Geology topics

Susan K. Jenson

Publications and source records attributed to Susan K. Jenson.

5 recordsLinked to original sources

USGS2006

Applications of hydrologic information automatically extracted from digital elevation models

Digital elevation models (DEMs) can be used to derive a wealth of information about the morphology of a land surface. Traditional raster analysis methods can be used to derive slope, aspect, and shaded relief information; recently-developed computer programs can be used to delineate depressions, overland flow paths, and watershed boundaries. These methods were used to delineate watershed boundaries for a geochemical stream sediment survey, to compare the results of extracting slope and flow paths from DEMs of varying resolutions, and to examine the geomorphology of a Martian DEM. -Author

Hydrological Processes↗

USGS1988

Extracting topographic structure from digital elevation data for geographic information-system analysis

Software tools have been developed at the U.S. Geological Survey's EROS Data Center to extract topographic structure and to delineate watersheds and overland flow paths from digital elevation models. The tools are specialpurpose FORTRAN programs interfaced with general-purpose raster and vector spatial analysis and relational data base management packages. The first phase of analysis is a conditioning phase that generates three data sets: the original OEM with depressions filled, a data set indicating the flow direction for each cell, and a flow accumulation data set in which each cell receives a value equal to the total number of cells that drain to it. The original OEM and these three derivative data sets can then be processed in a variety of ways to optionally delineate drainage networks, overland paths, watersheds for userspecified locations, sub-watersheds for the major tributaries of a drainage network, or pour point linkages between watersheds. The computer-generated drainage lines and watershed polygons and the pour point linkage information can be transferred to vector-based geographic information systems for futher analysis. Comparisons between these computergenerated features and their manually delineated counterparts generally show close agreement, indicating that these software tools will save analyst time spent in manual interpretation and digitizing.

Photogrammetric Engineering and Remote Sensing↗

USGS1987

Methods and applications in surface depression analysis

Gridded surface data sets are often incorporated into digital data bases, but extracting information from the data sets requires specialized raster processing techniques different from those historically used on remotely sensed and thematic data. Frequently, the information desired of a gridded surface is directly related to the topologic peaks and pits of the surface. A method for isolating these peaks and pits has been developed, and two examples of its application are presented. The perimeter of a pit feature is the highest-valued closed contour surrounding a minimum level. The method devised for finding all such contours is designed to operate on large raster surfaces. If the data are first inversely mapped, this algorithm will find surface peaks rather than pits. In one example the depressions, or pits, expressed in Digital Elevation Model data, are hydrologically significant potholes. Measurement of their storage capacity is the objective. The potholes are found and labelled as polygons; their watershed boundaries are found and attributes are computed. In the other example, geochemical surfaces, which were interpolated from chemical analyses of irregularly distributed stream sediment samples, were analyzed to determine the magnitude, morphology, and areal extent of peaks (geochemical anomalies).

Conference Paper↗

USGS1985

Automated derivation of hydrologic basin characteristics from digital elevation model data

Digital elevation model (DEM) data in a raster format can be used to automatically derive the drainage characteristics of an area. A procedure has been designed that is capable of operating on matrices of elevation data having no algorithmically imposed size limit, while performing within the resolution and accuracy tolerances of the DEM data. Each cell is processed as the center of a 3- by 3-cell spatial window in the raster elevation data. If a cell is a local minimum in comparison with two of its non-adjacent neighbors, it is labeled as a drainage cell. The linkages of the drainage cells within user-specified distance and elevation thresholds are established in a separate process. The products of these processing steps are digital masks of the drainage cells and the watershed basins, both in raster format. A drainage cell mask derived using this procedure is useful in computing slope values for a raster data base. Slope has traditionally been calculated for each cell by fitting a plane through the eight nearest cells. However, if the terrain represented by these cells is V-shaped, such as a gully, a plane does not fit well; in fact, the desired slope value is the slope along the bottom of the gully, regardless of the steepness of the gully sides. The automated drainage process will label such a cell as a drainage cell, and its slope can then be computed from the elevation values of neighboring drainage cells.

Conference Paper↗

USGS1982

Evaluation of AMOEBA: a spectral-spatial classification method

Muitispectral remotely sensed images have been treated as arbitrary multivariate spectral data for purposes of clustering and classifying. However, the spatial properties of image data can also be exploited. AMOEBA is a clustering and classification method that is based on a spatially derived model for image data. In an evaluation test, Landsat data were classified with both AMOEBA and a widely used spectral classifier. The test showed that irrigated crop types can be classified as accurately with the AMOEBA method as with the generally used spectral method ISOCLS; the AMOEBA method, however, requires less computer time.

Journal of Applied Photographic Engineering↗