A Technique for Building Representation in Oblique View Maps of Modern Urban Areas

Abstract

This paper presents a technique for creating oblique view maps of urban areas. We identify and apply cartographic and cognitive principles to develop a solution in the context of state-of-art geographic information systems. The gap in the ability of these systems to render three-dimensional buildings into maps is addressed. At the core of our solution is a building facade modelling approach that supports varying degrees of abstraction. This is achieved by introducing a concept of 'facade waveforms' and representing building facades as combinations of these waveforms. A Fourier series approximation of the waveforms is used during the rendering processes resulting in an elegant solution to anti-aliasing. The formulation retains the semantic information in the representation that enables meaningful extensions like night time facade generation. The solution is implemented as a pixel shader and therefore leads to a large reduction in texture memory requirement compared with existing building rendering techniques. Additionally, in the case of web based systems, there is significant reduction in bandwidth requirement. We highlight the features of the proposed solution by generating demonstrative maps and images.     

The National Geospatial Program

Fragmentary river segments have to be reconnected before addressing various routing and tracking problems. Elevation determines drainage directions, so the partial heights available through LiDAR may provide useful hints on how the segments should be joined. However, it is not trivial how this information can be applied. This paper bridges this gap by proposing the induced structure approach, which first approximates a terrain compatible with those observations, and then derives a river network from that induced terrain. Since the network is derived from an induced terrain that honors the partial observations, we expect that the derived river network will enforce most restrictions imposed by the partial observations. This paper also provides specifics on the implementation. In the first step regarding terrain reconstruction, we find that the optimal scheme depends on the height sample distribution. If the samples are sparsely yet evenly distributed, natural neighbor interpolation with stream burning (NN-SB) is the most cost-effective. If the samples are offered only at the given river locations, the hydrology-aware version of Over determined Palladian Partial Differential Equation (HA-ODETLAP) should be used instead. In the second step concerning river derivation, we find it necessary to favor those given river locations. Otherwise they will be missed out. We set their respective initial water amounts to the critical accumulation level to ensure a river flows across them. In the subsequent branch thinning process, those locations are protected from being trimmed. We foresee applications of our solution framework in a few 2D and 3D network tracing problems with similar observation distribution, like dendrite network reconstruction.     

Semi-Automatic Modeling of Buildings from Digital Surface Models

Semi-automatic building detection and extraction is a topic of growing interest due to its potential application in such areas as cadastral information systems, cartographic revision, and GIS. One of the existing strategies for building extraction is to use a digital surface model (DSM) represented by a cloud of known points on a visible surface, and comprising features such as trees or buildings. Conventional surface modeling using stereo-matching techniques has its drawbacks, the most obvious being the effect of building height on perspective, shadows, and occlusions. The laser scanner, a recently developed technological tool, can collect accurate DSMs with high spatial frequency. This paper presents a methodology for semi-automatic modeling of buildings which combines a region-growing algorithm with line-detection methods applied over the DSM.     

On the Uncertainty of Local Shape of Lines and Surfaces

Modeling line or surface phenomena digitally involves two tasks: discretization of the phenomenon, which yields a finite set of data, and subsequent interpolation, which reconstructs the continuum. Many mathematical techniques exist for the latter task, and most methods require a number of parameters to be specified. The shape of digital line or surface models between the data points (that is, the local shape) and the information derived from these models both depend on the selected method and, possibly, on the specification of parameters. The reconstruction of the continuum thus introduces uncertainty. This paper examines the sources and effects of this type of uncertainty. For this purpose, the modeling of lines and surfaces is separated into an abstraction, an implementation, and measurement. The individual factors affecting uncertainty of local shape in each step are identified and discussed. The paper concludes that local shape uncertainty, unlike positional uncertainty of given data, cannot be numerically assessed. Instead, measures of plausibility have to be used to denote the quality of digital models of lines and surfaces. Finally, the concept and potential problems of future empirical investigations are discussed.     

Simulating Complex Adaptive Geographic Systems: A Geographically Aware Intelligent Agent Approach

The objective of this paper is to present a spatially explicit agent-based simulation framework with a supporting software package to explore complex adaptive geographic systems. This framework is particularly suitable for modeling entities that are contextually aware, knowledge driven, and adaptive because it represents them as geographically aware intelligent agents. Fundamental advances in the explicit representation of contextual information, knowledge structures, and learning processes are needed for modeling intelligent agents situated within geographic systems. The representation of these agents requires the integration of agent-based models, machine learning, and GIS. Existing software packages for agent-based modeling, however, often provide insufficient support for this integration. The agent-based simulation package presented here is specifically designed to achieve such integration by assisting the development of agent-based models from the simulation framework. Object-oriented modeling techniques were used to implement this simulation package, which includes four modules: simulation, visualization, learning, and geoprocessing. In particular, the learning and geoprocessing modules facilitate the representation of adaptive behavior in agents within spatially explicit environments. The utility of the agent-based simulation package is illustrated using two simulation models: one of adaptive elk behavior and another of pedestrian movement. The successful design of the simulation models suggests that the modeling framework with the supporting software package is well suited to the resolution of complex adaptive geographic problems.     

Matrix Line Printer Maps

Areal gray tone symbols produced on standard line printers seldom adhere to acceptable cartographic design standards. The recent development of matrix line printers provides an alternative means of producing more effective map symbolization with a device also suitable for ordinary character output. Matrix printers permit a greater range of gray tones in a regular sequence, more uniform symbol configuration, and improved print quality     

Visual and Statistical Comparisons of Surface Modeling Techniques for Point-based Environmental Data

Existing studies on spatial interpolation tend to overplay statistical perspective, paying little attention the locality and the visual performance of generated surface models. In an attempt to bridge these gaps in literatures, the authors compared the performance of five surface modelling methods, using a set of integrative criteria including absolute and relative statistical accuracy, visual pleasantness and faithfulness of generated surface models, sensitivity to changing sample size and search conditions, and computational intensity. The modeling methods used were: inverse distance, kriging, linear triangulation, minimum curvature, and radial basis functions. Because terrain relief is one of few environmental attributes whose continuous surfaces can be directly observed through appropriate procedures, we used as input data two sets of elevation points sampled irregularly from a USGS 1:24,000 topographical map covering a hilly area. We found that surface modeling methods, even if statistically accurate, may not always ensure a graphically faithful representation of the reality. The surprising result of this study was that the surface models generated from a larger sample were less statistically accurate than those generated from a smaller sample.     

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.     

Spatio-temporal Trends of Diarrheal Mortality of Children in Association with Hydrographic Regions of Brazil

In this paper, we analyze trends in average annual peak timing values (MPT) of pediatric mortality attributed to diarrheal disease in Brazil for the period 1979-1989 using a novel approach for environmental health risk studies, that is using natural boundaries instead of politically derived boundaries to define the unit of analysis (UOA). We evaluate the approach at varying spatial scales: (1) Country-wide based on observed Municipal level mortality data aggregated to Census Micro Regions (CMR); (2) Country-wide based on a grid of 20 Km2 raster cells generated by geostatistical modeling of MPT values; (3) Within eight officially designated Hydrographic Regions of Brazil based on results from the geostatistical models, and (4) Along longitudinal “vectors” of 1 km raster cells defining the stream network (hydrologic regime) within each Hydrographic Region.

At the country level, we found evidence of a trend west to east of increasing MPT over an annual cycle (May to April) using the CMR-level estimates. However, when we examined the model results at finer scales i.e., Hydrographic Regions, we discovered greater geographic heterogeneity in MPT across units. At the spatial scale of the stream network within the Hydrographic Regions, we observed consistent trends of increasing MPT from the source areas (upper watersheds) to downstream locations in some Hydrographic Regions, especially those composed of a single river basin.

Here, trends were no longer predominantly east to west as at the country level, but oriented in the direction of flow of the major river draining the basin. Our study results indicate substantial spatial variation in peak timing of pediatric mortality attributed to diarrheal disease in Brazil over our study period. This could have important ramifications in studies concerning known or suspected risk factors with significant temporal variation over an annual cycle. We found the geographic orientation of trend in mortality peak timing to be highly dependent on the geographic extent and derivation of the UOA. We demonstrate that a UOA based on natural boundaries, e.g., stream segments or watershed boundaries can result in more consistent and robust prediction of trends in mortality peak timing attributed to diarrhea.     

Allied Military Model Making during World War II

It is generally accepted that the three-dimensional nature of the digital terrain model enhances our visualization of surfaces. Modern techniques enable a detailed landscape to be constructed as a facsimile of reality that provides an opportunity to move through or fly over the landscape. Given these benefits, it is little surprise that simulations using digital terrain models are employed as essential visual aids for briefing and training military personnel prior to land, air, and sea operations. Though these capabilities are significant, they are not necessarily, in the basic sense, new. This paper traces the development and examines the role of terrain models made by the Allies during World War II, a period prior to the development of computer-based modeling. Though made from basic materials, these sophisticated terrain models were hand crafted by enlisted sculptors, architects, stage designers, and artists, who carefully modeled a sculpture of the landscape to be an invaluable aid during key military operations of World War II.