Bathymetry and selected views of the fringing coral reef, South Moloka'i, Hawaii
No abstract available.
Hawaii↗
Geology topics
Pat S. Chavez
Publications and source records attributed to Pat S. Chavez.
Monitoring dust storms and mapping landscape vulnerability to wind erosion using satellite and ground-based digital images
Wind-induced dust emission in the southwestern United States is important regionally because of its impact on human health and safety and its influence on ecosystem dynamics. Factors that control dust emission include wind velocity, sediment availability, and surface conditions (e.g., vegetation type and degree of cover, surface crusts and armoring, and soil moisture - Gillette and Passi, 1988; Gillette and Hanson 1989; Marticorena and others, 1997). Emission of dust from the land surface is a process of degradation that depletes fine-grained minerals needed for optimum vegetation growth, creates potentially hazardous air quality for humans on a local and regional scale, and can affect climate on a regional and global scale. Future climatic change may lead to increased aridification of southwestern deserts, reducing protective vegetation and enhancing dust emissions, thereby increasing the impacts of dust in this region. It is currently not well understood how climate change in the Southwest will affect dust emission and, in turn, how dust emission will affect climate and human health. As part of a study of landscape vulnerability to wind erosion and the potential impacts of dust, we are investigating remotely sensed satellite, airborne, and ground-based image data to determine their ability to detect and monitor active dust storms, as well as to map areas vulnerable to wind erosion. A main objective has been to investigate the use of high temporal resolution digital images collected by satellite and a long-term, ground-based digital camera station, along with wind data collected at our field sites, to detect, monitor, and analyze the location, size, frequency, duration, and transport patterns of dust storms in the Mojave Desert of the southwestern United States. Generally, many current methods and instruments are not developed to the level required to routinely detect and monitor dust storms or to develop models that accurately predict total dust flux and emission rates. Improving these capabilities is critical to generating baseline datasets for assessments of landscape vulnerability to future climate change. On going modeling efforts are attempting to identify meteorological parameters and soil surface roughness parameters needed to predict the vulnerability of various geomorphic substrates to wind erosion. Datasets to calibrate model results are difficult to collect and typically not available. Results of our studies, incorporating digital image maps and new methods using remotely sensed images to identify and monitor dust sources, will be useful for the calibration of dust-emission models of the Mojave Desert and other arid environments. At the same time, we are exploring new methods to map the amount, sizes, and spatial distribution of particles at the surface to enable detailed wind-erosion vulnerability mapping at a regional scale.
California↗
City of Flagstaff Project: Ground Water Resource Evaluation, Remote Sensing Component
Many regions, cities, and towns in the Western United States need new or expanded water resources because of both population growth and increased development. Any tools or data that can help in the evaluation of an area's potential water resources must be considered for this increasingly critical need. Remotely sensed satellite images and subsequent digital image processing have been under-utilized in ground water resource evaluation and exploration. Satellite images can be helpful in detecting and mapping an area's regional structural patterns, including major fracture and fault systems, two important geologic settings for an area's surface to ground water relations. Within the United States Geological Survey's (USGS) Flagstaff Field Center, expertise and capabilities in remote sensing and digital image processing have been developed over the past 25 years through various programs. For the City of Flagstaff project, this expertise and these capabilities were combined with traditional geologic field mapping to help evaluate ground water resources in the Flagstaff area. Various enhancement and manipulation procedures were applied to the digital satellite images; the results, in both digital and hardcopy format, were used for field mapping and analyzing the regional structure. Relative to surface sampling, remotely sensed satellite and airborne images have improved spatial coverage that can help study, map, and monitor the earth surface at local and/or regional scales. Advantages offered by remotely sensed satellite image data include: 1. a synoptic/regional view compared to both aerial photographs and ground sampling, 2. cost effectiveness, 3. high spatial resolution and coverage compared to ground sampling, and 4. relatively high temporal coverage on a long term basis. Remotely sensed images contain both spectral and spatial information. The spectral information provides various properties and characteristics about the surface cover at a given location or pixel (that is, vegetation and/or soil type). The spatial information gives the distribution, variation, and topographic relief of the cover types from pixel to pixel. Therefore, the main characteristics that determine a pixel's brightness/reflectance and, consequently, the digital number (DN) assigned to the pixel, are the physical properties of the surface and near surface, the cover type, and the topographic slope. In this application, the ability to detect and map lineaments, especially those related to fractures and faults, is critical. Therefore, the extraction of spatial information from the digital images was of prime interest in this project. The spatial information varies among the different spectral bands available; in particular, a near infrared spectral band is better than a visible band when extracting spatial information in highly vegetated areas. In this study, both visible and near infrared bands were analyzed and used to extract the desired spatial information from the images. The wide swath coverage of remotely sensed satellite digital images makes them ideal for regional analysis and mapping. Since locating and mapping highly fractured and faulted areas is a major requirement for ground water resource evaluation and exploration this aspect of satellite images was considered critical; it allowed us to stand back (actually up about 440 miles), look at, and map the regional structural setting of the area. The main focus of the remote sensing and digital image processing component of this project was to use both remotely sensed digital satellite images and a Digital Elevation Model (DEM) to extract spatial information related to the structural and topographic patterns in the area. The data types used were digital satellite images collected by the United States' Landsat Thematic Mapper (TM) and French Systeme Probatoire d'Observation de laTerre (SPOT) imaging systems, along with a DEM of the Flagstaff region. The USGS Mini Image Processing Sy
Open-File Report↗
Satellite image map of Antarctica, 1996
Explore the source record for details and available documents.
IMAP↗
An improved dark-object subtraction technique for atmospheric scattering correction of multispectral data
Digital analysis of remotely sensed data has become an important component of many earth-science studies. These data are often processed through a set of preprocessing or “clean-up” routines that includes a correction for atmospheric scattering, often called haze. Various methods to correct or remove the additive haze component have been developed, including the widely used dark-object subtraction technique. A problem with most of these methods is that the haze values for each spectral band are selected independently. This can create problems because atmospheric scattering is highly wavelength-dependent in the visible part of the electromagnetic spectrum and the scattering values are correlated with each other. Therefore, multispectral data such as from the Landsat Thematic Mapper and Multispectral Scanner must be corrected with haze values that are spectral band dependent. An improved dark-object subtraction technique is demonstrated that allows the user to select a relative atmospheric scattering model to predict the haze values for all the spectral bands from a selected starting band haze value. The improved method normalizes the predicted haze values for the different gain and offset parameters used by the imaging system. Examples of haze value differences between the old and improved methods for Thematic Mapper Bands 1, 2, 3, 4, 5, and 7 are 40.0, 13.0, 12.0, 8.0, 5.0, and 2.0 vs. 40.0, 13.2, 8.9, 4.9, 16.7, and 3.3, respectively, using a relative scattering model of a clear atmosphere. In one Landsat multispectral scanner image the haze value differences for Bands 4, 5, 6, and 7 were 30.0, 50.0, 50.0, and 40.0 for the old method vs. 30.0, 34.4, 43.6, and 6.4 for the new method using a relative scattering model of a hazy atmosphere.
Arizona↗
UNDERWATER MAPPING USING GLORIA AND MIPS.
Advances in digital image processing of the (GLORIA) Geological Long-Range Induced Asdic) sidescan-sonar image data have made it technically and economically possible to map large areas of the ocean floor including the Exclusive Economic Zone. Software was written to correct both geometric and radiometric distortions that exist in the original raw GLORIA data. A digital mosaicking technique was developed enabling 2 degree by 2 degree quadrangles to be generated.
Conference Paper↗
Digital processing techniques and film density calibration for printing image data
Satellite image data that cover a wide range of environments are being used to make prints that represent a map type product. If a wide distribution of these products is desired, they are printed using lithographic rather than photographic procedures to reduce the cost per print. Problems are encountered in the photo lab if the film products to be used for lithographic printing have the same density range and density curve characteristics as the film used for photographic printing. A method is presented that keeps the film densities within the 1.1 range required for lithographic printing, but generates film products with contrast similar to that in photographic film for the majority of data (80 percent). Also, spatial filters can be used to enhance local detail in dark and bright regions, as well as to sharpen the final image product using edge enhancement techniques.
Conference Paper↗
DIGITAL PROCESSING TECHNIQUES FOR IMAGE MAPPING WITH LANDSAT TM AND SPOT SIMULATOR DATA.
To overcome certain problems associated with the visual selection of Landsat TM bands for image mapping, the author used a quantitative technique that ranks the 20 possible three-band combinations based upon their information content. Standard deviations and correlation coefficients can be used to compute a value called the Optimum Index Factor (OIF) for each of the 20 possible combinations. SPOT simulator images were digitally processed and compared with Landsat-4 Thematic Mapper (TM) images covering a semi-arid region in northern Arizona and a highly vegetated urban area near Washington, D. C. Statistical comparisons indicate the more radiometric or color information exists in certain TM three-band combinations than in the three SPOT bands.
Conference Paper↗
An automatic optimum kernel-size selection technique for edge enhancement
Edge enhancement is a technique that can be considered, to a first order, a correction for the modulation transfer function of an imaging system. Digital imaging systems sample a continuous function at discrete intervals so that high-frequency information cannot be recorded at the same precision as lower frequency data. Because of this, fine detail or edge information in digital images is lost. Spatial filtering techniques can be used to enhance the fine detail information that does exist in the digital image, but the filter size is dependent on the type of area being processed. A technique has been developed by the authors that uses the horizontal first difference to automatically select the optimum kernel-size that should be used to enhance the edges that are contained in the image.
Remote Sensing of Environment↗
Arid land monitoring using Landsat albedo difference images
The Landsat albedo, or percentage of incoming radiation reflected from the ground in the wavelength range of 0.5 [mu]m to 1.1 [mu]m, is calculated from an equation using the Landsat digital brightness values and solar irradiance values, and correcting for atmospheric scattering, multispectral scanner calibration, and sun angle. The albedo calculated for each pixel is used to create an albedo image, whose grey scale is proportional to the albedo. Differencing sequential registered images and mapping selected values of the difference is used to create quantitative maps of increased or decreased albedo values of the terrain. All maps and other output products are in black and white rather than color, thus making the method quite economical. Decreases of albedo in arid regions may indicate improvement of land quality; increases may indicate degradation. Tests of the albedo difference mapping method in the Desert Experimental Range in southwestern Utah (a cold desert with little long-term terrain change) for a four-year period show that mapped changes can be correlated with erosion from flash floods, increased or decreased soil moisture, and increases or decreases in the density of desert vegetation, both perennial shrubs and annual plants. All terrain changes identified in this test were related to variations in precipitation. Although further tests of this method in hot deserts showing severe "desertification" are needed, the method is nevertheless recommended for experimental use in monitoring terrain change in other arid and semiarid regions of the world.
Utah↗
Digital processing techniques for small digital arrays (FLD data set)
The purpose of the Workshop on Luminescence Techniques was threefold: (1) to review the state-of-the-art capabilities of luminescence methods, (2) to consider a variety of concepts for the development of future luminescence sensor systems, and (3) to discuss appropriate research and development strategies for advancing the current state-of-the-art.
Conference Paper↗
Integration of geological, geochemical, and geophysical spatial data of the Cement oil field, Oklahoma, test site
Measurement pertaining to geology, geochemistry, and geophysics of the Cement oil field, Oklahoma, test site were collected employing both airborne sensors and ground-based data collection. The measurements include: (1) airborne gamma-ray spectrometry (supplying bismuth 214, thalium 208, and potassium 40 gamma-ray intensities); (2) aeromagnetic survey data; (3) multi-frequency airborne resistivity survey data (supplying apparent electrical resistivity of near surface materials); (4) gravity data; (5) geological and topographic maps; and (6) image data from Landsat MSS and U-2 photography.
Oklahoma↗