The convergence of GIS and social media: challenges for GIScience

It is hard to believe that 10 years have passed since we wrote our guest editorial for IJGIS (Sui and Goodchild 2001 Sui, D.Z. and Goodchild, M.F. 2001. Are GIS becoming new media?. International Journal of Geographical Information Science, 15(5): 387–390. [Taylor & Francis Online], [Web of Science ®] , [Google Scholar]). Using the nascent evidence that emerged in the late 1990s, we speculated back in 2001 that geographic information systems (GIS) were rapidly becoming part of the mass media. On the basis of the proposition of GIS as media, we were able to link GIScience with theories in media studies such as Marshall McLuhan's law of the media, which considers modern media as modifiable perceptive extensions of human thought (Sui and Goodchild 2003 Sui, D.Z. and Goodchild, M.F. 2003. A tetradic analysis of GIS and society using McLuhan's law of media. Canadian Geographers, 47(1): 5–17. [Crossref], [Web of Science ®] , [Google Scholar]). Remarkable conceptual and technological advances in GIS have been made during the past 10 years. The goal of this review is to provide an update on the ‘GIS as media’ argument we made 10 years ago and to discuss the new challenges for GIScience posed by the growing convergence of GIS and social media.     

Approximation of Gaussian spatial autoregressive models for massive regular square tessellation data

Most of the literature to date proposes approximations to the determinant of a positive definite n × n spatial covariance matrix (the Jacobian term) for Gaussian spatial autoregressive models that fail to support the analysis of massive georeferenced data sets. This paper briefly surveys this literature, recalls and refines much simpler Jacobian approximations, presents selected eigenvalue estimation techniques, summarizes validation results (for estimated eigenvalues, Jacobian approximations, and estimation of a spatial autocorrelation parameter), and illustrates the estimation of the spatial autocorrelation parameter in a spatial autoregressive model specification for cases as large as n = 37,214,101. The principal contribution of this paper is to the implementation of spatial autoregressive model specifications for any size of georeferenced data set. Its specific additions to the literature include (1) new, more efficient estimation algorithms; (2) an approximation of the Jacobian term for remotely sensed data forming incomplete rectangular regions; (3) issues of inference; and (4) timing results.     

Sediment loads and processes in large rivers

<正>The pressure and impact on large rivers have increased greatly in recent years,as a consequence of their exploitation to meet various human needs.Large rivers are particularly exposed to problems of multiple uses,often with conflicting aims.At the global scale river systems are increasingly altered by dams,leading to interruption of continuity and a disrupted sediment regime,which results in far-reaching problems.These challenges point also to the need for more integrated management approaches and consideration of catchment-river interactions emphasizing land use management and effects of these uses.At the global scale,there is currently no overview assessment of the current status of the world's large rivers,the conflicting demands on such rivers,and likely future anthropogenic impacts,as well as the potential for restoration,improvements in integrated management and the associated problems caused by their multiple uses.The special issue in the International Journal of Sediment Research on"Sediment loads and processes in large rivers"aims to provide a global forum for a wide-ranging discussion of key issues related to research on large rivers and to their effective and sustainable management,involving both scientists and decision makers.The sequence of papers in the special issue highlights the current situation in different river systems with regard to morphodynamic reactions of     

Phase difference analysis of temperature and vegetation phenology for beech forest: a wavelet approach

Temporal shifts in phenology or vegetation period of plants are seen as indicators of global warming with potentially severe impacts on ecosystem functioning. In spite of increasing knowledge on drivers, it is of utmost importance to disentangle the relationship between air temperatures, phenological events, potential temporal lags (phase shifts) and time scale for certain plant species. Assessing the phase shifts as well as the scale-dependent relationship between temperature and vegetation phenology requires the development of a nonlinear temporal model. Therefore, we use wavelet analysis and present a framework for identifying scale-dependent cross-phase coupling of bivariate time series. It allows the calculation of (a) scale-dependent decompositions of time series, (b) phase shifts of seasonal components in relation to the annual cycle, and (c) inter-annual phase differences between seasonal phases of different time series. The model is applied to air temperature data and remote sensing phenology data of a beech forest in Germany. Our study reveals that certain seasonal changes in amplitude and phase with respect to the normal annual rhythm of temperature and beech phenology are coupled time-delayed components, which are characterized by a time shift of about one year.     

Numerical relationships between magnetic parameters measured in Quaternary sediments and global paleoclimatic proxies

The complexity of most geological and geophysical problems prompts sometimes the use of non linear mathematical methods to handle them. An adaptive neuro fuzzy inference system (ANFIS) that combines fuzzy logic with neural networks, is applied here to study a paleoclimate section from the Quaternary sedimentary fill of the Lake Mucubají (western Venezuela). The purpose of this work is to find a set of numerical relationships that could predict the possible connections between oxygen isotope (δ¹⁸O) values from two different locations in the northern hemisphere (Ammersee in southern Germany and an ice core from the Greenland Ice Core Project — GRIP) and rock-magnetic parameters measured in Mucubají samples (i.e. mass-specific magnetic susceptibility — χ, magnetic remanence S-ratio, mass-specific saturation isothermal remanent magnetization — SIRM and anhysteretic remanent magnetization — ARM). The best inferences in terms of coefficient of determionation R² and the Root Mean-Square Error (RMSE) are obtained using those magnetic data as input that include information about magnetite grain size distributions, e.g., SIRM and ARM in FIS structures [1χ, 4ARM] and [4ARM, 1SIRM]. A comparison between Ammersee and GRIP actual data, as well as their corresponding inferences for the FIS structure [4ARM, 1SIRM], reveals a reasonable good inference of global trends for both records, overlooking the regional and/or local paleoclimate forcings that might have affected Ammersee. A better correlation between global isotope paleoclimate records and magnetic proxies, is perhaps prevented by the role played by local and regional paleoclimate and tectonism in Mucubají. We also argue that the ratio of ARM over SIRM appears to be related in a complex way to the onset and to the end of the Younger Dryas. Our novel approach to the assessment of a specific paleoclimate case study shows the potential of the ANFIS technique in solving problems where traditional univariate and multivariate linear regression methods could prove inadequate.     

Estimation of precipitation fields from 1-minute rain gauge time series – comparison of spatial and spatio-temporal interpolation methods

Accurate estimations of spatio-temporal fields at unsampled locations are important in a number of applications. Often, spatio-temporal fields are advected, which means the change in field values over time at a particular point in space stems to a large extent from motion of a more or less constant spatial field. For such dynamic fields, interpolation methods including information on the motion behaviour of the field are promising extensions of solely spatial (snapshot) and symmetric spatio-temporal methods. In this paper, the performance of different deterministic and geostatistical interpolation methods is compared for precipitation estimation from 1-minute time series of spatially distributed rain gauges. The focus is on spatio-temporal methods that include information on the motion behaviour of the rainfield, estimated from weather radar using optical flow. The different interpolation methods are introduced and evaluated using rain gauge measurements of a 15-day period and cross-validation. The results show that including information on the motion behaviour significantly improves interpolation quality in terms of RMSE.     

Estimation of phosphorus loads with sparse data for agricultural watersheds in the Czech Republic

Abstract

Agricultural watersheds in the Czech Republic are one of the primary sources of non-point-source phosphorus (P) loads in receiving waters. Since such non-point sources are generally located in headwater catchments, streamflow and P concentration data are sparse. We show how very short daily streamflow and P concentration records can be combined with nearby longer existing daily streamflow records to result in reliable estimates of daily and annual P concentrations and loads. Maintenance of variance streamflow record extension methods (MOVE) can be employed to extend short streamflow records. Constituent load regressions are used to predict daily P constituent loads from streamflow and other time varying characteristics. Annual P loads are then estimated for individual watersheds. Resulting annual P load estimates ranged from 0.21 to 95.4 kg year^-1 with a mean value of 11.77 kg year^-1. Similarly annual P yield estimates ranged from 0.01 to 0.3 kg ha^-1 year^-1 with an average yield of 0.07 kg ha^-1 year^-1. We document how short records of daily streamflow and P concentrations can be combined with a national network of daily streamflow records in the Czech Republic to arrive at meaningful and reliable estimates of annual P loads for small agricultural watersheds.

Citation Beránková, T., Vogel, R. M., Fiala, D. & Rosendorf, P. (2010) Estimation of phosphorus loads with sparse data for agricultural watersheds in the Czech Republic. Hydrol. Sci. J. 55(8), 1417–1426.     

Solitary Rossby Waves in Zonally Varying Jet Flows

The dynamics of solitary Rossby waves (SRWs) embedded in a meridionally sheared, zonally varying background flow are examined using a non-divergent barotropic model centered on a midlatitude g -plane. The zonally varying background flow, which is produced by an external potential vorticity (PV) forcing, yields a modified Korteweg-de Vries (K-dV) equation that governs the spatial-temporal evolution of a disturbance field that contains both Rossby wave packets and SRWs. The modified K-dV equation differs from the classical equation in that the zonally varying background flow, which varies on the same scale as the disturbance field, directly affects the disturbance linear translation speed and linear growth characteristics. In the limit of a locally parallel background flow, equations governing the amplitude and propagation characteristics of SRWs are derived analytically. These equations show, for example, that a sufficiently large (small) translation speed and/or a sufficiently weak (strong) background zonal shear favor transmission (reflection) of the SRW through (from) the jet. Conservation equations are derived showing that time changes in the domain averaged amplitude ("mass") or squared amplitude ("momentum") are due to zonal variation in both the linear, long-wave phase speed and linear growth; dispersion and nonlinearity do not affect the "mass" or "momentum". Provided (1) the background PV forcing is sufficiently small, or (2) the background PV forcing is meridionally symmetric and the disturbance is a SRW, the dynamics of the disturbance field is Hamiltonian and mass and energy are thus conserved. Numerical solutions of the K-dV equation show that the zonally varying background flow yields three general classes of behavior: reflection, transmission, or trapping. Within each class there exists SRWs and Rossby wave packets. SRWs that become trapped within the zonally localized jet region may exhibit the following behaviors: (1) an oscillatory decay to a steady state at the jet center, (2) the creation of additional SRWs within the jet region, or (3) a steady-state wherein the solution has a smoothed step-like structure located downstream along the jet axis.     

INTRINSIC THRESHOLDS IN SOIL SYSTEMS

The threshold concept has been applied with considerable success to the understanding of geomorphic systems. Both intrinsic and extrinsic thresholds can be recognized in soil systems, but intrinsic thresholds have previously been largely ignored. Examples of intrinsic thresholds in soils include minimum levels of sesquioxides for immobilization of organic matter in spodic horizons, leaching of carbonates before clay movement can take place, and certain minimum clay mineral ratios before a pedogenic regime dominated by pedoturbation can occur. Recognition of intrinsic thresholds explains soil instability in the absence of environmental change.