Techniques for augmenting the visualisation of dynamic raster surfaces

Despite their aesthetic appeal and condensed nature, dynamic raster surface representations such as a temporal series of a landform and an attribute series of a socio-economic attribute of an area, are often criticised for the lack of an effective information delivery and interactivity.In this work, we readdress some of the earlier raised reasons for these limitations -information-laden quality of surface datasets, lack of spatial and temporal continuity in the original data, and a limited scope for a real-time interactivity. We demonstrate with examples that the use of four techniques namely the re-expression of the surfaces as a framework of morphometric features, spatial generalisation, morphing, graphic lag and brushing can augment the visualisation of dynamic raster surfaces in temporal and attribute series

Weighted and metric surface networks - new insights and an interactive application for their generalisation in Tcl/Tk

The idea of characterising the different forms of natural topographic surfaces by a topologicalmodel based on their fundamental surface features has attracted many proposals. In this paper, adetailed discussion and new proposals on various issues related to the concept, generation, andvisualisation of two graph theoretic based surface topology data structures ? Weighted SurfaceNetworks and their improved version, Metric Surface Networks - are presented. Also presented isan interactive Tcl/Tk application called Surface Topology Toolkit, which has been developed tosupport the discussion on aspects of their generalisation and visualisation. The highlight of theSurface Topology Toolkit is the utility to allow arbitrary contraction unlike the usual verteximportance based criterion. This paper proposes that effective automated surface topologymodelling based on these surface networks requires (a) further research in the development of?computing? algorithms that will accurately locate critical surface points, be able to establishtopological links, and also check topological consistency, (b) transforming their 2D straight linegraph like appearance to 3D to improve visualisation and contraction, and (c) assessment and userawarenessabout the effects of each type of contraction criterion on the topography

Surface networks

© Copyright CASA, UCL. The desire to understand and exploit the structure of continuous surfaces is common to researchers in a range of disciplines. Few examples of the varied surfaces forming an integral part of modern subjects include terrain, population density, surface atmospheric pressure, physico-chemical surfaces, computer graphics, and metrological surfaces. The focus of the work here is a group of data structures called Surface Networks, which abstract 2-dimensional surfaces by storing only the most important (also called fundamental, critical or surface-specific) points and lines in the surfaces. Surface networks are intelligent and “natural ” data structures because they store a surface as a framework of “surface ” elements unlike the DEM or TIN data structures. This report presents an overview of the previous works and the ideas being developed by the authors of this report. The research on surface networks has fou

Two mechanisms for optic flow and scale change processing of looming

Published in final edited form as: J Vis. ; 11(3): . doi:10.1167/11.3.5.The detection of looming, the motion of objects in depth, underlies many behavioral tasks, including the perception of self-motion and time-to-collision. A number of studies have demonstrated that one of the most important cues for looming detection is optic flow, the pattern of motion across the retina. Schrater et al. have suggested that changes in spatial frequency over time, or scale changes, may also support looming detection in the absence of optic flow (P. R. Schrater, D. C. Knill, & E. P. Simoncelli, 2001). Here we used an adaptation paradigm to determine whether the perception of looming from optic flow and scale changes is mediated by single or separate mechanisms. We show first that when the adaptation and test stimuli were the same (both optic flow or both scale change), observer performance was significantly impaired compared to a dynamic (non-motion, non-scale change) null adaptation control. Second, we found no evidence of cross-cue adaptation, either from optic flow to scale change, or vice versa. Taken together, our data suggest that optic flow and scale changes are processed by separate mechanisms, providing multiple pathways for the detection of looming.We thank Jonathan Victor and the anonymous reviewers of the paper for feedback and suggestions regarding the stimuli used here. This work was supported by NIH grant R01NS064100 to LMV. (R01NS064100 - NIH)Accepted manuscrip

Farmers' management of rice varietal diversity in the mid-hills of Nepal: implications for on-farm conservation and crop improvement

Season-long monitoring of on-farm rice (Oryza sativa, L.) plots in Nepal explored farmers' decision-making process on the deployment of varieties to agroecosystems, application of production inputs to varieties, agronomic practices and relationship between economic return and area planted per variety. Farmers deploy varieties [landraces (LRs) and modern varieties (MVs)] to agroecosystems based on their understanding of characteristics of varieties and agroecosystems, and the interaction between them. In marginal growing conditions, LRs can compete with MVs. Within an agroecosystem, economic return and area planted to varieties have positive relationship, but this is not so between agroecosystems. LRs are very diverse on agronomic and economic traits; therefore, they cannot be rejected a priori as inferior materials without proper evaluation. LRs have to be evaluated for useful traits and utilized in breeding programmes to generate farmer-preferred materials for marginal environments and for their conservation on-farm

CORRECTING FOR BIASES WHEN ESTIMATING PRODUCTION FUNCTIONS: AN ILLUSION OF THE LAWS OF ALGEBRA?

this paper argues that the true cause of the endogeneity bias that allegedly appears when estimating production functions, and which the literature has tried to deal with since the 1940s, is s imply the result of omitted-variable bias due to an incorrect approximation to an accounting identity. As a result we question recent attempts to solve the problem by developing new estimators.