Comparison of Thematic Maps Using Symbolic Entropy

Comparison of thematic maps is an important task in a number of disciplines. Map comparison has traditionally been conducted using cell-by-cell agreement indicators, such as the Kappa measure. More recently, other methods have been proposed that take into account not only spatially coincident cells in two maps, but also their surroundings or the spatial structure of their differences. The objective of this paper is to propose a framework for map comparison that considers 1) the patterns of spatial association in two maps, in other words, the map elements in their surroundings; 2) the equivalence of those patterns; and 3) the independence of patterns between maps. Two new statistics for the spatial analysis of qualitative data are introduced. These statistics are based on the symbolic entropy of the maps, and function as measures of map compositional equivalence and independence. As well, all inferential elements to conduct hypothesis testing are developed. The framework is illustrated using real and synthetic maps. Key word: Thematic maps, map comparison, qualitative variables, spatial association, symbolic entropy, hypothesis tests

Real-world comparison of probe vehicle emissions and fuel consumption using diesel and 5 % biodiesel (B5) blend.

An instrumented EURO I Ford Mondeo was used to perform a real-world comparison of vehicle exhaust (carbon dioxide, carbon monoxide, hydrocarbons and oxides of nitrogen) emissions and fuel consumption for diesel and 5% biodiesel in diesel blend (B5) fuels. Data were collected on multiple replicates of three standardised on-road journeys: (1) A simple urban route; (2) A combined urban/inter-urban route; and, (3) An urban route subject to significant traffic management. At the total journey measurement level, data collected here indicate that replacing diesel with a B5 substitute could result in significant increases in both NOx emissions (8-13%) and fuel consumption (7-8%). However, statistical analysis of probe vehicle data demonstrated the limitations of comparisons based on such total journey measurements, i.e., methods analogous to those used in conventional dynamometer/drive cycle fuel comparison studies. Here, methods based on the comparison of speed/acceleration emissions and fuel consumption maps are presented. Significant variations across the speed/acceleration surface indicated that direct emission and fuel consumption impacts were highly dependent on the journey/drive cycle employed. The emission and fuel consumption maps were used both as descriptive tools to characterise impacts and predictive tools to estimate journey-specific emission and fuel consumption effects

Statistical and spatial analysis of landslide susceptibility maps with different classification systems

The final publication is available at Springer via http://dx.doi.org/10.1007/s12665-016-6124-1A landslide susceptibility map is an essential tool for land-use spatial planning and management in mountain areas. However, a classification system used for readability determines the final appearance of the map and may therefore influence the decision-making tasks adopted. The present paper addresses the spatial comparison and the accuracy assessment of some well-known classification methods applied to a susceptibility map that was based on a discriminant statistical model in an area in the Eastern Pyrenees. A number of statistical approaches (Spearman’s correlation, kappa index, factorial and cluster analyses and landslide density index) for map comparison were performed to quantify the information provided by the usual image analysis. The results showed the reliability and consistency of the kappa index against Spearman’s correlation as accuracy measures to assess the spatial agreement between maps. Inferential tests between unweighted and linear weighted kappa results showed that all the maps were more reliable in classifying areas of highest susceptibility and less reliable in classifying areas of low to moderate susceptibility. The spatial variability detected and quantified by factorial and cluster analyses showed that the maps classified by quantile and natural break methods were the closest whereas those classified by landslide percentage and equal interval methods displayed the greatest differences. The difference image analysis showed that the five classified maps only matched 9 % of the area. This area corresponded to the steeper slopes and the steeper watershed angle with forestless and sunny slopes at low altitudes. This means that the five maps coincide in identifying and classifying the most dangerous areas. The equal interval map overestimated the susceptibility of the study area, and the landslide percentage map was considered to be a very optimistic model. The spatial pattern of the quantile and natural break maps was very similar, but the latter was more consistent and predicted potential landslides more efficiently and reliably in the study area.Peer ReviewedPreprin

X-ray measured metallicities of the intra-cluster medium: a good measure for the metal mass?

Aims. We investigate whether X-ray observations map heavy elements in the Intra-Cluster Medium (ICM) well and whether the X-ray observations yield good estimates for the metal mass, with respect to predictions on transport mech- anisms of heavy elements from galaxies into the ICM. We further test the accuracy of simulated metallicity maps. Methods. We extract synthetic X-ray spectra from N-body/hydrodynamic simulations including metal enrichment pro- cesses, which we then analyse with the same methods as are applied to observations. By changing the metal distribution in the simulated galaxy clusters, we investigate the dependence of the overall metallicity as a function of the metal distribution. In addition we investigate the difference of X-ray weighted metal maps produced by simulations and metal maps extracted from artifcial X-ray spectra, which we calculate with SPEX2.0 and analyse with XSPEC12.0. Results. The overall metallicity depends strongly on the distribution of metals within the galaxy cluster. The more inhomogeneously the metals are distributed within the cluster, the less accurate is the metallicity as a measure for the true metal mass. The true metal mass is generally underestimated by X-ray observations. The difference between the X-ray weighted metal maps and the metal maps from synthetic X-ray spectra is on average less than 7% in the temperature regime above T > 3E7 K, i.e. X-ray weighted metal maps can be well used for comparison with observed metal maps. Extracting the metal mass in the central parts (r < 500 kpc) of galaxy clusters with X-ray observations results in metal mass underestimates up to a factor of three.Comment: 7 pages, 9 figures, accepted for publication in A&

On-line Vis-Nir sensor determination of soil variations of sodium, potassium and magnesium

Among proximal measurement methods, visible and near infrared (Vis-Nir) spectroscopy probably has the greatest potential for determining the physico-chemical properties of different natural resources, including soils. This study was conducted to determine the sodium, potassium and magnesium variations in a 10. Ha field located in Karacabey district (Bursa Province, Turkey) using an on-line Vis-Nir sensor. A total of 92 soil samples were collected from the field. The performance and accuracy of the Na, K and Mg calibration models was evaluated in cross-validation and independent validation. Three categories of maps were developed: 1) reference laboratory analyses maps based on 92 points 2) Full-data point maps based on all 6486 on-line points Vis-Nir predicted in 2013 and 3) full- data point maps based on all 2496 on-line points Vis-Nir predicted in 2015. Results showed that the prediction performance in the validation set was successful, with average R2 values of 0.82 for Na, 0.70 for K, and 0.79 for Mg, average root mean square error of prediction (RMSEP) values of 0.02% (Na), 0.20% (K), and 1.32% (Mg) and average residual prediction deviation (RPD) values of 2.13 (Na), 0.97 (K), and 2.20 (Mg). On-line field measurement was also proven to be successful with validation results showing average R2 values of 0.78 (Na), 0.64 (K), and 0.60 (Mg), average RMSEP values of 0.04% (Na), 0.13% (K), and 2.19% (Mg) and average RPD values of 1.57 (Na) 1.68 (K) and 1.56 (Mg). Based on 3297 points, maps of Na, K and Mg were produced after N, P, K and organic fertilizer applications, and these maps were then compared to the corresponding maps from the previous year. The comparison showed a variation in soil properties that was attributed to the variable rate of fertilization implemented in the preceding year

A Proposal for Semantic Map Representation and Evaluation

Semantic mapping is the incremental process of “mapping” relevant information of the world (i.e., spatial information, temporal events, agents and actions) to a formal description supported by a reasoning engine. Current research focuses on learning the semantic of environments based on their spatial location, geometry and appearance. Many methods to tackle this problem have been proposed, but the lack of a uniform representation, as well as standard benchmarking suites, prevents their direct comparison. In this paper, we propose a standardization in the representation of semantic maps, by defining an easily extensible formalism to be used on top of metric maps of the environments. Based on this, we describe the procedure to build a dataset (based on real sensor data) for benchmarking semantic mapping techniques, also hypothesizing some possible evaluation metrics. Nevertheless, by providing a tool for the construction of a semantic map ground truth, we aim at the contribution of the scientific community in acquiring data for populating the dataset