Data-driven estimation of building interior plans

This work investigates constructing plans of building interiors using learned building measurements. In particular, we address the problem of accurately estimating dimensions of rooms when measurements of the interior space have not been captured. Our approach focuses on learning the geometry, orientation and occurrence of rooms from a corpus of real-world building plan data to form a predictive model. The trained predictive model may then be queried to generate estimates of room dimensions and orientations. These estimates are then integrated with the overall building footprint and iteratively improved using a two-stage optimisation process to form complete interior plans.

The approach is presented as a semi-automatic method for constructing plans which can cope with a limited set of known information and constructs likely representations of building plans through modelling of soft and hard constraints. We evaluate the method in the context of estimating residential house plans and demonstrate that predictions can effectively be used for constructing plans given limited prior knowledge about the types of rooms and their topology.     

A Time Neighborhood Method for the Verification of Landfalling Typhoon Track Forecast

Landfalling typhoons can cause disasters over large regions. The government and emergency responders need to take measures to mitigate disasters according to the forecast of landfall position, while slight timing error can be ignored. The reliability of operational model forecasts of typhoon landfall position needs to be evaluated beforehand, according to the forecasts and observation of historical cases. In the evaluation of landfalling typhoon track, the traditional method based on point-to-po...     

Agent-Based Simulation of Urban Residential Dynamics and Land Rent Change in a Gentrifying Area of Boston

Certain complex processes are most effectively modeled not on the macro-scale, but from the bottom-up, by simulating the decisions of individual entities, or agents. This study uses an agent-based modeling (ABM) approach to simulate residential dynamics in an area of Boston that has increasingly experienced gentrification in the past decades. The model is instantiated using basic empirical data and uses simple decision-making rules, differentiated into four classes, to simulate the process of residential dynamics. The model employs the consumption explanation of the cause of gentrification, which emphasizes the choices of individuals drawn to urban amenities, while testing the production explanation, which suggests that major investments from the public and private sphere attract and explain gentrification. Verification shows that the processes in the model work according to its construction, simulates complexity and emergent phenomena, and may be a valuable explanatory tool for understanding and learning about some processes underlying gentrification.     

The biogeography and community structure of kelp forest macroinvertebrates

Understanding species distributions and their community structure is increasingly important when taking an ecosystem‐based approach to conservation and management. However, knowledge of the distribution and community structure of species in mid‐range trophic levels (e.g. macroinvertebrates) is lacking in most marine ecosystems. Our study aimed to examine the spatial distribution and community‐level biogeographic patterns of common kelp forest–rocky reef macroinvertebrates in Southern California and to evaluate the effects of environmental gradients on these communities. Quantitative SCUBA surveys were used to estimate macroinvertebrate densities at 92 sites from 2008–2012. Non‐metric multidimensional scaling was used to evaluate spatial patterns of macroinvertebrate communities among Regions. We found that kelp forest–rocky reef macroinvertebrate communities are distinct among different island and mainland regions, and their community patterns exhibited a strong relationship with an environmental gradient (i.e. sea surface temperature) even after controlling for geographic distance between sites. High abundances of urchin species (Strongylocentrotus purpuratus and Strongylocentrotus franciscanus) were strong drivers of regional differences. Macroinvertebrate community patterns were driven by characteristic species that were typically more prevalent at warmer or colder sites. Our results provide the first quantitative analysis of macroinvertebrate community structure within the California kelp forest ecosystem. We also describe the distribution and abundance of 92 conspicuous kelp forest‐rocky reef macroinvertebrates among nine pre‐defined Regions. This study provides important preliminary information on these macroinvertebrate species that will be directly useful to inform management of invertebrate fisheries and spatial protection of marine resources.     

Progress and Challenges in Coupled Hydrodynamic-Ecological Estuarine Modeling

Numerical modeling has emerged over the last several decades as a widely accepted tool for investigations in environmental sciences. In estuarine research, hydrodynamic and ecological models have moved along parallel tracks with regard to complexity, refinement, computational power, and incorporation of uncertainty. Coupled hydrodynamic-ecological models have been used to assess ecosystem processes and interactions, simulate future scenarios, and evaluate remedial actions in response to eutrophication, habitat loss, and freshwater diversion. The need to couple hydrodynamic and ecological models to address research and management questions is clear because dynamic feedbacks between biotic and physical processes are critical interactions within ecosystems. In this review, we present historical and modern perspectives on estuarine hydrodynamic and ecological modeling, consider model limitations, and address aspects of model linkage, skill assessment, and complexity. We discuss the balance between spatial and temporal resolution and present examples using different spatiotemporal scales. Finally, we recommend future lines of inquiry, approaches to balance complexity and uncertainty, and model transparency and utility. It is idealistic to think we can pursue a “theory of everything” for estuarine models, but recent advances suggest that models for both scientific investigations and management applications will continue to improve in terms of realism, precision, and accuracy.     

High‐frequency precipitation and stream water quality time series from Plynlimon,Wales: an openly accessible data resource spanning the periodic table

This scientific briefing announces the availability of a new multi‐element high‐frequency water quality data set that is openly accessible to the research community. The data set comprises up to 2 years of 7‐hourly water quality data for two streams and one rainfall site in the Upper Severn catchment at Plynlimon in Mid‐Wales. The measurements cover 50 analytes ranging from H⁺ to U and spanning six orders of magnitude in concentration, including major, minor and trace elements as well as nutrients, and they complement decades of weekly measurements of the same analytes at the Upper Severn. Together, the weekly and 7‐hourly time series provide a unique data set for studying both long‐term trends and short‐term dynamics. The data show complex behaviour over a wide range of timescales, challenging our understanding of catchment processes and informing future modelling efforts. Copyright © 2013 John Wiley & Sons, Ltd.     

Modelling changes in suspended sediment from forest road surfaces in a coastal watershed of British Columbia

Erosion from logging road surfaces, cut slopes, banks, and ditches represents a chronic source of sediment input to streams that can degrade aquatic habitats. Road surface erosion is of particular concern because the magnitude of sediment generation when traffic levels are high can be large. Current models for predicting sediment production from roads require information on area‐specific sediment delivery, which is not often available. Here, we developed a model to quantify suspended sediment concentrations (SSC) generated by forest roads surfaces under different conditions of use and density. This model is designed for a typical medium‐size coastal watershed of British Columbia or the American Pacific Northwest, and was applied to the Chilliwack River watershed as a case study. The results illustrate that intensive use of forest roads combined with high road density can increase the number of extreme sedimentation events over a predetermined threshold. A comparison of the effects of road density and the level of road use suggests that the level of road use is more important than the road density for the generation of fine sediment from road surfaces. However, the model omits the impact of roads on mass movements in a watershed, which represent a major source of sediment in steep watersheds, so the effect of road density is likely more substantial than the model predicts. The model is an attempt to overcome field data limitations by using an empirical relation between SSC and traffic variables, and presents a starting point for more intensive field studies that could be used to validate it. Copyright © 2013 John Wiley & Sons, Ltd.