The space-time cube as part of a GeoVisual analytics environment to support the understanding of movement data

This paper reports the results of an empirical usability experiment on the performance of the space-time cube in a GeoVisual analytics environment. It was developed to explore movement data based on the requirements of human geographers. The interactive environment consists of multiple coordinated views incorporating three graphical representations. For the experiment, two groups of the user, domain experts and non-domain experts, had to execute several map-use tasks to answers specific question. The data collected during the experiment were analysis resulting in a set of usability metrics related to the effectiveness, efficiency and user satisfaction of developed application. The comparison of both groups showed that domain experts were able to operate the visual analytical environment more effectively and efficiently due to their interest to explore their data. The user feedback derived from the analysis of both experiments was further processed for the improvement of the application.     

A ten-to-twelve year variation in the stratosphere of the Northern Hemisphere

This review paper for STIB (Stratosphere-Troposphere Interaction and the Biosphere; a proposed core project for IGBP) summarizes several features of a recently discovered 10–12 year oscillation in the atmosphere on the Northern Hemisphere. The oscillation is especially strong in the stratosphere during the warmer half of the year, but it is evident in the stratosphere and troposphere also in winter if the data are grouped according to the phase of the Quasi-Biennial Oscillation of the wind in the equatorial stratosphere. During the 40 years with data available to describe the oscillation it was phase locked with the 11-year solar cycle.Affiliate Scientist, NCAR.The National Center for Atmospheric Research is sponsored by the National Science Foundation.     

Semi-automatic delineation of badlands using contrast in vegetation activity: a case study in the lower Chambal valley,India

Population growth worldwide leads to an increasing pressure on the land. Recent studies reported that many areas covered by badlands are decreasing because parts of badlands are being levelled and converted into arable land. It is important to monitor these changes for environmental planning. This paper proposes a remote-sensing-based detection method which allows mapping of badland dynamics based on seasonal vegetation changes in the lower Chambal valley, India. Supervised classification was applied on three Landsat (Thematic Mapper) images, from 3 different seasons; January (winter), April (summer) and October (post-monsoon). Different band selection methods were applied to get the best classification. Validation was done by ground referencing and a GeoEye-1 satellite image. The image from January performed best with overall accuracy of 87% and 0.69 of kappa. This method opens the possibilities of using semi-automatic classification for the Chambal badlands which is so far mapped with manual interpretations only.     

Correcting superconducting gravity time-series using rainfall modelling at the Vienna and Membach stations and application to Earth tide analysis

We demonstrate the possibility to improve the signal-to-noise ratio of superconducting gravity time-series by correcting for local hydrological effects. Short-term atmospheric events associated with heavy rain induce step-like gravity signals that deteriorate the frequency spectrum estimates. Based on 4D modeling constrained by high temporal resolution rain gauge data, rainfall admittances for the Vienna and Membach superconducting gravity stations are calculated. This allows routine correction for Newtonian rain water effects, which reduces the standard deviation of residuals after tidal parameter adjustment by 10%. It also improves the correction of steps of instrumental origin when they coincide with step-like water mass signals.     

Efficient collection of training data for sub-pixel land cover classification using neural networks

Artificial neural networks (ANNs) are a popular class of techniques for performing soft classifications of satellite images. They have successfully been applied for estimating crop areas through sub-pixel classification of medium to low resolution images. Before a network can be used for classification and estimation, however, it has to be trained. The collection of the reference area fractions needed to train an ANN is often both time-consuming and expensive. This study focuses on strategies for decreasing the efforts needed to collect the necessary reference data, without compromising the accuracy of the resulting area estimates. Two aspects were studied: the spatial sampling scheme (i) and the possibility for reusing trained networks in multiple consecutive seasons (ii). Belgium was chosen as the study area because of the vast amount of reference data available. Time series of monthly NDVI composites for both SPOT-VGT and MODIS were used as the network inputs. The results showed that accurate regional crop area estimation (R² > 80%) is possible using only 1% of the entire area for network training, provided that the training samples used are representative for the land use variability present in the study area. Limiting the training samples to a specific subset of the population, either geographically or thematically, significantly decreased the accuracy of the estimates. The results also indicate that the use of ANNs trained with data from one season to estimate area fractions in another season is not to be recommended. The interannual variability observed in the endmembers’ spectral signatures underlines the importance of using up-to-date training samples. It can thus be concluded that the representativeness of the training samples, both regarding the spatial and the temporal aspects, is an important issue in crop area estimation using ANNs that should not easily be ignored.     

Carbon costs and benefits of France’s biomass energy production targets

Background

Concern about climate change has motivated France to reduce its reliance on fossil fuel by setting targets for increased biomass-based renewable energy production. This study quantifies the carbon costs and benefits for the French forestry sector in meeting these targets. A forest growth and harvest simulator was developed for French forests using recent forest inventory data, and the wood-use chain was reconstructed from national wood product statistics. We then projected wood production, bioenergy production, and carbon balance for three realistic intensification scenarios and a business-as-usual scenario. These intensification scenarios targeted either overstocked, harvest-delayed or currently actively managed stands.

Results

All three intensification strategies produced 11.6–12.4 million tonnes of oil equivalent per year of wood-based energy by 2026, which corresponds to the target assigned to French wood-energy to meet the EU 2020 renewable energy target. Sustaining this level past 2026 will be challenging, let alone further increasing it. Although energy production targets can be reached, the management intensification required will degrade the near-term carbon balance of the forestry sector, compared to continuing present-day management. Even for the best-performing intensification strategy, i.e., reducing the harvest diameter of actively managed stands, the carbon benefits would only become apparent after 2040. The carbon balance of a strategy putting abandoned forests back into production would only break even by 2055; the carbon balance from increasing thinning in managed but untended stands would not break even within the studied time periods, i.e. 2015–2045 and 2046–2100. Owing to the temporal dynamics in the components of the carbon balance, i.e., the biomass stock in the forest, the carbon stock in wood products, and substitution benefits, the merit order of the examined strategies varies over time.

Conclusions

No single solution was found to improve the carbon balance of the forestry sector by 2040 in a way that also met energy targets. We therefore searched for the intensification scenario that produces energy at the lowest carbon cost. Reducing rotation time of actively managed stands is slightly more efficient than targeting harvest-delayed stands, but in both cases, each unit of energy produced has a carbon cost that only turns into a benefit between 2060 and 2080.

     

Integrating Indoor and Outdoor Spaces for Pedestrian Navigation Guidance: A Review

In light of the many improvements within 3D urban modeling and Location‐Based Services, this article provides a timely review of the state‐of‐the‐art on integrating indoor and outdoor spaces in pedestrian navigation guidance aids. With people moving seamlessly between buildings and surrounding areas, navigation guidance tools should extend from merely outdoor or indoor guidance, to provide support in the combined indoor‐outdoor context. This article first examines the challenges and complexities of integrating indoor and outdoor spaces into a single navigation system. Next, by using objective selection criteria, 36 relevant studies were withheld and further reviewed on their specific developments in data model requirements, and algorithmic and context support for integrated IO navigation systems. This review shows that the challenges of dealing with both indoor and outdoor space structures, while taking into account pedestrian's freer use of space, currently complicate the proposition of a unified IO space concept for navigation. However, there are some ongoing developments (e.g. context definitions, algorithmic extensions, increased data availability, growing awareness of pedestrians’ perception during wayfinding) that will help to bring outdoor and indoor spaces closer together in the realm of combined geospatial analysis.     

Geoid, topography, and the Bouguer plate or shell

 Topography plays an important role in solving many geodetic and geophysical problems. In the evaluation of a topographical effect, a planar model, a spherical model or an even more sophisticated model can be used. In most applications, the planar model is considered appropriate: recall the evaluation of gravity reductions of the free-air, Poincaré–Prey or Bouguer kind. For some applications, such as the evaluation of topographical effects in gravimetric geoid computations, it is preferable or even necessary to use at least the spherical model of topography. In modelling the topographical effect, the bulk of the effect comes from the Bouguer plate, in the case of the planar model, or from the Bouguer shell, in the case of the spherical model. The difference between the effects of the Bouguer plate and the Bouguer shell is studied, while the effect of the rest of topography, the terrain, is discussed elsewhere. It is argued that the classical Bouguer plate gravity reduction should be considered as a mathematical construction with unclear physical meaning. It is shown that if the reduction is understood to be reducing observed gravity onto the geoid through the Bouguer plate/shell then both models give practically identical answers, as associated with Poincaré's and Prey's work. It is shown why only the spherical model should be used in the evaluation of topographical effects in the Stokes–Helmert solution of Stokes' boundary-value problem. The reason for this is that the Bouguer plate model does not allow for a physically acceptable condensation scheme for the topography. Received: 24 December 1999 / Accepted: 11 December 2000