“At the request of the U.S. Geological Survey, the National Research Council is conducting a study that will: (1) identify existing knowledge and document lessons learned during previous efforts to develop Spatial Data Infrastructures (SDI) and their support of scientific endeavors; (2) develop a vision for optimizing an SDI to organize, integrate, access, and use scientific data; and (3) create a roadmap to guide the USGS in accomplishing the vision within the scope of the USGS Science Strategy. For the committee’s full statement of task, click here.
“Because the committee cannot hear from all the individuals and organizations that have valuable experience and ideas on this topic during its few scheduled meetings, the committee seeks your help in the form of written contributions on the following set of questions.”
Based on the last five years working with spatial data infrastructures:
1. What has worked well?
2. What has not worked?
3. What are the major challenges (technical, organizational, cultural, policy, financial)?
4. What would you do differently?
5. In what domain(s) are your data (e.g. biological, hydrologic, cultural, etc.)?
6. What is your vision for an SDI to meet the needs of the USGS Science Strategy?
“Comments received by December 6, 2009 will be considered at the committee’s next meeting (December 10-11, 2009). However, the committee welcomes all input through February 2010. The final report is scheduled for public release in January 2011. Please note that any written comments submitted to the committee (whether by mail, e-mail, fax, or this comment form) will be included in the study’s public access file.”
Proceedings of the Third International Workshop on Knowledge Discovery from Sensor Data, Paris, France, 2009
Vladan Radosavljevic, Slobodan Vucetic, and Zoran Obradovic
“In many remote sensing applications it is important to use multiple sensors to be able to understand the major spatio-temporal distribution patterns of an observed phenomenon. A particular remote sensing application addressed in this study is estimation of an important property of atmosphere, called Aerosol Optical Depth (AOD). Remote sensing data for AOD estimation are collected from ground and satellite-based sensors. Satellite-based measurements can be used as attributes for estimation of AOD and in this way could lead to better understanding of spatio-temporal aerosol patterns on a global scale. Ground-based AOD estimation is more accurate and is traditionally used as ground-truth information in validation of satellite-based AOD estimations. In contrast to this traditional role of ground-based sensors, a data mining approach allows more active use of ground-based measurements as labels in supervised learning of a regression model for AOD estimation from satellite measurements. Considering the high operational costs of ground-based sensors, we are studying a budget-cut scenario that requires a reduction in a number of ground-based sensors. To minimize loss of information, the objective is to retain sensors that are the most useful as a source of labeled data. The proposed goodness criterion for the selection is how close the accuracy of a regression model built on data from a reduced sensor set is to the accuracy of a model built of the entire set of sensors. We developed an iterative method that removes sensors one by one from locations where AOD can be predicted most accurately using training data from the remaining sites. Extensive experiments on two years of globally distributed AERONET ground-based sensor data provide strong evidence that sensors selected using the proposed algorithm are more informative than the competing approaches that select sensors at random or that select sensors based on spatial diversity.”
…from The Cartographic Journal …
Kirsi Virrantaus, David Fairbairn, and Menno-Jan Kraak
“Maps and geographic information (GI) have special power through their ability to connect and integrate data sets by the inherent geographical location, and present the information contents in a user-friendly and understandable visual and tactual way. Such ability has long been recognized as an intrinsic property of the map artefact, as well as contemporary geodatabases. The power of maps and geographic data handling has been recently recognized in many real world applications and strategic decision making situations related to current topics like crisis management, early warning systems, efforts for supporting sustainability and decreasing global poverty.
“The international cartographic association (ICA), as a globally well represented and internationally visible organization, has a special position and role as a promoter of the development of cartography and GI science. Research and development in ICA aim in general to create theory and methods for cartography and GI handling. By applying theories and methods in various fields, new tools can be created for cartographic and GI practice. Such topics are
addressed at the main work-forums of ICA, its Commissions. These organizations are formally established by vote at the quadrennial ICA General Assemblies, although interim Working Groups can also be established between General Assemblies by the ICA Executive Committee (EC) to address specific short-term issues.”
Environmental Modelling & Software, Volume 24, Issue 8, August 2009, Pages 959-968
J.N. Callow and K.R.J. Smettem
“System coupling and landscape connectivity control the flow of water and sediment through landscapes. Although coupling is well known to control long-term landscape development and shorter-term sensitivity to disturbance, the anthropogenic influences on coupling are seldom considered in hydrologic investigations. In particular, the building of small-scale water diversion (earth banks) and collection (farm dams) infrastructure on hillslopes in dryland agricultural areas may significantly alter hillslope–channel coupling. Twelve sub-catchment basins in a dryland agricultural region were investigated under their natural (ignoring infrastructure) and modified (including infrastructure) conditions to investigate the influence of water collection infrastructure on hydrologic connectivity, and whether manual modification of a Digital Elevation Model (DEM) could account for the impact of these factors in hydrologic simulation of hydrologic and geomorphic processes.
“Dam numbers and density have both increased over the period of available aerial photography (1965–1999), resulting in an average 39.5% reduction (range 4.3–86.7%) in the area retaining hydrologic connectivity with the basin outlet. Analysis of basins dominated by either banks or dams, and with combinations of both was performed using the Cumulative Area Distribution (CAD), Hypsometric Curve (HC), Simplified Width Function (SWF) and Instantaneous Unit Hydrograph (IUH). The geomorphic descriptors (CAD and HC) showed little change in basin structure as a result of farm dam and bank construction, but hydrologic descriptors (SWF and IUH) indicate that hillslope processes are significantly altered by farm dams and banks. Because runoff models are sensitive to catchment area, incorporating hillslope water capture and diversion infrastructure into the base data sets may offer a solution to improved parameterisation of spatial models of hydrology, particularly in dryland agricultural regions.”
The Professional Geographer, Volume 62, Issue 1 February 2010 , pages 46 – 65
Tonny J. Oyana; Florence M. Margai
“Lead poisoning remains a major environmental health threat and a persistent source of health disparities in the United States. In this retrospective study, statistical and geospatial approaches were used to evaluate age- and gender-specific differences in childhood lead prevalence across Chicago, assess the spatiotemporal dynamics of the disease, and identify the socioeconomic and racial composition of high-risk communities. Elevated blood lead levels (≥ 10 μ g/dL of lead) decreased significantly during the study period but disparities persisted across neighborhoods. A significant association was observed between high-risk neighborhoods and housing age, low income, and minority populations. These findings provide insights into the complex geographies of lead exposure and could serve as a basis for developing more targeted health intervention programs. ”