Papers by Barbara Buttenfield
AGU Fall Meeting Abstracts, Dec 1, 2011
ABSTRACT Terrestrial laser scanning (TLS) represents a new and particularly effective remote sens... more ABSTRACT Terrestrial laser scanning (TLS) represents a new and particularly effective remote sensing technique for investigating geomorphologic processes. Unfortunately, TLS data are commonly characterized by extremely large volume, heterogeneous point distribution, and erroneous measurements, raising challenges for applied researchers. To facilitate efficient and accurate use of TLS in geomorphology, and to improve accessibility for TLS processing in commercial software environments, we are developing a filtering method for raw TLS data to: eliminate data redundancy; produce a more uniformly spaced dataset; remove erroneous measurements; and maintain the ability of the TLS dataset to accurately model terrain. Our method conducts local aggregation of raw TLS data using a 3-D search algorithm based on the geometrical expression of expected random errors in the data. This approach accounts for the estimated accuracy and precision limitations of the instruments and procedures used in data collection, thereby allowing for identification and removal of potential erroneous measurements prior to data aggregation. Initial tests of the proposed technique on a sample TLS point cloud required a modest processing time of approximately 100 minutes to reduce dataset volume over 90 percent (from 12,380,074 to 1,145,705 points). Preliminary analysis of the filtered point cloud revealed substantial improvement in homogeneity of point distribution and minimal degradation of derived terrain models. We will test the method on two independent TLS datasets collected in consecutive years along a non-vegetated reach of the North Fork Toutle River in Washington. We will evaluate the tool using various quantitative, qualitative, and statistical methods. The crux of this evaluation will include a bootstrapping analysis to test the ability of the filtered datasets to model the terrain at roughly the same accuracy as the raw datasets.
... CAPTURE AND DATA MODELING Barbara P. Buttenfield, University of Colorado-Boulder (USA) babs@c... more ... CAPTURE AND DATA MODELING Barbara P. Buttenfield, University of Colorado-Boulder (USA) [email protected] Charlie Frye, ESRI (USA) [email protected] Introduction Data capture of base cartographic features continues as a major activity in national ...
Lecture notes in geoinformation and cartography, 2017
CRC Press eBooks, Nov 25, 2020
Annals of the American Association of Geographers, Jun 9, 2017
Small area health estimates are important for studying environmental exposure, disease transmissi... more Small area health estimates are important for studying environmental exposure, disease transmission, and health outcomes at the local scale. Yet, to protect privacy, the majority of publicly available health data are aggregated within larger spatial units such as states or counties. This article describes a method to generate small area mortality estimates from individual microdata that are available only for larger geographic entities. The mortality estimates are based on the probabilistic reweighting and spatial allocation of a population constructed by combining the individual-level microdata with census tract–level summary data. The generated mortality counts can be used to explore local mortality patterns and identify clusters of mortality from various causes. Validation of the allocated death counts against actual restricted-use census tract–level death counts suggests that the estimated counts reliably duplicate the total mortality patterns found in the actual data. The allocations of cause-specific mortality outcomes are less accurate, however.
International Journal of Remote Sensing, Feb 26, 2019
ABSTRACT Terrain is modelled in Geographic Information Science on a grid, assuming that elevation... more ABSTRACT Terrain is modelled in Geographic Information Science on a grid, assuming that elevation values are constant within any single pixel of a Digital Elevation Model (DEM). Pixels are considered flat and rigid, for computational simplicity (a ‘rigid pixel’ paradigm). This paradigm does not account for the slope and curvature of terrain within each pixel, generating imprecise measurements, particularly as pixel size increases or in uneven terrain. This paper relaxes the rigid pixel assumption, allowing for possible sub-pixel variations in slope and curvature (a ‘surface-adjusted’ paradigm). This paper compares different interpolation methods to investigate sub-pixel variations for estimating elevation of arbitrary points given a regular grid. Tests interpolating elevation values for 20,000 georeferenced off-centroid random points from a regular grid DEM are presented, using a variety of exact and inexact local deterministic interpolation methods within contiguity configurations incorporating first and second order neighbours. The paper examines the accuracy of surface-adjusted estimations across a progression of spatial resolutions (10 m, 30 m, 100 m, and 1,000 m DEMs) and a suite of terrain types varying in latitude, altitude, slope, and roughness, validating off-centre estimates against direct elevation measurements on 3 m resolution lidar DEM. Results illustrate that the Bi-quadratic and Bi-cubic interpolation methods outperform Weighted Average, Linear, and Bi-linear methods at coarse resolutions and in rough or non-uniform terrain. In smooth or flat terrain and at finest resolutions, the interpolation method impacts estimation accuracy less or not at all. The type of contiguity configuration appears to play a role in estimation errors as well, with tighter neighbourhoods exhibiting higher accuracy. The analysis also examined regularized mathematical surfaces, adding autocorrelated randomly distributed noise to simulate terrain. The results of experiments based on regularized smooth mathematical surfaces do not translate directly to terrain modelling. The analysis also considers the balance between the increased computation times needed to measure surface-adjusted elevation against improvements in accuracy.
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Digital Library Use, 2003
Introduction: Digital Libraries as Sociotechnical Systems. Nancy A. Van House, Ann P. Bishop and ... more Introduction: Digital Libraries as Sociotechnical Systems. Nancy A. Van House, Ann P. Bishop and Barbara P. Buttenfield. This book is about digital libraries as sociotechnical systems -- networks of technology, information, documents, people, and practices. ...
Cartography and Geographic Information Science, 2015
Uploads
Papers by Barbara Buttenfield