Geology topics

M.P. Finn

Publications and source records attributed to M.P. Finn.

4 recordsLinked to original sources

USGS2013

Effects of sampling interval on spatial patterns and statistics of watershed nitrogen concentration

This study investigates how spatial patterns and statistics of a 30 m resolution, model-simulated, watershed nitrogen concentration surface change with sampling intervals from 30 m to 600 m for every 30 m increase for the Little River Watershed (Georgia, USA). The results indicate that the mean, standard deviation, and variogram sills do not have consistent trends with increasing sampling intervals, whereas the variogram ranges remain constant. A sampling interval smaller than or equal to 90 m is necessary to build a representative variogram. The interpolation accuracy, clustering level, and total hot spot areas show decreasing trends approximating a logarithmic function. The trends correspond to the nitrogen variogram and start to level at a sampling interval of 360 m, which is therefore regarded as a critical spatial scale of the Little River Watershed. Copyright ?? 2009 by Bellwether Publishing, Ltd. All right reserved.

GIScience and Remote Sensing↗

USGS2009

Data layer integration for the national map of the united states

The integration of geographic data layers in multiple raster and vector formats, from many different organizations and at a variety of resolutions and scales, is a significant problem for The National Map of the United States being developed by the U.S. Geological Survey. Our research has examined data integration from a layer-based approach for five of The National Map data layers: digital orthoimages, elevation, land cover, hydrography, and transportation. An empirical approach has included visual assessment by a set of respondents with statistical analysis to establish the meaning of various types of integration. A separate theoretical approach with established hypotheses tested against actual data sets has resulted in an automated procedure for integration of specific layers and is being tested. The empirical analysis has established resolution bounds on meanings of integration with raster datasets and distance bounds for vector data. The theoretical approach has used a combination of theories on cartographic transformation and generalization, such as T??pfer's radical law, and additional research concerning optimum viewing scales for digital images to establish a set of guiding principles for integrating data of different resolutions.

Cartographic Perspectives↗

USGS2008

An assessment of the effects of cell size on AGNPS modeling of watershed runoff

This study investigates the changes in simulated watershed runoff from the Agricultural NonPoint Source (AGNPS) pollution model as a function of model input cell size resolution for eight different cell sizes (30 m, 60 m, 120 m, 210 m, 240 m, 480 m, 960 m, and 1920 m) for the Little River Watershed (Georgia, USA). Overland cell runoff (area-weighted cell runoff), total runoff volume, clustering statistics, and hot spot patterns were examined for the different cell sizes and trends identified. Total runoff volumes decreased with increasing cell size. Using data sets of 210-m cell size or smaller in conjunction with a representative watershed boundary allows one to model the runoff volumes within 0.2 percent accuracy. The runoff clustering statistics decrease with increasing cell size; a cell size of 960 m or smaller is necessary to indicate significant high-runoff clustering. Runoff hot spot areas have a decreasing trend with increasing cell size; a cell size of 240 m or smaller is required to detect important hot spots. Conclusions regarding cell size effects on runoff estimation cannot be applied to local watershed areas due to the inconsistent changes of runoff volume with cell size; but, optimal cells sizes for clustering and hot spot analyses are applicable to local watershed areas due to the consistent trends.

Cartography and Geographic Information Science↗

USGS2004

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↗