…from the Anchorage Daily News…
From 2005 to 2007, 11 grizzly bears in Anchorage were captured and fitted with radio collars that transmitted their locations. Follow their travels through the town.
Day: January 4, 2010
2010 Advanced Spatial Analysis Workshop Schedule from PRI and CSISS
The Population Research Institute (PRI) at Penn State and the Center for Spatially Integrated Social Science (CSISS) at UC Santa Barbara are pleased to announce the offering of two summer workshops in 2010 under the Advanced Spatial Analysis Training for Population Scientists program (funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD). This year both workshops will take place in July 2010 on the UC Santa Barbara campus with Don Janelle serving as the local coordinator. These workshops have a participation cap and are highly competitive. Anyone interested in these workshops must complete an application form (to be posted on‐line at the project website in mid‐January 2010). Closing dates for receipt of an application will be March 31, 2010 and successful applicants will receive notification of invitation to participate by mid‐April.
- Geographically Weighted Regression – July 12‐16, 2010 (arrival day July 11th)
The instructors include A. Stewart Fotheringham, Martin Charlton and Chris Brunsdon. A similar workshop was held at Penn State in 2008 and the format for the 2010 workshop will likely be similar. See http://www.csiss.org/GISPopSci/workshops/2008/PSU/agenda.php
- Spatial Pattern Analysis ‐ July 19‐23, 2010 (arrival day July 18th)
The instructors include Art Getis, John Weeks and Jared Aldstadt. A similar workshop was held in 2008 at UCSB and the format for the 2010 workshops will likely be similar. See http://www.csiss.org/GISPopSci/workshops/2008/UCSB/agenda.php
Please consult the training program website for updates: http://www.csiss.org/GISPopSci/
Doug Richardson, Executive Director of the Association of American Geographers, on GIScience and Climate Change
…from the Winter 2009/2010 issue of ArcNews…
“Geographers and GIScientists have long played key roles in climate change research, and the tools and methods of geography—including GIS—will be crucial to understanding, limiting, and adapting to climate change in the decades ahead.
“After years of delay and denial, responsible climate change research and responsive policy agendas are now assuming center stage in President Barack Obama’s administration. Nearly all federal agencies now have legacy or newly mandated and funded research programs that actively seek to identify causes and impacts of global climate change and policies for mitigating or adapting to these impacts. Geography and GIScience, with long experience in the integration of the physical and social sciences, offer a well-placed bridge that can bring together the disparate natural and human system elements of climate change research and policy.”
Contemporary Roles for Spatial Analysis in Archaeology: Seminar Series at University College London
The UCL Institute of Archaeology Seminar Series (January–March 2010)
31-34 Gordon Square, London WC1H 0PY
Mondays 4pm, Room 612 (followed by a wine reception)
Schedule
- 11 January 2010 – Benjamin Ducke (Oxford Archaeology)
‘Science without software no longer. Archaeological data analysis and the Open Source paradigm’
- 18 January 2010 – Chris Green (University of Leicester)
‘Temporal GIS and archaeology’
- 25 January 2010 – Tony Wilkinson (Durham University)
‘From household to region: incorporating agency into the interpretation of regional settlement’
- 1 February 2010 – Tim Williams (University College London)
‘Earth viewers and GIS in archaeological resource management: access and accessibility’
- 08 February 2010 – Luke Premo (Max Planck Institute for Evolutionary Anthropology)
‘A spatially explicit model of Early Stone Age archaeological landscapes’
- 15 February 2010 (Reading Week – no seminar)
- 22 February 2010 – Frederic Fol Leymarie (Goldsmiths College)
‘Advances in 3D procedural modelling with applications to archaeology’
- 01 March 2010 – Michael Barton (Arizona State University)
‘Stories of the past or science of the future? Archaeology and computational social science’
- 08 March 2010 – Irmela Herzog (Archaeological Heritage Management of the Rhineland)
‘Patterns of movement, least cost paths and our understanding of the archaeological record’
- 15 March 2010 – Kate Devlin (Goldsmiths College)
‘Illuminating virtual reconstructions of past environments’
- 22 March 2010 – Mark Lake (University College London)
‘Rewind and fast‐forward: how archaeological GIS analyses recapitulate general theory’
On Three-dimensional Visualization of Geospatial Information: Graphics Based or Imagery Based?
Annals of GIS, Volume 15, Issue 2 December 2009 , pages 75 – 84
Li Deren; Wang Mi; Hu Qingwu; Hu Fen
“The three-dimensional (3D) visualization of geospatial information constitutes a fundamental property of the geo-information services nowadays, along with the requirements of popularity, openness and capabilities of target measuring and knowledge mining. Accordingly, in this article, the two major technical routines now applied to 3D visualization of geospatial information, that is the graphics-based approaches and the imagery-based approaches, are both described and discussed. After a comparative analysis of both advantages and disadvantages of the two manifestation modes, an optimized integrative strategy for 3D visualization of geospatial information is proposed finally.”
University of New Mexico Graduate Research Opportunity in Historical Geography
The Department of Geography at the University of New Mexico is seeking to hire a Graduate Research Assistant (GRA) in Historical Geography, starting Fall 2010. GRAs are expected to be enrolled full-time in the MS in Geography program. Some of the specific research projects the GRA will be working on include:
- Historical transitions in New Mexico’s water resource management funded by the National Science Foundation. This research examines the ways local New Mexican communities responded to federal and territorial/state initiatives for centralized water management in the early 20th century. Data sources include district court cases, newspaper publications, and archival materials.
- Development of hydrological science in the arid West funded by the National Science Foundation. This research examines the rhetorical, cultural, and structural development of hydrology as a “science” for irrigation in the late-nineteenth-century American West, focusing on the ways water engineers and water administrators represented their work. Data sources include government documents, newspaper publications, and personal papers of water engineers.
- Cartography and expertise in water management funded by the National Science Foundation. This research examines the role of cartography in early 20th-century water management in New Mexico. Data sources include government documents, district court cases, and personal papers of water engineers.
Qualified applicants should have an undergraduate degree in Geography, History, or related field, with strong research and writing skills. Interest in natural resource management and experience with archival materials is also desirable. The GRA position consists of a competitive monthly stipend, including tuition waiver and benefits. Those interested in the position should apply to the MS program in Geography and indicate that they would like to be considered for the GRA position in Historical Geography. Application deadline to be considered for Fall 2010 is February 1, 2010.
Applications materials can be accessed at www.unm.edu/grad/admissions/admissions.html.
Details on the Department of Geography and the MS program in Geography can be found at http://geography.unm.edu .
More details on these specific research projects can also be found at
www.unm.edu/~mdlane.
For more information, contact:
Maria Lane, Assistant Professor
Department of Geography
Bandelier West Room 111, MSC01 1110
1 University of New Mexico
Albuquerque, NM 87131
E-mail: mdlane@unm.edu
Tel: (505) 277-1752
Using GIS to Assess Climate Change Impacts on the Rio Grande and its Riparian Forest
American Water Resources Association 2010 Summer Specialty Conference: GIS & Water Resources VI, 29 – 31 March 2010, Orlando, Florida
Session 4: Hydrologic Modeling I. Monday, 29 March, 1:30 p.m. – 3:00 p.m.
Julie Coonrod, Department of Civil Engineering, Albuquerque, NM (co-authors: Kelly Isaacson, Venkatesh Merwade)
“River restoration projects in the vicinity of Albuquerque, New Mexico are often focused on the riparian forest. Exotic species are removed, while native cottonwood trees are planted. The cottonwood trees are ‘pole planted’ such that their roots tap into the groundwater table adjacent to the river. Such projects are located anywhere current cottonwood trees exist and not necessarily where groundwater depths have been estimated to determine likelihood of species survival. This work is aimed at utilizing Geographic Information Systems (GIS) along with the Hydrologic Engineering Center River Analysis System (RAS) to determine depth to groundwater as a function of river flow rate. The RAS model utilizes a terrain model developed by various data sets including point data from Light Detection and Ranging, surveyed cross-section points, and aerial photographs. The RAS model is calibrated with readily available flow gage data. In-channel water surfaces from RAS are combined with well data in GIS to create groundwater surfaces. The groundwater surfaces are thus created as a function of flow rate. Doing so allows for simulation of groundwater surfaces for average years, dry years, and wet years. Furthermore, climate change scenarios (that employed GIS methods) can be used to estimate changes in stream flow. These changes show the groundwater surface can drop below the depth that the cottonwood trees can reach. By subtracting the groundwater surface from the digital terrain, the depth to groundwater is determined. Locations where riparian vegetation will be most stressed can be identified.”
Genocide and GIScience: Integrating Personal Narratives and Geographic Information Science to Study Human Rights
The Professional Geographer, Volume 61, Issue 4 November 2009 , pages 508 – 526
Marguerite Madden; Amy Ross
“This project combines qualitative data of personal narratives with geographic information science (GIScience) technologies to explore the potential for critical cartography in the study of mass atrocity. The case study used is northern Uganda, where millions have been affected by physical violence and hardship, displacement, and fear. Web-based virtual globes as a ready source of imagery for remote areas and derived spatial data imported to geographic information systems (GIS) provide quantified data that complement testimonials and other qualitative data from the field. Cartographic functions, geovisualization, and spatial analyses available in GIS are used to extract information from high-resolution remote sensing images documenting internally displaced persons (IDP) camps and quantifying evidence of crimes against humanity. These techniques explore spatial relationships and communicate results on the extent and impact of the atrocities in northern Uganda.”
PhD Scholarship, Institute of Geomatics and Analysis of Risk (IGAR), University of Lausanne
IGAR opens a position in the field of application of machine learning algorithms (neural networks of different architectures, support vector machines, etc.) and geostatistics for geo/environmental sciences. The main tasks concern the development, adaptation, and programming of data mining (pattern recognition) models and tools. In particular, topics to be studied include modeling of data clustering, novelty detection, feature selection, manifold learning, risk mapping, and spatio-temporal simulations. In addition to the PhD the candidate is expected to assist in teaching (French, English) and other projects at the institute.
Requires an MS degree in one of the following disciplines: statistics, machine learning, computer science, physics, geosciences, applied mathematics. Candidates should have a sound background in spatio-temporal data analysis using machine learning and geostatistical approaches. Knowledge of scientific programming languages as Matlab, C, or R is important.
- More information [PDF]
GIS, Multi-criteria and Multi-factor Spatial Analysis for the Probability Assessment of the Existence of Illegal Landfills
International Journal of Geographical Information Science, Volume 23, Issue 10 October 2009 , pages 1233 – 1244
Giancarlo Biotto; Sonia Silvestri; Lucia Gobbo; Elisa Furlan; Sonia Valenti; Roberto Rosselli.
“This work deals with the identification of potentially contaminated areas using remote sensing, geographic information systems (GIS) and multi-criteria spatial analysis. The identification of unknown illegal landfills is a crucial environmental problem in all developed and developing countries, where a large number of illegal waste deposits exist as a result of fast, and relatively unregulated, industrial growth over the past century. The criteria used to perform the spatial analysis are here selected by considering the characteristics which are ‘desirable’ for an illegal waste disposal site, chiefly related to the existence of roads for easy access and to a low population density which facilitates unnoticed dumping of illegal waste materials. A large dataset describing known legal and illegal landfills and the context of their location (population, road network, etc.) was used to perform a spatial statistical analysis to select factors and criteria allowing for the identification of the known waste deposits. The final result is a map describing the likelihood of an illegal waste deposit to be located at any arbitrary location. Such a probability map is then used together with remote sensing techniques to narrow down the set of possibly contaminated sites (Silvestri and Omri, 2008), which are candidates for further analyses and field investigations. The importance of the integration of GIS and remote sensing is highlighted and represents a key instrument for environmental management and for the spatially-distributed characterization of possible uncontrolled landfill sites.”
GIS and Science 