Geography Commons^™

Mountain Passes And Saddle Points, James Bisgard

All Faculty Scholarship for the College of the Sciences

Variational methods find solutions of equations by considering a solution as a critical point of an appropriately chosen function. Local minima and maxima are well-known types of critical points. We explore methods for finding critical points that are neither local maxima or minima, but instead are mountain passes or saddle points. Criteria for the existence of minima or maxima are well known, but those for mountain passes or saddle points are less well known. We give an accessible treatment of some criteria for the existence of such points (including the mountain pass lemma), as well as describe a method that …

Analysis Of Spatial Variability Of Near-Surface Soil Moisture To Increase Rainfall-Runoff Modelling Accuracy In Sw Hungary, P. Hegedüs, S. Czigány, E. Pirkhoffer, L. Balatonyi, Robert Hickey

All Faculty Scholarship for the College of the Sciences

Between September 5, 2008 and September 5, 2009, near-surface soil moisture time series were collected in the northern part of a 1.7 km2 watershed in SWHungary at 14 monitoring locations using a portable TDR-300 soil moisture sensor. The objectives of this study are to increase the accuracy of soil moisture measurement at watershed scale, to improve flood forecasting accuracy, and to optimize soil moisture sensor density.

According to our results, in 10 of 13 cases, a strong correlation exists between the measured soil moisture data of Station 5 and all other monitoring stations; Station 5 is considered representative for the …

Mapsnap System To Perform Vector-To-Raster Fusion, Boris Kovalerchuk, Peter Doucette, Gamal Seedahmed, Jerry Tagestad, Sergei Kovalerchuk, Brian Graff

All Faculty Scholarship for the College of the Sciences

As the availability of geospatial data increases, there is a growing need to match these datasets together. However, since these datasets often vary in their origins and spatial accuracy, they frequently do not correspond well to each other, which create multiple problems. To accurately align with imagery, analysts currently either: 1) manually move the vectors, 2) perform a labor-intensive spatial registration of vectors to imagery, 3) move imagery to vectors, or 4) redigitize the vectors from scratch and transfer the attributes. All of these are time consuming and labor-intensive operations. Automated matching and fusing vector datasets has been a subject …