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This paper describes a research and development effort on a GIS‐based pipeline planning system (GIS‐based PPS). Research was first conducted to identify the aspects of pipeline planning and pipeline network design that could benefit from a computer assisted approach, and the recent advancements in information technology. This paper describes a cohesive computer environment that integrates the hydraulic analysis and geographic information processing with a graphic user interface (GUI), in order to improve the effectiveness of pipeline design functions. An interactive system prototype was implemented and is currently being applied in real‐world pipeline network planning and design for municipal and industrial water conveyance.

The purpose of this paper is threefold: first, to present a framework of five “facets,” i.e., distinct but complementary ways in which the observed appeal of a consumer shopping site’s features can potentially be generalized across product/service domains (the authors call this framework the feature appeal generalization perspective); second, to determine if and how observed feature preferences for consumer electronics, bookstores, and sites “in general” generalize across domains; third, to test hypotheses about the impact of frequency of domain usage upon feature generalizability.

Via an online survey administered in a controlled laboratory setting, 313 respondents evaluated 26 website features in three domains (books, electronics, general) for a total of 24,414 preference judgments.

Two facets, individual feature values and within domain evaluative dimensions, revealed minimal generalizability, while there was moderate comparability across all domains in between domain feature correspondence. Personal preference elevation could be generalized between books and general, but not between these two and electronics. Differentiating dimensions showed that preferences were not generalizable from electronics to books and general because consumers wanted electronics features to provide “flashy sizzle” and books/general features to give “comfortable safety.” As hypothesized, patterns of generalizability coincided with frequency of domain usage.

Practitioners should not apply published studies of feature appeal to their domain of interest unless those studies directly analyzed that domain. Scientists should incorporate all five facets in modeling what attracts consumers to commercial websites.

This is the first multidimensional analysis of the generalizability of site feature appeal across business-to-consumer product/service domains, and the first to propose this integrated evaluative framework with its unique facets.

The purpose of this study is to evaluate the reliability of the technique for estimating solar radiation in areas of rough topography and to detect the source of error and means for improvement.

Spatial data of the study area in the form of digital elevation model (DEM) coupled with geographic information system (GIS) were used to estimate the monthly solar radiation at locations with rough topography. The generated data were compared with measured data collected from all the selected locations using NASA data.

The results show that the variation in topographic parameters has a strong influence on the amount of solar radiation received by two close locations. However, the method performed well for solar radiation estimated in the areas of rough topography.

The proposed approach overestimates the monthly solar radiation as compared with NASA data due to the impact of topographic parameters accounted for by the model which are not accounted by conventional methods of measurements. This approach can be improved by incorporating the reflected component of radiation in the model used to estimate the solar radiation implemented in the GIS.

The approach of using GIS with DEM to estimate solar radiation enables to identify the spatial variability in solar radiation between two closest locations due to the influence of topographic parameters, and this will assist in proper energy planning and decision making for optimal areas of solar photovoltaic installation.

Within the past 20 years hiking and backpacking have enjoyed rapid growth among Americans as favorite outdoor activities. From 1965 to 1977 the number of hikers almost tripled, from 9.9 million to 28.1 million, while national forest visitor days among hikers and mountaineers increased from 4 million in 1966 to 11 million in 1979. Accompanying this growth in interest has been a boom in books about the sport. These include both “how‐to‐do‐it” volumes and guides to specific geographical areas. Each year brings another spate of books, yet to this compiler's knowledge no bibliography of hiking guides to the Rocky Mountains, one of North America's premier outdoor regions, has yet been attempted. This bibliography is an effort to correct that situation.

Peat swamp forest fire hazard areas were identified and mapped by integrating GIS‐grid‐based and multi‐criteria analysis to provide valuable information about the areas most likely to be affected by fire in the Pekan District, south of Pahang, Malaysia. A spatially weighted index model was implemented to develop the fire hazard assessment model used in this study. Fire‐causing factors such as land use, road network, slope, aspect and elevation data were used in this application. A two‐mosaic Landsat TM scene was used to extract land use parameters of the study area. A triangle irregular network was generated from the digitized topographic map to produce a slope risk map, an aspect risk map and an elevation risk map. Spatial analysis was applied to reclassify and overlay all grid hazard maps to produce a final peat swamp forest fire hazard map. To validate the model, the actual fire occurrence map was compared with the fire hazard zone area derived from the model. The model can be used only for specific areas, and other criteria should be considered if the model is used for other areas. The results show that most of the actual fire spots are located in very high and high fire risk zones identified by the model.

The purpose of this paper is to build a classification system which mimics the perceptual ability of human vision, in gathering knowledge about the structure, content and the surrounding environment of a real-world natural scene, at a quick glance accurately. This paper proposes a set of novel features to determine the gist of a given scene based on dominant color, dominant direction, openness and roughness features.

The classification system is designed at two different levels. At the first level, a set of low level features are extracted for each semantic feature. At the second level the extracted features are subjected to the process of feature evaluation, based on inter-class and intra-class distances. The most discriminating features are retained and used for training the support vector machine (SVM) classifier for two different data sets.

Accuracy of the proposed system has been evaluated on two data sets: the well-known Oliva-Torralba data set and the customized image data set comprising of high-resolution images of natural landscapes. The experimentation on these two data sets with the proposed novel feature set and SVM classifier has provided 92.68 percent average classification accuracy, using ten-fold cross validation approach. The set of proposed features efficiently represent visual information and are therefore capable of narrowing the semantic gap between low-level image representation and high-level human perception.

The method presented in this paper represents a new approach for extracting low-level features of reduced dimensionality that is able to model human perception for the task of scene classification. The methods of mapping primitive features to high-level features are intuitive to the user and are capable of reducing the semantic gap. The proposed feature evaluation technique is general and can be applied across any domain.

The applications of geographic information systems (GIS) are described in the civil engineering literature for generation, visualisation and evaluation of the construction schedule. GIS use is also explored for construction quantity takeoffs and cost estimation. The purpose of this paper is to supplement the already explored capabilities of GIS in construction by providing the methodology for direct sunlight visualisation on buildings.

The proposed methodology for direct sunlight visualisation is to calculate the solar angles and use them for spatial distribution representation of the amount of sunlight received on different faces of a building by rendering it with the colour of varied gradients. The colour gradient on any face of a building depends upon the amount of direct sunlight received. The solar gain is demonstrated through the multi‐dimensional data visualisation like sun angle variations with diurnal and annual cycles in a navigable 3D animation.

GIS‐based methodology provides the planner a way to control the natural lighting and solar gain on a building which can be combined with the project schedule, quantity takeoffs, cost estimate and 4D visualisation in a single environment. Beginning with this idea, the planner may store and share information about a construction project, site and surrounding geography.

Most of the existing 4D CAD technologies do not have project management capabilities and are used mainly for the planning and design stage of a construction project. In comparison, GIS‐based tools may be used in different stages. These are more management‐based and allow more collaborative and cooperative relationships between designer, constructor and client. By using a GIS‐based approach, construction documents like schedules, drawings, quantity takeoffs, cost estimates, project specifications and direct sunlight visualisations are more consistent with each other.

Preservation of historic structures meets ecological criteria of sustainable development. In Mount Lebanon, the traditional house is a cultural asset built of native stone one-meter thick double-wythe walls. Today, lack of public policies is causing those environmental assets to approach extinction. The paper aims to discuss this issue.

The methodology uses multivariate regression on 128 data points. A mathematical model is developed and empirically tested on public attitudes toward restoration. Independent variables represent the need for protectionist policies, X1; contribution of restoration to environmental sustainability, X2; contribution to culture, X3; and financial benefits, X4.

It is found that stone houses transfer heat significantly slower than modern construction. There is a statistically significant and positive correlation with X1, X2, and X3, but negative with X4, most likely due to favoring return on investment of multistory buildings over the attractiveness of stone houses.

As future research implications, the undergirding of urban planning policies need to be revisited. Current policies neither protect heritage, nor offer legal means to restore heritage houses.

Practical implications include revisions to building laws in Mount Lebanon, as they marginalize old stone structures. Environmental valuation techniques, use value and existence value, are recommended.

Social awareness needs to be built about valuation techniques to account for complex assets that cannot be approximated through short-term real estate market price. Social rather than financial cost-benefit analysis must be performed to quantify environmental assets.

This research illustrates a pilot restoration project with critical issues faced by heritage stone houses. These assets are underrepresented in building laws which warrants social and environmental activism.