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M. Bearden

Publications and source records attributed to M. Bearden.

2 recordsLinked to original sources

Geospatial data resampling and resolution effects on watershed modeling: A case study using the agricultural non-point source pollution model

Researchers have been coupling geographic information systems (GIS) data handling and processing capability to watershed and waterquality models for many years. This capability is suited for the development of databases appropriate for water modeling. However, it is rare for GIS to provide direct inputs to the models. To demonstrate the logical procedure of coupling GIS for model parameter extraction, we selected the Agricultural Non-Point Source (AGNPS) pollution model. Investigators can generate data layers at various resolutions and resample to pixel sizes to support models at particular scales. We developed databases of elevation, land cover, and soils at various resolutions in four watersheds. The ability to use multiresolution databases for the generation of model parameters is problematic for grid-based models. We used database development procedures and observed the effects of resolution and resampling on GIS input datasets and parameters generated from those inputs for AGNPS. Results indicate that elevation values at specific points compare favorably between 3- and 30-m raster datasets. Categorical data analysis indicates that land cover classes vary significantly. Derived parameters parallel the results of the base GIS datasets. Analysis of data resampled from 30-m to 60-, 120-, 210-, 240-, 480-, 960-, and 1920-m pixels indicates a general degradation of both elevation and land cover correlations as resolution decreases. Initial evaluation of model output values for soluble nitrogen and phosphorous indicates similar degradation with resolution. ?? Springer-Verlag 2004.

Journal of Geographical Systems↗

Projecting global datasets to achieve equal areas

Scientists routinely accomplish global modeling in the raster domain, but recent research has indicated that the transformation of large areas through map projection equations leads to errors. This research attempts to gauge the extent of map projection and resampling effects on the tabulation of categorical areas by comparing the results of three datasets for seven common projections. The datasets, Global Land Cover, Holdridge Life Zones, and Global Vegetation, were compiled at resolutions of 30 arc-second, 1/2 degree, and 1 degree, respectively. These datasets were projected globally from spherical coordinates to plane representations. Results indicate significant problems in the implementation of global projection transformations in commercial software, as well as differences in areal accuracy across projections. The level of raster resolution directly affects the accuracy of areal tabulations, with higher resolution yielding higher accuracy. If the raster resolution is high enough for individual pixels to approximate points, the areal error tends to zero. The 30-arc-second cells appear to approximate this condition.

Cartography and Geographic Information Science↗