Photos: Space Shuttle Endeavour Flies Over Jet Propulsion Lab

I was shocked at how many people descended on JPL today to watch the Space Shuttle Endeavor fly over…

We staked out a good spot just east of JPL, on a bluff overlooking the parking lot.  Perfect spot really.

Waiting for the flyover, we didn’t expect to be able to first see it way off in the distance, flying over of Griffith Park and the Hollywood sign!

About 5-10 minutes later, it came back, south of JPL, and then disappeared to the east as it did a u-turn over downtown.

A few minutes later, it popped up right over our heads and buzzed JPL!

It then banked around to fly southeast down to Orange County.

Nice shot with the two chase planes.

Continuing to bank, almost leveled out.

Next stop: Disneyland…

Last view before it disappeared behind the trees.

Heading back to the car…it took us 25 minutes to drive the first block!  But it was well worth it.

How Influential is Geographic Information Science?

GIScience 2012, Columbus, Ohio, 18-21 September 2012

Thomas Blaschke and Clemens Eisank

“GIScientists find themselves sometimes in a somewhat defending role when to position Geographic Information Science. Kemp et al. (2012) state that researchers in this field often find it difficult to argue in established disciplines like Geography, Statistics, or Computer Science. Kemp et al. diagnose reasons for this to include problems of a narrow focus on indices like Thomson-Reuters’ for use in assessment metrics, the relative importance of conferences versus journals, or different criteria used in geography and computer science (as well as other fields, such as statistics or economics), or the highly variable meaning of “strong impact factors” across fields, and so on (Kemp et al. 2012: 268).

“Reitsma (2012) argued that GIScience may be considered as a science if using similar criteria as Stamos (2007), namely simplicity, predictive accuracy, coherence with known facts and testability and pleads not for just a yes or no classification, but for some kind of degree classification. What distinguishes GIScience from man other sciences is the fact that GIScientists study the representation of the world and not the world in concrete. For this knowledge and principles from other disciplines are needed and used (Reitsma 2012:9). Following this line of arguments one may reason that GIScience exists in symbiosis with other disciplines and can hardly exist without them. This could be one reason why it is still in the process of self-justification. Nevertheless, in this short article, we will avoid to discuss whether or not GIScience is a science or a discipline and if it is scientific at all. Rather, we try to analyse in an unbiased and neutral way how well GIScience is reflected in the literate. We are well aware of the limitations of this approach. We of course reduce a positive hit as a “citations” if a search term is found in the title or keywords of a particular database. This will produce quite a high number of errors of omission and – less often – errors of commission: we – as many other studies which analyse publications and the number of their citations in other publications – hypothesize that an entry is a confirmation of its contents.”

Spatial Analysis of Conservation Priorities Based on Ecosystem Services in the Atlantic Forest Region of Misiones, Argentina

Forests 2012, 3(3)

Andrea E. Izquierdo and Matthew L. Clark

“Understanding the spatial pattern of ecosystem services is important for effective environmental policy and decision-making. In this study, we use a geospatial decision-support tool (Marxan) to identify conservation priorities for habitat and a suite of ecosystem services (storage carbon, soil retention and water yield) in the Upper Paraná Atlantic Forest from Misiones, Argentina—an area of global conservation priority. Using these results, we then evaluate the efficiency of existing protected areas in conserving both habitat and ecosystem services.

Maps of the analyzed ecosystem services.

Maps of the analyzed ecosystem services.

“Selected areas for conserving habitat had an overlap of carbon and soil ecosystem services. Yet, selected areas for water yield did not have this overlap. Furthermore, selected areas with relatively high overlap of ecosystem services tended to be inside protected areas; however, other important areas for ecosystem services (i.e., central highlands) do not have legal protection, revealing the importance of enforcing existing environmental regulations in these areas.”

Free Book from URISA: Foundations of Urban and Regional Information Systems and Geographic Information Systems and Science

Foundations of Urban and Regional Information Systems and Geographic Information Systems and ScienceURISA is pleased to announce the publication of Foundations of Urban and Regional Information Systems and Geographic Information Systems and Science, a 300-page book assembled to celebrate URISA’s 50th anniversary conference. Sponsored by URISA past presidents, the commemorative book discusses some of the research, education, training, and applications foundations that URISA and its members have contributed to urban and regional information systems and geographic information systems and science during the past five decades. The dozens of contributors to this publication, bring their experiences from governments at all levels, private sector firms, research institutes, and universities, represent the ‘Who’s Who’ of influencers in the field.

Dr. Barry Wellar, GISP (President, Wellar Consulting Inc., retired Professor, University of Ottawa, URISA President 1977-1978 and member of URISA’s GIS Hall of Fame) served as publication Editor and coordinated the effort. “The sum of the matter as I see it, is that URISA has an amazingly rich history, and the right people were in the right place at the right time to prepare a book which delves into that record of achievement, and does considerable justice to the many individuals, agencies, ideas, initiatives, etc., that have made URISA the leading international organization in the field of urban and regional information systems and geographic information systems and science. URISA has a long and rich history of producing substantive documents, and I am optimistic that Foundations will be recognized as an important legacy of URISA’s 50th anniversary conference.”

Each of the 23 chapters in Foundations of Urban and Regional Information Systems and Geographic Information Systems and Science contains insights, ideas, suggestions, lessons learned, lessons to be learned, and recommendations regarding information system education, research, training, and application.

The book is currently available, for free, as a downloadable file on URISA’s website, www.urisa.org/foundations, and printed copies, supported with funding from Esri, will be available for purchase at GIS-Pro 2012: URISA’s 50th Annual Conference for GIS Professionals (September 30-October 4, 2012 in Portland, Oregon). Many of the contributing authors will be in attendance and it is anticipated that a book signing event will take place during the conference. Further, the publication will be celebrated in a conference plenary session on Thursday morning, October 4. Visit www.urisa.org/gispro2012 for details about GIS-Pro 2012.

[Source: URISA press release]

A Density Based Accessibility Measure for Mobile Objects

GIScience 2012, Columbus, Ohio, 18-21 September 2012

M.W. Horner and J. A. Downs

“Mobile object analysis continues to be well-studied in GIScience (Hornsby and Egenhofer 2002; Laube et al. 2005; Neutens et al. 2011). Time geography remains the key theoretical framework for understanding mobile objects’ movement possibilities (Miller 2005). Within time geography, recent efforts have sought to enhance its ‘probabilistic’ potential through exploring questions of data uncertainty, spatial representation, and limitations of classical approaches (Kuijpers et al. 2010; Neutens et al. 2011; Winter and Lin 2011). Along these lines, Downs (2010) fused time geography and kernel density estimation in developing timegeographic density estimation (TGDE), which may be used to estimate mobile objects’ probable locations in continuous space, given a time budget between control points (Downs 2010). Downs and Horner (2012) extend TGDE to discrete network space, demonstrating its application with GPS-based vehicle tracking data (Downs and Horner 2012) and using it in searches for travellers’ destinations missing in travel surveys (Horner et al. 2012).

Intensity Values for Traveller 1 (eq. 1).

Intensity Values for Traveller 1 (eq. 1).

“The present paper explores a new direction for TGDE, namely the creation of a densitybased accessibility measure for mobile objects. Related to time geography, accessibility measures have also garnered widespread attention in the literature (Kwan 1998; Miller 1999; O’Sullivan et al. 2000; Yu and Shaw 2008; Delafontaine et al. 2012). Our new metrics gauge how accessible a moving object is to particular opportunities of interest, given the constraints inherent to its movement plan. Thus, we are able not only visualize where the object most likely could have been (Downs and Horner 2012), but we also capture the configuration and magnitude of activities relative to its travel path from both a visual and analytic perspective.”

Data Transformation and Uncertainty in Geostatistical Combination of Radar and Rain Gauges

Journal of Hydrometeorology Journal of Hydrometeorology, Volume 13 Issue 4, August 2012

Rebekka Erdin, Christoph Frei, and Hans R. Künsch

“Geostatistics provides a popular framework for deriving high-resolution quantitative precipitation estimates (QPE) by combining radar and rain gauge data. However, the skewed and heteroscedastic nature of precipitation is in contradiction to assumptions of classical geostatistics. This study examines the potential of trans-Gaussian kriging to overcome this contradiction. Combination experiments are undertaken with kriging with external drift (KED) using several settings of the Box–Cox transformation. Hourly precipitation data in Switzerland for the year 2008 serve as test bed to compare KED with and without transformation. The impact of transformation is examined with regard to compliance with model assumptions, accuracy of the point estimate, and reliability of the probabilistic estimate. Data transformation improves the compliance with model assumptions, but some level of contradiction remains in situations with many dry gauges. Very similar point estimates are found for KED with untransformed and appropriately transformed data. However, care is needed to avoid excessive transformation (close to log) because this can introduce a positive bias. Strong benefits from transformation are found for the probabilistic estimate, which is rendered positively skewed, sensitive to precipitation amount, and quantitatively more reliable. Without transformation, 44% of all precipitation observations larger than 5 mm h−1 are considered as extremely unlikely by the probabilistic estimate in the test application. Transformation reduces this rate to 4%. Although transformation cannot fully remedy the complications for geostatistics in radar–gauge combination, it seems a useful procedure if realistic and reliable estimation uncertainties are desired, such as for the stochastic simulation of QPE ensembles.”

Aerial Survey and Spatial Analysis of Sources of Light Pollution in Berlin, Germany

Remote Sensing of EnvironmentRemote Sensing of Environment, Volume 126, November 2012, Pages 39–50

Helga U. Kuechly, Christopher C.M. Kyba, Thomas Ruhtz, Carsten Lindemann, Christian Wolter, Jürgen Fischer, and Franz Hölker

“Highlights

  • A 391 square kilometer urban light pollution map is produced with 1 m resolution.
  • Geospatial analysis of the map compares lighting to land use type.
  • Lighting associated with streets accounts for 1/3 of the total zenith uplight.
  • Land use types of differing areas are compared equivalently using mean brightness.
  • The utility of night aerial photography for light pollution studies is demonstrated.

“Aerial observations of light pollution can fill an important gap between ground based surveys and nighttime satellite data. Terrestrially bound surveys are labor intensive and are generally limited to a small spatial extent, and while existing satellite data cover the whole world, they are limited to coarse resolution. This paper describes the production of a high resolution (1 m) mosaic image of the city of Berlin, Germany at night. The dataset is spatially analyzed to identify the major sources of light pollution in the city based on urban land use data. An area-independent ‘brightness factor’ is introduced that allows direct comparison of the light emission from differently sized land use classes, and the percentage area with values above average brightness is calculated for each class. Using this methodology, lighting associated with streets has been found to be the dominant source of zenith directed light pollution (31.6%), although other land use classes have much higher average brightness. These results are compared with other urban light pollution quantification studies. The minimum resolution required for an analysis of this type is found to be near 10 m. Future applications of high resolution datasets such as this one could include: studies of the efficacy of light pollution mitigation measures, improved light pollution simulations, economic and energy use, the relationship between artificial light and ecological parameters (e.g. circadian rhythm, fitness, mate selection, species distributions, migration barriers and seasonal behavior), or the management of nightscapes. To encourage further scientific inquiry, the mosaic data is freely available at Pangaea: http://dx.doi.org/10.1594/PANGAEA.785492.”