpentine outcrops in the central Appalachian Piedmont of North America

The use of LANDSAT as a tool for geobotanical prospecting was studied in a 13,137 sq km area from southeastern Pennsylvania to northern Virginia. Vegetation differences between known serpentine and non-sepentine sites were most easily distinguished on early summer images. A multispectral signature was derived from vegetation of two known serpentine sites and a map was produced of 159 similar signatures of vegetation in the study area. Authenticity of the serpentine nature of the mapped sites was checked via geochemical analysis of collected soils from 14% of the sites. Overall success of geobotanical prospecting was about 35% for the total study area. When vegetation distribution was taken into account, the success rate was 67% for the region north of the Potomac, demonstrates the effectiveness of the multispectral satellite for quickly and accurately locating mineral sensitive vegetation communities over vast tracts of land.

Mielke, H. W.↗