The Scale of VGI in Map Production: A Perspective on European National Mapping Agencies

The perspective of European National Mapping Agencies (NMA) on the role of citizen sensing in map production was explored. The NMAs varied greatly in their engagement with the community generating volunteered geographic information (VGI) and in their future plans. From an assessment of NMA standard practices, it was evident that much VGI was acquired with a positional accuracy that, while less than that typically acquired by NMAs, actually exceeded the requirements of the nominal data capture scale used by most NMAs. Opportunities for VGI use in map revision and updating were evident, especially for agencies that use a continuous rather than cyclical updating policy. Some NMAs had also developed systems to engage with citizen sensors and examples are discussed. Only rarely was VGI used to collect data on features beyond the standard set used by the NMAs. The potential role of citizen sensing and so its current scale of use by NMAs is limited by a series of concerns, notably relating to issues of data quality, the nature and motivation of the contributors, legal issues, the sustainability of data source, and employment fears of NMA staff. Possible priorities for future research and development are identified to help ensure that the potential of VGI in mapping is realized.     

Stochastic synthesis approximating any process dependence and distribution

An extension of the symmetric-moving-average (SMA) scheme is presented for stochastic synthesis of a stationary process for approximating any dependence structure and marginal distribution. The extended SMA model can exactly preserve an arbitrary second-order structure as well as the high order moments of a process, thus enabling a better approximation of any type of dependence (through the second-order statistics) and marginal distribution function (through statistical moments), respectively. Interestingly, by explicitly preserving the coefficient of kurtosis, it can also simulate certain aspects of intermittency, often characterizing the geophysical processes. Several applications with alternative hypothetical marginal distributions, as well as with real world processes, such as precipitation, wind speed and grid-turbulence, highlight the scheme’s wide range of applicability in stochastic generation and Monte-Carlo analysis. Particular emphasis is given on turbulence, in an attempt to simulate in a simple way several of its characteristics regarded as puzzles.     

A spatial genetic algorithm for automating land partitioning

Land fragmentation is a widespread situation which may often hinder agricultural development. Land consolidation is considered to be the most effective land management planning approach for controlling land fragmentation and hence improving agricultural efficiency. Land partitioning is a basic process of land consolidation that involves the subdivision of land into smaller sub-spaces subject to a number of constraints. This paper explains the development of a module called LandParcelS (Land Parcelling System) that is a part of an integrated planning and decision support system called LACONISS (LAndCONsolidation Integrated Support System) which has been developed to assist land consolidation planning in Cyprus. LandParcelS automates the land partitioning process by designing and optimising land parcels in terms of their shape, size and value. The methodology integrates geographical information systems and a genetic algorithm that has been applied to two land blocks that are part of a larger case study area in Cyprus. Partitioning is treated as either a single or multi-objective problem for various optimisation cases. The results suggest that a step forward has been made in solving this complex spatial problem, although further research is needed to improve the algorithm. This approach may have relevance to other spatial planning tasks that involve single or multi-objective optimisation problems, especially those dealing with space partitioning.     

Something old,something new,something red,something blue*

Abstract

Hydrologists responsible for flood management need real-time data in order to manage imminent or ongoing floods. In this paper, innovative methods for accessing hydrological data and their spatial visualization are introduced. A multitude of relevant real-time, forecast and historical information is provided in a single, self-updating hydrological map information system. The system consists of a central database and a cartographic user interface and provides harmonized and filtered data in the form of interactive, customizable maps. Maps may also be cross-referenced with historical maps or may be animated for improved comprehension and decision making. Emphasis is placed on the development of the hydrological real-time database that manages large amounts of spatial, temporal and attributive data. The paper focuses on the cartographic user interface, its functionality and the resulting interactive hydrological maps.

Citation Lienert, C., Weingartner, R. &; Hurni, L. (2011) An interactive, web-based, real-time hydrological map information system. Hydrol. Sci. J. 56(1), 1–16     

On the prediction of persistent processes using the output of deterministic models

A problem frequently met in engineering hydrology is the forecasting of hydrological variables conditional on their historical observations and the hindcasts and forecasts of a deterministic model. On the contrary, it is a common practice for climatologists to use the output of general circulation models (GCMs) for the prediction of climatic variables despite their inability to quantify the uncertainty of the predictions. Here we apply the well-established Bayesian processor of forecasts (BPF) for forecasting hydroclimatic variables using stochastic models through coupling them with GCMs. We extend the BPF to cases where long-term persistence appears, using the Hurst-Kolmogorov process (HKp, also known as fractional Gaussian noise) and we investigate its properties analytically. We apply the framework to calculate the distributions of the mean annual temperature and precipitation stochastic processes for the time period 2016–2100 in the United States of America conditional on historical observations and the respective output of GCMs.     

Analysis of a Long Record of Annual Maximum Rainfall in Athens,Greece, and Design Rainfall Inferences

An annual series of maximum dailyrainfall extending through 1860–1995, i.e., 136 years,was extracted from the archives of a meteorologicalstation in Athens. This is the longest rainfall recordavailable in Greece and its analysis is required forthe prediction of intense rainfall in Athens, wherecurrently major flood protection works are under way.Moreover, the statistical analysis of this long recordcan be useful for investigating more generalisedissues regarding the adequacy of extreme valuedistributions for extreme rainfall analysis and theeffect of sample size on design rainfall inferences.Statistical exploration and tests based on this longrecord indicate no statistically significant climaticchanges in extreme rainfall during the last 136 years.Furthermore, statistical analysis shows that theconventionally employed Extreme Value Type I (EV1 orGumbel) distribution is inappropriate for the examinedrecord (especially in its upper tail), whereas thisdistribution would seem as an appropriate model iffewer years of measurements were available (i.e., partof this sample were used). On the contrary, theGeneral Extreme Value (GEV) distribution appears to besuitable for the examined series and its predictionsfor large return periods agree with the probablemaximum precipitation estimated by the statistical(Hershfield's) method, when the latter is consideredfrom a probabilistic point of view. Thus, the resultsof the analysis of this record agree with a recently(and internationally) expressed scepticism about theEV1 distribution which tends to underestimate thelargest extreme rainfall amounts. It is demonstratedthat the underestimation is quite substantial (e.g.,1 : 2) for large return periods and this fact must beconsidered as a warning against the widespread use ofthe EV1 distribution for rainfall extremes.