Morphological Image Analysis of Transmission Systems

This paper proposes morphological decimation of power network images for the purpose of analysis. The method creates a graphical image of a power network with a thickness of lines proportional to their respective rated megavolt-ampere capacity. Through morphological tools, the network image is decimated. This decimation process eliminates weak lines. Thus, strongly connected subnetworks emerge. This method of identification of several strongly connected subnetworks in a large network is tested on an IEEE test system. The method provides a quick bird's eye view of the strong subnetworks in a power system. Creation and decimation of network images to analyze other facets of the transmission system are also presented and discussed

Analysis of Geophysical Networks Derived From Multiscale Digital Elevation Models: A Morphological Approach

We provide a simple and elegant framework based on morphological transformations to generate multiscale digital elevation models (DEMs) and to extract topologically significant multiscale geophysical networks. These terrain features at multiple scales are collectively useful in deriving scaling laws, which exhibit several significant terrain characteristics. We present results derived from a part of Cameron Highlands DEM

Delineation of valleys and valley floors

Methods to automatically derive landforms have typically focused on pixel-based, bottom-up approaches and most commonly on the derivation of topographic eminences. In this paper we describe an object-based, top-down algorithm to identify valley floors. The algorithm is based on a region growing approach, seeded by thalwegs with pixels added to the region according to a threshold gradient value. Since such landforms are fiat we compare the results of our algorithm for a particular valley with a number of textual sources describing that valley. In a further comparison, we computed a pixel-based six-fold morphometric classification for regions we classified as either being, or not being, valley floor. The regions classified as valley floor are dominated by pla nar slopes and channels, though the algorithm is robust enough to allow local convexities to be classified as within the valley floor. Future work will explore the delineation of valley sides, and thus complete valleys