Modeling hourly diffuse solar-radiation in the city of São Paulo using a neural-network technique

dIn this work, a perceptron neural-network technique is applied to estimate hourly values of the diffuse solar-radiation at the surface in São Paulo City, Brazil, using as input the global solar-radiation and other meteorological parameters measured from 1998 to 2001. The neural-network verification was performed using the hourly measurements of diffuse solar-radiation obtained during the year 2002. The neural network was developed based on both feature determination and pattern selection techniques. It was found that the inclusion of the atmospheric long-wave radiation as input improves the neural-network performance. on the other hand traditional meteorological parameters, like air temperature and atmospheric pressure, are not as important as long-wave radiation which acts as a surrogate for cloud-cover information on the regional scale. An objective evaluation has shown that the diffuse solar-radiation is better reproduced by neural network synthetic series than by a correlation model. (C) 2004 Elsevier Ltd. All rights reserved.

A Featureless Approach to 3D Polyhedral Building Modeling from Aerial Images

This paper presents a model-based approach for reconstructing 3D polyhedral building models from aerial images. The proposed approach exploits some geometric and photometric properties resulting from the perspective projection of planar structures. Data are provided by calibrated aerial images. The novelty of the approach lies in its featurelessness and in its use of direct optimization based on image rawbrightness. The proposed framework avoids feature extraction and matching. The 3D polyhedral model is directly estimated by optimizing an objective function that combines an image-based dissimilarity measure and a gradient score over several aerial images. The optimization process is carried out by the Differential Evolution algorithm. The proposed approach is intended to provide more accurate 3D reconstruction than feature-based approaches. Fast 3D model rectification and updating can take advantage of the proposed method. Several results and evaluations of performance from real and synthetic images show the feasibility and robustness of the proposed approach.

GRASS GIS for the distinction of vegetation from buildings using LiDAR altimetric data

La tecnología LiDAR (Light Detection and Ranging), basada en el escaneado del territorio por un telémetro láser aerotransportado, permite la construcción de Modelos Digitales de Superficie (DSM) mediante una simple interpolación, así como de Modelos Digitales del Terreno (DTM) mediante la identificación y eliminación de los objetos existentes en el terreno (edificios, puentes o árboles). El Laboratorio de Geomática del Politécnico de Milán – Campus de Como- desarrolló un algoritmo de filtrado de datos LiDAR basado en la interpolación con splines bilineares y bicúbicas con una regularización de Tychonov en una aproximación de mínimos cuadrados. Sin embargo, en muchos casos son todavía necesarios modelos más refinados y complejos en los cuales se hace obligatorio la diferenciación entre edificios y vegetación. Este puede ser el caso de algunos modelos de prevención de riesgos hidrológicos, donde la vegetación no es necesaria; o la modelización tridimensional de centros urbanos, donde la vegetación es factor problemático. (...)

Duplicating road patterns in South African informal settlements using procedural techniques

The formation of informal settlements in and around urban complexes has largely been ignored in the context of procedural city modeling. However, many cities in South Africa and globally can attest to the presence of such settlements. This paper analyses the phenomenon of informal settlements from a procedural modeling perspective. Aerial photography from two South African urban complexes, namely Johannesburg and Cape Town is used as a basis for the extraction of various features that distinguish different types of settlements. In particular, the road patterns which have formed within such settlements are analysed, and various procedural techniques proposed (including Voronoi diagrams, subdivision and L-systems) to replicate the identified features. A qualitative assessment of the procedural techniques is provided, and the most suitable combination of techniques identified for unstructured and structured settlements. In particular it is found that a combination of Voronoi diagrams and subdivision provides the closest match to unstructured informal settlements. A combination of L-systems, Voronoi diagrams and subdivision is found to produce the closest pattern to a structured informal settlement.

Diurnal evolution of solar radiation at the surface in the city of São Paulo: Seasonal variation and modeling

Seasonal variations in the diurnal evolution of the global, diffuse and direct solar radiation at the surface, the clearness index, diffuse fraction and direct fraction are described in detail for the City of Sao Paulo, Brazil. The description is based on measurements of global and diffuse solar radiation carried out over 5.25 years. The diffuse component was measured with a shadow-band device. The annual evolution of the amplitude of the diurnal cycle of all radiometric parameters indicates a seasonal pattern with two distinct periods: autumn-winter and spring-summer. About 10% of the observed period was characterized by clear sky days. This seasonal variation is determined by a larger incidence of clear sky days in the autumn-winter period. Reductions of up to 10% in hourly and daily values of global radiation were observed in conjunction with an increase in particulate matter concentration on clear sky days. The pollution effect may be responsible for the discrepancy, of 16%, found between local and more regional estimates of global solar radiation in Sao Paulo. The diurnal evolution of hourly values of monthly-averaged global and diffuse solar radiation were successfully estimated by the empirical expressions derived here. Daily values of monthly-averaged global solar radiation were satisfactorily estimated using the Angstrom expression.

Analysis of Contributions to NO2 Ambient Air Quality Levels in Madrid City (Spain) through Modeling. Implications for the Development of Policies and Air Quality Monitoring

As environmental standards become more stringent (e.g. European Directive 2008/50/EC), more reliable and sophisticated modeling tools are needed to simulate measures and plans that may effectively tackle air quality exceedances, common in large cities across Europe, particularly for NO2. Modeling air quality in urban areas is rather complex since observed concentration values are a consequence of the interaction of multiple sources and processes that involve a wide range of spatial and temporal scales. Besides a consistent and robust multi-scale modeling system, comprehensive and flexible emission inventories are needed. This paper discusses the application of the WRF-SMOKE-CMAQ system to the Madrid city (Spain) to assess the contribution of the main emitting sectors in the region. A detailed emission inventory was compiled for this purpose. This inventory relies on bottom-up methods for the most important sources. It is coupled with the regional traffic model and it makes use of an extensive database of industrial, commercial and residential combustion plants. Less relevant sources are downscaled from national or regional inventories. This paper reports the methodology and main results of the source apportionment study performed to understand the origin of pollution (main sectors and geographical areas) and define clear targets for the abatement strategy. Finally the structure of the air quality monitoring is analyzed and discussed to identify options to improve the monitoring strategy not only in the Madrid city but the whole metropolitan area.

Application of a digital elevation model for flood modeling for the Pagsangaan River in Leyte

Flood related scientific and community-based data are rarely systematically collected and analysed in the Philippines. Over the last decades the Pagsangaan River Basin, Leyte, has experienced several flood events. However, documentation describing flood characteristics such as extent, duration or height of these floods are close to non-existing. To address this issue, computerized flood modelling was used to reproduce past events where there was data available for at least partial calibration and validation. The model was also used to provide scenario-based predictions based on A1B climate change assumptions for the area. The most important input for flood modelling is a Digital Elevation Model (DEM) of the river basin. No accurate topographic maps or Light Detection And Ranging (LIDAR)-generated data are available for the Pagsangaan River. Therefore, the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Map (GDEM), Version 1, was chosen as the DEM. Although the horizontal spatial resolution of 30 m is rather desirable, it contains substantial vertical errors. These were identified, different correction methods were tested and the resulting DEM was used for flood modelling. The above mentioned data were combined with cross-sections at various strategic locations of the river network, meteorological records, river water level, and current velocity to develop the 1D-2D flood model. SOBEK was used as modelling software to create different rainfall scenarios, including historic flooding events. Due to the lack of scientific data for the verification of the model quality, interviews with local stakeholders served as the gauge to judge the quality of the generated flood maps. According to interviewees, the model reflects reality more accurately than previously available flood maps. The resulting flood maps are now used by the operations centre of a local flood early warning system for warnings and evacuation alerts. Furthermore these maps can serve as a basis to identify flood hazard areas for spatial land use planning purposes.

Modeling predictors of risky drug use behavior among male street laborers in urban Vietnam

Background The application of theoretical frameworks for modeling predictors of drug risk among male street laborers remains limited. The objective of this study was to test a modified version of the IMB (Information-Motivation-Behavioral Skills Model), which includes psychosocial stress, and compare this modified version with the original IMB model in terms of goodness-of-fit to predict risky drug use behavior among this population. Methods In a cross-sectional study, social mapping technique was conducted to recruit 450 male street laborers from 135 street venues across 13 districts of Hanoi city, Vietnam, for face-to-face interviews. Structural equation modeling (SEM) was used to analyze data from interviews. Results Overall measures of fit via SEM indicated that the original IMB model provided a better fit to the data than the modified version. Although the former model was able to predict a lesser variance than the latter (55% vs. 62%), it was of better fit. The findings suggest that men who are better informed and motivated for HIV prevention are more likely to report higher behavioral skills, which, in turn, are less likely to be engaged in risky drug use behavior. Conclusions This was the first application of the modified IMB model for drug use in men who were unskilled, unregistered laborers in urban settings. An AIDS prevention program for these men should not only distribute information and enhance motivations for HIV prevention, but consider interventions that could improve self-efficacy for preventing HIV infection. Future public health research and action may also consider broader factors such as structural social capital and social policy to alter the conditions that drive risky drug use among these men.

Built heritage management systems : the framework of a digital tool for the conservation of Brisbane City Hall

Brisbane City Hall (BCH) is arguably one of Brisbane’s most notable and iconic buildings. Serving as the public’s central civic and municipal building since 1930, the importance of this heritage listed building to cultural significance and identity is unquestionable. This attribute is reflected within the local government, with a simplified image of the halls main portico entrance supplying Brisbane City Council with its insignia and trademark signifier. Regardless of these qualities, this building has been neglected in a number of ways, primarily in the physical sense with built materials, but also, and just as importantly, through inaccurate and undocumented works. Numerous restoration and renovation works have been undertaken throughout BCH’s lifetime, however the records of these amendments are far and few between. Between 2010 and 2013, BCH underwent major restoration works, the largest production project undertaken on the building since its initial construction. Just prior to this conservation process, the full extent of the buildings deterioration was identified, much of which there was little to no original documentation of. This has led to a number of issues pertaining to what investigators expected to find within the building, versus what was uncovered (the unexpected), which have resulted directly from this lack of data. This absence of record keeping is the key factor that has contributed to the decay and unknown deficiencies that had amassed within BCH. Accordingly, this raises a debate about the methods of record keeping, and the need for a more advanced process that is able to be integrated within architectural and engineering programs, whilst still maintaining the ability to act as a standalone database. The immediate objective of this research is to investigate the restoration process of BCH, with focus on the auditorium, to evaluate possible strategies to record and manage data connected to building pathology so that a framework can be developed for a digital heritage management system. The framework produced for this digital tool will enable dynamic uses of a centralised database and aims to reduce the significant data loss. Following an in-depth analysis of this framework, it can be concluded that the implementation of the suggested digital tool would directly benefit BCH, and could ultimately be incorporated into a number of heritage related built form.

Multi-agent systems for modeling high penetration photovoltaic system impacts in distribution networks

This paper reviews the use of multi-agent systems to model the impacts of high levels of photovoltaic (PV) system penetration in distribution networks and presents some preliminary data obtained from the Perth Solar City high penetration PV trial. The Perth Solar City trial consists of a low voltage distribution feeder supplying 75 customers where 29 consumers have roof top photovoltaic systems. Data is collected from smart meters at each consumer premises, from data loggers at the transformer low voltage (LV) side and from a nearby distribution network SCADA measurement point on the high voltage side (HV) side of the transformer. The data will be used to progressively develop MAS models.

Modeling Equitable Distribution of Water: Dynamic Inversion-Based Controller Approach

It is a well-known fact that most of the developing countries have intermittent water supply and the quantity of water supplied from the source is also not distributed equitably among the consumers. Aged pipelines, pump failures, and improper management of water resources are some of the main reasons for it. This study presents the application of a nonlinear control technique to overcome this problem in different zones in the city of Bangalore. The water is pumped to the city from a large distance of approximately 100km over a very high elevation of approximately 400m. The city has large undulating terrain among different zones, which leads to unequal distribution of water. The Bangalore, inflow water-distribution system (WDS) has been modeled. A dynamic inversion (DI) nonlinear controller with proportional integral derivative (PID) features (DI-PID) is used for valve throttling to achieve the target flows to different zones of the city. This novel approach of equitable water distribution using DI-PID controllers that can be used as a decision support system is discussed in this paper.

LANDSCAPE DYNAMICS MODELING THROUGH INTEGRATED MARKOV, FUZZY-AHP AND CELLULAR AUTOMATA

Multi temporal land use information were derived using two decades remote sensing data and simulated for 2012 and 2020 with Cellular Automata (CA) considering scenarios, change probabilities (through Markov chain) and Multi Criteria Evaluation (MCE). Agents and constraints were considered for modeling the urbanization process. Agents were nornmlized through fiizzyfication and priority weights were assigned through Analytical Hierarchical Process (AHP) pairwise comparison for each factor (in MCE) to derive behavior-oriented rules of transition for each land use class. Simulation shows a good agreement with the classified data. Fuzzy and AHP helped in analyzing the effects of agents of growth clearly and CA-Markov proved as a powerful tool in modelling and helped in capturing and visualizing the spatiotemporal patterns of urbanization. This provided rapid land evaluation framework with the essential insights of the urban trajectory for effective sustainable city planning.