New book from the Committee on Challenges and Opportunities in Earth Surface Processes, National Research Council:
“During geologic spans of time, Earth’s shifting tectonic plates, atmosphere, freezing water, thawing ice, flowing rivers, and evolving life have shaped Earth’s surface features. The resulting hills, mountains, valleys, and plains shelter ecosystems that interact with all life and provide a record of Earth surface processes that extend back through Earth’s history. Despite rapidly growing scientific knowledge of Earth surface interactions, and the increasing availability of new monitoring technologies, there is still little understanding of how these processes generate and degrade landscapes.
“Landscapes on the Edge identifies nine grand challenges in this emerging field of study and proposes four high-priority research initiatives. The book poses questions about how our planet’s past can tell us about its future, how landscapes record climate and tectonics, and how Earth surface science can contribute to developing a sustainable living surface for future generations.”
“This is an EPSRC-funded research position working on the Explaining, Modelling & Forecasting Global Dynamics (ENFOLD-ing) project. The main purpose of this post is to initiate, develop, design and be responsible for the delivery of a programme of high quality quantitative research into the relevant statistical, geographical and theoretical aspects related to migration analysis, as well as related issues to the overall aims of the ENFOLD project; this includes working in and contributing to the wider ENFOLD team effort.
“Funding is available for two years in the first instance.
“The ideal candidate will have extensive programming experience (in C#, C++, Java, Python etc) , expertise in designing, constructing and analysing large databases and a PhD in any of the following:
- a quantitative speciality within a social science discipline such as; statistics, geography, economics, sociology, epidemiology/ public health, GIS, spatial analysis
- a science discipline with experience in social science applications, such as computer science, maths, physics, medicine, and any other relevant disciplines.”
Forest Ecology and Management, 257 (9), p.1910-1919, Apr 2009
Teich, M. / Bebi, P.
“The protection of people, buildings and infrastructure against natural hazards is one of the key functions of mountain forests. Since the protective function strongly depends on small-scale local conditions such as terrain and stand characteristics, spatially explicit evaluation methods are necessary to provide information required for an effective and cost-efficient forest management. Risk analyses are recognized as the best method for estimating the danger from various natural hazards. Currently, however, risk-based strategies are rarely addressed in the management of protection forest. We present and discuss a risk-based approach to evaluate the protective effect of mountain forests in a spatially explicit manner to demonstrate the advantages of future risk-based protection forest management. We illustrate the approach by performing a GIS-based risk analysis in the case study area ‘Bannwald of Andermatt’ (Switzerland) for a 300-year snow avalanche event. Classifying forest structures based on aerial photographs allowed developing different forest cover scenarios and modeling potential avalanche release areas within the forest. Potential avalanche release areas above the forest and the avalanche run-out distances under five different scenarios of forest cover were calculated by using a two-dimensional avalanche simulation model. We calculated the annual collective risk for each scenario and compared the change in risk to reveal the spatial distribution of the protective effect of the forest. Resulting risks differed strongly between forest cover change scenarios. An enlargement of an existing wind-disturbed area within lower parts of the slope resulted only in a slight increase of risk. In contrast, the effect of an unforested area in the upper parts of the observed forest more than doubled the risk. These results show how a risk-based approach can help to quantify and illustrate the impact of differences in forest cover on the protective effect of mountain forests. It is a promising approach to determine the economic value of protection forests and thus provide quantitative and qualitative information for cost-efficient forest maintenance planning. With regard to the achievements of research to date, the presented approach may serve as a valuable method to support decision-making in a future protection forest management.”
Environmental Research Letters, Volume 5, Number 1, 2010
Olga VWilhelmi and Mary H Hayden
“Climate change is predicted to increase the intensity and negative impacts of urban heat events, prompting the need to develop preparedness and adaptation strategies that reduce societal vulnerability to extreme heat. Analysis of societal vulnerability to extreme heat events requires an interdisciplinary approach that includes information about weather and climate, the natural and built environment, social processes and characteristics, interactions with stakeholders, and an assessment of community vulnerability at a local level. In this letter, we explore the relationships between people and places, in the context of urban heat stress, and present a new research framework for a multi-faceted, top-down and bottom-up analysis of local-level vulnerability to extreme heat. This framework aims to better represent societal vulnerability through the integration of quantitative and qualitative data that go beyond aggregate demographic information. We discuss how different elements of the framework help to focus attention and resources on more targeted health interventions, heat hazard mitigation and climate adaptation strategies.”
International Journal of Geographical Information Science, Volume 24, Issue 4 April 2010 , pages 607 – 621
Lin Hui; Zhu Jun; Gong Jianhua; Xu Bingli; Qi Hua
“To improve the efficiency of planning and designing silt dam systems, this article employs theories and technologies of collaboration and distributed virtual geographic environments (VGEs) to construct a collaborative virtual geographic environment (CVGE) system. The CVGE system provides geographically distributed users with a shared virtual space and a collaborative platform to implement collaborative planning. Many difficulties have been found in integrating data resources and model procedures for the planning of silt dam systems because of their diversity in heterogeneous environments. Unlike most of the current distributed system applications, the proposed CVGE system not only supports multi-platform and multi-program-language interoperability in the dynamically changing network environment, but also shares programs, data and software in the collaborative environment. Based on creating a shared 3D space by virtual reality technology, agent and grid technologies were tightly coupled to develop the CVGE system. A grid-based multi-agent system service framework was designed to implement this new paradigm for the CVGE system, which efficiently integrates and shares geographically distributed resources as well as having the ability to build modelling procedures on different platforms. At the same time, mobile agent computing services were implemented to reduce the network load, process parallel tasks, enhance communication efficiency and adapt dynamically to the changing network environment. Using Java, JMF (Java Media Framework API), Globus Toolkits (GT) core, Voyager, C++, and the OpenGL development package, a prototype system was developed to support silt dam systems planning in the case study area, the Jiu-Yuan-Gou watershed of the Loess Plateau, China. Compared with the traditional workflow, the CVGE system can reduce the workload by between one third and a half.”
Environmental Modelling and Software, 25 (4), p.539-553, Apr 2010
Wang, J. / Chen, J. / Ju, W. / Li, M.
“Land use, land use change and forestry (LULUCF) can play a positive role in mitigating global warming by sequestering carbon from the atmosphere into vegetation and soils. Local entities (e.g. local government, community, stockholders) have been making great efforts in enhancing carbon sequestration (CS) of local forests for mitigating global climate change and participating in international carbon-trade promoted by the Kyoto Protocol. Approaches and tools are needed to assess the enhancement of CS through land use changes and proper policy decisions. This paper presents an integrated assessment framework and a spatial decision support system (IA-SDSS) as a tool to support land-use planning and local forestry development with consideration of CS. The IA-SDSS integrates two process-based carbon models, a spatial decision (EMDS) module, a spatial cost-benefit analysis (CBA) module, and the analytic hierarchy process (AHP) module. It can provide spatially explicit CS information as well as CS-induced economic benefits under various scenarios of the carbon credit market. A case study conducted in Liping County, Guizhou Province, China demonstrated that the IA-SDSS developed in this study is applicable in supporting decision-making on ‘where’ and ‘how’ to adopt forestry land use options in favor of CS.”
Cartography and Geographic Information Science, Volume 37, Number 1, January 2010 , pp. 45-56(12)
Curtis, Andrew; Duval-Diop, Dominique; Novak, Jenny
“The devastation caused by Hurricane Katrina is still being felt by many neighborhoods of New Orleans and along the Gulf Coast. As these communities struggle to recover, academia has been forced to acknowledge that there is little known or theorized about the spatial processes of recovery, especially at the fine scale. As a result this paper will investigate how post-disaster landscape characteristics can be extracted from spatial video data for neighborhoods of New Orleans. These will be turned into a statistical surface using analytical approaches more commonly applied in spatial epidemiology. Spatial patterns of abandonment and recovery will be identified that can be used as a basis for a next round of causative investigation. The paper finds that by using the spatial overlap of four different analyses involving two different data input locations and two filter sizes, the Holy Cross neighborhood of New Orleans does indeed reveal areas with higher rates of recovery, and continuing abandonment. However, even within these areas, spatial heterogeneity can be found. This paper uses Google Street View to mirror spatial video data collected in participatory collaborations with New Orleans community groups so that readers can replicate the methods presented here for other neighborhoods of New Orleans.”