Sharing Geographic Data: How to Update Distributed or Replicated Data

Geographic data is expensive to collect and maintain and sharing data is crucial for its effective use in urban planning at all levels. For a few hardly ever changing themes the simple distribution of copies of data is feasible, but for other data, access to “live” data and updating, sometimes even distributed updating, of the data is necessary. The organization of sharing data can be separated into three sets of issues: (1) Interpretation: how to understand the data, (2) Authorization: is a user permitted to use the data, and (3) Access: how to achieve effective and non-disturbing use and updating of data by several users? Solutions must take threats into account: hackers may try to steal or disturb the use of data, and the revelations of Snowden's documents only emphasize the danger of others reading data not intended for their eyes. Effective sharing geographic data without conflicts requires integrating results from different areas of computer science research, including at least: cryptography, computer security, database management, and computer networking

Why Is Cartographic Generalization So Hard?

I remember first presentations about cartographic generalizations (Spiess 1971), where tools for generalization were shown, but the conclusions stated, more or less clearly, that fully automated cartographic generalization was not possible. There has been an impressive stream of research documenting methods to generalize maps. The consensus today seems to be that automated tools under control of a cartographer are the most effective means (Buttenfield et al. 1991; Weibel 1995). In this contribution some fundamental aspects of map making, including generalizations are analyzed. Map generalization is studied by most map producers, especially the National Mapping Agencies, because they have to maintain maps at different scale and it appears economical to derive a map at smaller from a map of a larger scale by an automated process. Equally important is the production of maps at arbitrary scales for the illustration of web pages. These tasks are the backdrop for the following abstract analysis

Constraints on Assembly Bias from Galaxy Clustering

We constrain the newly-introduced decorated Halo Occupation Distribution (HOD) model using SDSS DR7 measurements of projected galaxy clustering or r-band luminosity threshold samples. The decorated HOD is a model for the galaxy-halo connection that augments the HOD by allowing for the possibility of galaxy assembly bias: galaxy luminosity may be correlated with dark matter halo properties besides mass, Mvir. We demonstrate that it is not possible to rule out galaxy assembly bias using DR7 measurements of galaxy clustering alone. Moreover, galaxy samples with Mr < -20 and Mr < -20.5 favor strong central galaxy assembly bias. These samples prefer scenarios in which high-concentration are more likely to host a central galaxy relative to low-concentration halos of the same mass. We exclude zero assembly bias with high significance for these samples. Satellite galaxy assembly bias is significant for the faintest sample, Mr < -19. We find no evidence for assembly bias in the Mr < -21 sample. Assembly bias should be accounted for in galaxy clustering analyses or attempts to exploit galaxy clustering to constrain cosmology. In addition to presenting the first constraints on HOD models that accommodate assembly bias, our analysis includes several improvements over previous analyses of these data. Therefore, our inferences supersede previously-published results even in the case of a standard HOD analysis.Comment: 15 pages, 8 figures. To be submitted to MNRAS. Comments Welcome. Python scripts to perform this analysis and MCMC chains will all be made publicly availabl

Expropriation in the Simple Cadastre

In this paper we investigate the necessary interaction between expropriation and the cadastre. We investigate first the role of expropriation in modern society and the stake holders and then analyze the interaction with land registration and cadastre. The "simple cadastre" framework allows a treatment independent of national particulars. A simple cadastre is a minimal model that satisfies the needs of the users of the cadastre and abstracts from non-essential aspects, any national legislation is full of. In this paper we investigate how a cadastre supports expropriation and what the necessary interface is. We conclude that the expropriation procedures need access to registration data and a process to register a transfer of ownership effectuated by a court judgment, but no special arrangements that would only serve expropriation procedures

Brightest galaxies as halo centre tracers in SDSS DR7

Determining the positions of halo centres in large-scale structure surveys is crucial for many cosmological studies. A common assumption is that halo centres correspond to the location of their brightest member galaxies. In this paper, we study the dynamics of brightest galaxies with respect to other halo members in the Sloan Digital Sky Survey DR7. Specifically, we look at the line-of-sight velocity and spatial offsets between brightest galaxies and their neighbours. We compare those to detailed mock catalogues, constructed from high-resolution, dark-matter-only $N$-body simulations, in which it is assumed that satellite galaxies trace dark matter subhaloes. This allows us to place constraints on the fraction $f_{\rm BNC}$ of haloes in which the brightest galaxy is not the central. Compared to previous studies we explicitly take into account the unrelaxed state of the host haloes, velocity offsets of halo cores and correlations between $f_{\rm BNC}$ and the satellite occupation. We find that $f_{\rm BNC}$ strongly decreases with the luminosity of the brightest galaxy and increases with the mass of the host halo. Overall, in the halo mass range $10^{13} - 10^{14.5} h^{-1} M_\odot$ we find $f_{\rm BNC} \sim 30\%$, in good agreement with a previous study by Skibba et al. We discuss the implications of these findings for studies inferring the galaxy--halo connection from satellite kinematics, models of the conditional luminosity function and galaxy formation in general.Comment: 24 pages, 15 figures. Accepted for publication in MNRA

Maturing Satellite Kinematics into a Competitive Probe of the Galaxy-Halo Connection

The kinematics of satellite galaxies moving in a dark matter halo are a direct probe of the underlying gravitational potential. Thus, the phase-space distributions of satellites represent a powerful tool to determine the galaxy-halo connection from observations. By stacking the signal of a large number of satellite galaxies this potential can be unlocked even for haloes hosting a few satellites on average. In this work, we test the impact of various modelling assumptions on constraints derived from analysing satellite phase-space distributions in the non-linear, 1-halo regime. We discuss their potential to explain the discrepancy between average halo masses derived from satellite kinematics and gravitational lensing previously reported. Furthermore, we develop an updated, more robust analysis to extract constraints on the galaxy-halo relation from satellite properties in spectroscopic galaxy surveys such as the SDSS. We test the accuracy of this approach using a large number of realistic mock catalogues. Furthermore, we find that constraints derived from such an analysis are complementary and competitive with respect to the commonly used galaxy clustering and galaxy-galaxy lensing observables.Comment: 24 pages, 15 figures; resubmitted to MNRAS after first referee repor

Updated Results on the Galaxy-Halo Connection from Satellite Kinematics in SDSS

We present new results on the relationship between central galaxies and dark matter haloes inferred from observations of satellite kinematics in the Sloan Digital Sky Survey (SDSS) DR7. We employ an updated analysis framework that includes detailed mock catalogues to model observational effects in SDSS. Our results constrain the colour-dependent conditional luminosity function (CLF) of dark matter haloes, as well as the radial profile of satellite galaxies. Confirming previous results, we find that red central galaxies live in more massive haloes than blue galaxies at fixed luminosity. Additionally, our results suggest that satellite galaxies have a radial profile less centrally concentrated than dark matter but not as cored as resolved subhaloes in dark matter-only simulations. Compared to previous works using satellite kinematics by More et al., we find much more competitive constraints on the galaxy-halo connection, on par with those derived from a combination of galaxy clustering and galaxy-galaxy lensing. We compare our results on the galaxy-halo connection to other studies using galaxy clustering and group catalogues, showing very good agreement between these different techniques. We discuss future applications of satellite kinematics in the context of constraining cosmology and the relationship between galaxies and dark matter haloes.Comment: 18 pages, 10 figures, submitted to MNRAS, comments welcom

How to Optimally Constrain Galaxy Assembly Bias: Supplement Projected Correlation Functions with Count-in-cells Statistics

Most models for the connection between galaxies and their haloes ignore the possibility that galaxy properties may be correlated with halo properties other than mass, a phenomenon known as galaxy assembly bias. Yet, it is known that such correlations can lead to systematic errors in the interpretation of survey data. At present, the degree to which galaxy assembly bias may be present in the real Universe, and the best strategies for constraining it remain uncertain. We study the ability of several observables to constrain galaxy assembly bias from redshift survey data using the decorated halo occupation distribution (dHOD), an empirical model of the galaxy--halo connection that incorporates assembly bias. We cover an expansive set of observables, including the projected two-point correlation function $w_{\mathrm{p}}(r_{\mathrm{p}})$, the galaxy--galaxy lensing signal $\Delta \Sigma(r_{\mathrm{p}})$, the void probability function $\mathrm{VPF}(r)$, the distributions of counts-in-cylinders $P(N_{\mathrm{CIC}})$, and counts-in-annuli $P(N_{\mathrm{CIA}})$, and the distribution of the ratio of counts in cylinders of different sizes $P(N_2/N_5)$. We find that despite the frequent use of the combination $w_{\mathrm{p}}(r_{\mathrm{p}})+\Delta \Sigma(r_{\mathrm{p}})$ in interpreting galaxy data, the count statistics, $P(N_{\mathrm{CIC}})$ and $P(N_{\mathrm{CIA}})$, are generally more efficient in constraining galaxy assembly bias when combined with $w_{\mathrm{p}}(r_{\mathrm{p}})$. Constraints based upon $w_{\mathrm{p}}(r_{\mathrm{p}})$ and $\Delta \Sigma(r_{\mathrm{p}})$ share common degeneracy directions in the parameter space, while combinations of $w_{\mathrm{p}}(r_{\mathrm{p}})$ with the count statistics are more complementary. Therefore, we strongly suggest that count statistics should be used to complement the canonical observables in future studies of the galaxy--halo connection.Comment: Figures 3 and 4 show the main results. Published in Monthly Notices of the Royal Astronomical Societ

The Galaxy Clustering Crisis in Abundance Matching

Galaxy clustering on small scales is significantly under-predicted by sub-halo abundance matching (SHAM) models that populate (sub-)haloes with galaxies based on peak halo mass, $M_{\rm peak}$. SHAM models based on the peak maximum circular velocity, $V_{\rm peak}$, have had much better success. The primary reason $M_{\rm peak}$ based models fail is the relatively low abundance of satellite galaxies produced in these models compared to those based on $V_{\rm peak}$. Despite success in predicting clustering, a simple $V_{\rm peak}$ based SHAM model results in predictions for galaxy growth that are at odds with observations. We evaluate three possible remedies that could "save" mass-based SHAM: (1) SHAM models require a significant population of "orphan" galaxies as a result of artificial disruption/merging of sub-haloes in modern high resolution dark matter simulations; (2) satellites must grow significantly after their accretion; and (3) stellar mass is significantly affected by halo assembly history. No solution is entirely satisfactory. However, regardless of the particulars, we show that popular SHAM models based on $M_{\rm peak}$ cannot be complete physical models as presented. Either $V_{\rm peak}$ truly is a better predictor of stellar mass at $z\sim 0$ and it remains to be seen how the correlation between stellar mass and $V_{\rm peak}$ comes about, or SHAM models are missing vital component(s) that significantly affect galaxy clustering.Comment: 25 pages, 22 figures, submitted to MNRAS, comments welcom