A review of wildland fire spread modelling, 1990-present 3: Mathematical analogues and simulation models

In recent years, advances in computational power and spatial data analysis (GIS, remote sensing, etc) have led to an increase in attempts to model the spread and behvaiour of wildland fires across the landscape. This series of review papers endeavours to critically and comprehensively review all types of surface fire spread models developed since 1990. This paper reviews models of a simulation or mathematical analogue nature. Most simulation models are implementations of existing empirical or quasi-empirical models and their primary function is to convert these generally one dimensional models to two dimensions and then propagate a fire perimeter across a modelled landscape. Mathematical analogue models are those that are based on some mathematical conceit (rather than a physical representation of fire spread) that coincidentally simulates the spread of fire. Other papers in the series review models of an physical or quasi-physical nature and empirical or quasi-empirical nature. Many models are extensions or refinements of models developed before 1990. Where this is the case, these models are also discussed but much less comprehensively.Comment: 20 pages + 9 pages references + 1 page figures. Submitted to the International Journal of Wildland Fir

A plot drainage network as a conceptual tool for the spatial representation of surface flow pathways in agricultural catchments

International audienceThe drainage network must take the farming systems and the landscape structure into consideration to describe flow pathways in the agricultural catchment. A new approach is proposed to build the drainage network which is based on the identification of the inlets and outlets for surface water flow on each farmers' field (or plot), estimating the relative areas contributing to the surface yield. The delineation of these areas and their links in terms of surface flow pathways provides us with a pattern of relationships between individual plots, i.e. going from each plot to the other plots over the entire catchment. In this approach, flow directions are firstly calculated in the usual way by taking account of slope direction. Plot outlets are defined from the DEM then linked together using a tree structure. If present, linear networks such as hedges modify both the flow directions and the location of plot outlets, hence modify this tree structure. In a final step, the plots are themselves linked together using a graph structure illustrated by an arrow diagram. This drainage network based on plot outlets is applied to a 15-km² catchment area represented by 38,300 pixels and 2,000 plots. This new drainage network takes into consideration 5,300 plot outlets, which greatly reduces the number of objects in comparison with a drainage network made up of pixels or DEM cells. This method leads to a simple and functional representation of surface flow pathways in an agricultural catchment. It allows us to identify the key plots controlling stream water pollution where converging flow pathways are coming from numerous or large-sized plots. Finally it produces a functional representation for decision support

Practical identifiability analysis of environmental models

Identifiability of a system model can be considered as the extent to which one can capture its parameter values from observational data and other prior knowledge of the system. Identifiability must be considered in context so that the objectives of the modelling must also be taken into account in its interpretation. A model may be identifiable for certain objective functions but not others; its identifiability may depend not just on the model structure but also on the level and type of noise, and may even not be identifiable when there is no noise on the observational data. Context also means that non-identifiability might not matter in some contexts, such as when representing pluralistic values among stakeholders, and may be very important in others, such as where it leads to intolerable uncertainties in model predictions. Uncertainty quantification of environmental systems is receiving increasing attention especially through the development of sophisticated methods, often statistically-based. This is partly driven by the desire of society and its decision makers to make more informed judgments as to how systems are better managed and associated resources efficiently allocated. Less attention seems to be given by modellers to understand the imperfections in their models and their implications. Practical methods of identifiability analysis can assist greatly here to assess if there is an identifiability problem so that one can proceed to decide if it matters, and if so how to go about modifying the model (transforming parameters, selecting specific data periods, changing model structure, using a more sophisticated objective function). A suite of relevant methods is available and the major useful ones are discussed here including sensitivity analysis, response surface methods, model emulation and the quantification of uncertainty. The paper also addresses various perspectives and concepts that warrant further development and use

Integrating an Agent-Based Model into a Web-Enabled Annual Brome Land Management System

The natural fire cycle in the Great Basin area of Nevada has shortened from every 50 to 60 years to 3 to 5 years, putting many natural ecosystems and occupied lands in danger. The spreading phenomenon of the invasive annual brome will be investigated to quantify this fire risk. It is renowned for its invasive nature, flammability, and the detrimental effects it has on native annual and perennial grasses. Based on vegetation classifications and dispersal characteristics, the rules for an agent-based model will be used to simulate the future extents. Agent Analyst software in conjunction with ArcGIS will integrate simulation results into a web-enabled decision support system for land manager

Archaeological 3D GIS

Archaeological 3D GIS provides archaeologists with a guide to explore and understand the unprecedented opportunities for collecting, visualising, and analysing archaeological datasets in three dimensions. With platforms allowing archaeologists to link, query, and analyse in a virtual, georeferenced space information collected by different specialists, the book highlights how it is possible to re-think aspects of theory and practice which relate to GIS. It explores which questions can be addressed in such a new environment and how they are going to impact the way we interpret the past. By using material from several international case studies such as Pompeii, Çatalhöyük, as well as prehistoric and protohistoric sites in Southern Scandinavia, this book discusses the use of the third dimension in support of archaeological practice. This book will be essential for researchers and scholars who focus on archaeology and spatial analysis, and is designed and structured to serve as a textbook for GIS and digital archaeology courses

A Map-algebra-inspired Approach for Interacting With Wireless Sensor Networks, Cyber-physical Systems or Internet of Things

The typical approach for consuming data from wireless sensor networks (WSN) and Internet of Things (IoT) has been to send data back to central servers for processing and analysis. This thesis develops an alternative strategy for processing and acting on data directly in the environment referred to as Active embedded Map Algebra (AeMA). Active refers to the near real time production of data, and embedded refers to the architecture of distributed embedded sensor nodes. Network macroprogramming, a style of programming adopted for wireless sensor networks and IoT, addresses the challenges of coordinating the behavior of multiple connected devices through a high-level programming model. Several macroprogramming models have been proposed, but none to date has adopted a comprehensive spatial model. This thesis takes the unique approach of adapting the well-known Map Algebra model from Geographic Information Science to extend the functionality of WSN/IoT and the opportunities for user interaction with WSN/IoT. As an inherently spatial model, the Map Algebra-inspired metaphor supports the types of computation desired from a network of geographically dispersed WSN nodes. The AeMA data model aligns with the conceptual model of GIS layers and specific layer operations from Map Algebra. A declarative query and network tasking language, based on Map Algebra operations, provides the basis for operations and interactions. The model adds functionality to calculate and store time series and specific temporal summary-type composite objects as an extension to traditional Map Algebra. The AeMA encodes Map Algebra-inspired operations into an extensible Virtual Machine Runtime system, called MARS (Map Algebra Runtime System) that supports Map Algebra in an efficient and extensible way. Map algebra-like operations are performed in a distributed manner. Data do not leave the network but are analyzed and consumed in place. As a consequence, collected information is available in-situ to drive local actions. The conceptual model and tasking language are designed to direct nodes as active entities, able to perform some actions on their environment. This Map Algebra inspired network macroprogramming model has many potential applications for spatially deployed WSN/IoT networks. In particular the thesis notes its utility for precision agriculture applications

Application of Geographic Information Systems

The importance of Geographic Information Systems (GIS) can hardly be overemphasized in today’s academic and professional arena. More professionals and academics have been using GIS than ever – urban & regional planners, civil engineers, geographers, spatial economists, sociologists, environmental scientists, criminal justice professionals, political scientists, and alike. As such, it is extremely important to understand the theories and applications of GIS in our teaching, professional work, and research. “The Application of Geographic Information Systems” presents research findings that explain GIS’s applications in different subfields of social sciences. With several case studies conducted in different parts of the world, the book blends together the theories of GIS and their practical implementations in different conditions. It deals with GIS’s application in the broad spectrum of geospatial analysis and modeling, water resources analysis, land use analysis, infrastructure network analysis like transportation and water distribution network, and such. The book is expected to be a useful source of knowledge to the users of GIS who envision its applications in their teaching and research. This easy-to-understand book is surely not the end in itself but a little contribution to toward our understanding of the rich and wonderful subject of GIS

Vector Zonal Operations for Spatiotemporal Analysis

Cartographic modeling (also known as map algebra) is a powerful set of operations for manipulating raster geographic data. Zonal operations are one type of cartographic modeling operations where the spatial scopes of the operations are defines by zones. The conventional zonal operations only work with raster data and lack the capability of performing spatiotemporal analysis. This research developed zonal operations for spatiotemporal analysis where spatiotemporal zones can be defined in the vector data model. The zonal operations were used to extract watershed hourly or daily precipitation for use in non-point source pollution models and to explore the effects of antecedent precipitation on water quality samples. The case studies demonstrated the usefulness of the operations. A software tool, NexTool was also developed to process and build NEXRDA precipitation database, which was used in the case studies