For the evaluation of results from remote sensing and high-resolution spatial models it is often necessary to assess the similarity of sets of maps. This paper describes a method to compare raster ...maps of categorical data. The method applies fuzzy set theory and involves both fuzziness of location and fuzziness of category. The fuzzy comparison yields a map, which specifies for each cell the degree of similarity on a scale of 0 to 1. Besides this spatial assessment of similarity also an overall value for similarity is derived. This statistic corrects the cell-average similarity value for the expected similarity. It can be considered the fuzzy equivalent of the Kappa statistic and is therefore called K
Fuzzy
. A hypothetical case demonstrates how the comparison method distinguishes minor changes and fluctuations within patterns from major changes. Finally, a practical case illustrates how the method can be useful in a validation process.
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BFBNIB, DOBA, GIS, IJS, IZUM, KILJ, KISLJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
People with low income often experience higher exposures to air pollutants. We compared the exposure to particulate matter (PM1, PM2.5 and PM10), Black Carbon (BC) and ultrafine particles (PNCs; ...0.02–1μm) for typical commutes by car, bus and underground from 4 London areas with different levels of income deprivation (G1 to G4, from most to least deprived). The highest BC and PM concentrations were found in G1 while the highest PNC in G3. Lowest concentrations for all pollutants were observed in G2. We found no systematic relationship between income deprivation and pollutant concentrations, suggesting that differences between transport modes are a stronger influence. The underground showed the highest PM concentrations, followed by buses and a much lower concentrations in cars. BC concentrations in the underground were overestimated due to Fe interference. BC concentrations were also higher in buses than cars because of a lower infiltration of outside pollutants into the car cabin. PNCs were highest in buses, closely followed by cars, but lowest in underground due to the absence of combustion sources. Concentration in the road modes (car and bus) were governed by the traffic conditions (such as traffic flow interruptions) at the specific road section. Exposures were reduced in trains with non-openable windows compared to those with openable windows. People from less income-deprived areas have a predominant use of car, receiving the lowest doses (RDD<1μgh−1) during commute but generating the largest emissions per commuter. Conversely, commuters from high income-deprived areas have a major reliance on the bus, receiving higher exposures (RDD between 1.52 and 3.49μgh−1) while generating less emission per person. These findings suggest an aspect of environmental injustice and a need to incorporate the socioeconomic dimension in life-course exposure assessments.
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•No systematic relationship between income deprivation and pollutant level was found.•Modes hierarchy for PM concentrations in London observed as underground≫bus>car.•Highest PNCs were measured in London buses, followed by car and underground train.•BC was 23% higher in London buses than cars and influenced by Fe in underground.•Air quality in trains depended on open/closed windows and above/underground tracks.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
ABSTRACT We use 317,000 emission-line galaxies from the Sloan Digital Sky Survey to investigate line-ratio selection of active galactic nuclei (AGNs). In particular, we demonstrate that "star ...formation (SF) dilution" by H ii regions causes a significant bias against AGN selection in low-mass, blue, star-forming, disk-dominated galaxies. This bias is responsible for the observed preference of AGNs among high-mass, green, moderately star-forming, bulge-dominated hosts. We account for the bias and simulate the intrinsic population of emission-line AGNs using a physically motivated Eddington ratio distribution, intrinsic AGN narrow line region line ratios, a luminosity-dependent bolometric correction, and the observed relation. These simulations indicate that, in massive ( ) galaxies, AGN accretion is correlated with specific star formation rate (SFR) but is otherwise uniform with stellar mass. There is some hint of lower black hole occupation in low-mass ( ) hosts, although our modeling is limited by uncertainties in measuring and interpreting the velocity dispersions of low-mass galaxies. The presence of SF dilution means that AGNs contribute little to the observed strong optical emission lines (e.g., and ) in low-mass and star-forming hosts. However the AGN population recovered by our modeling indicates that feedback by typical (low- to moderate-accretion) low-redshift AGNs has nearly uniform efficiency at all stellar masses, SFRs, and morphologies. Taken together, our characterization of the observational bias and resultant AGN occupation function suggest that AGNs are unlikely to be the dominant source of SF quenching in galaxies, but instead are fueled by the same gas which drives SF activity.
ABSTRACT We compare the physical and morphological properties of z ∼ 2 Ly emitting galaxies (LAEs) identified in the HETDEX Pilot Survey and narrow band studies with those of z ∼ 2 optical emission ...line selected galaxies (oELGs) identified via HST WFC3 infrared grism spectroscopy. Both sets of galaxies extend over the same range in stellar mass ( ), size (0.5 < R < 3.0 kpc), and star formation rate ( yr−1). Remarkably, a comparison of the most commonly used physical and morphological parameters-stellar mass, half-light radius, UV slope, SFR, ellipticity, nearest neighbor distance, star formation surface density, specific SFR, O iii luminosity, and O iii equivalent width-reveals no statistically significant differences between the populations. This suggests that the processes and conditions which regulate the escape of Ly from a z ∼ 2 star-forming galaxy do not depend on these quantities. In particular, the lack of dependence on the UV slope suggests that Ly emission is not being significantly modulated by diffuse dust in the interstellar medium. We develop a simple model of Ly emission that connects LAEs to all high-redshift star-forming galaxies where the escape of Ly depends on the sightline through the galaxy. Using this model, we find that mean solid angle for Ly escape is steradians; this value is consistent with those calculated from other studies.
► We developed
K
Simulation to assess the accuracy of simulated changes explicitly. ► This method truly tests a models’ capacity to explain land-use changes over time. ►
K
Simulation can be applied ...for any model that simulates categorical changes.
Land-use change models are typically calibrated to reproduce known historic changes. Calibration results can then be assessed by comparing two datasets: the simulated land-use map and the actual land-use map at the same time. A common method for this is the Kappa statistic, which expresses the agreement between two categorical datasets corrected for the expected agreement. This expected agreement is based on a stochastic model of random allocation given the distribution of class sizes. However, when a model starts from an initial land-use map and makes changes to it, that stochastic model does not pose a meaningful reference level. This paper introduces
K
Simulation, a statistic that is identical in form to the Kappa statistic but instead applies a more appropriate stochastic model of random allocation of class transitions relative to the initial map. The new method is illustrated on a simple example and then the results of the Kappa statistic and
K
Simulation are compared using the results of a land-use model. It is found that only
K
Simulation truly tests models in their capacity to explain land-use changes over time, and unlike Kappa it does not inflate results for simulations where little change takes place over time.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Dissolved fission product samples were analyzed using advanced radio-emission spectroscopy techniques using a proof-of-concept instrument. Reduction factors of 2–7 in the minimum detectable activity ...relative to traditional gamma counting were observed for trace fission products and actinides. A gamma-gamma coincidence detector was combined with a custom liquid scintillation counter to evaluate the benefits of alpha and beta coincident and anti-coincident analysis. The improvements observed in the detection sensitivity of fission products and actinides achieved by combining time-correlated radiation signatures is of value to applications such as nuclear physics, environmental monitoring, reactor releases, and nuclear forensics.
Landscape decisions are multi‐faceted. Framing landscape decision‐making as a governance process that requires a collective approach can encourage key stakeholders to come together to co‐inform a ...discussion about their priorities and what constitutes good governance, leading to more holistic landscape decisions.
In this paper, we recognise that a suite of complementary and multi‐dimensional approaches are in practice used to inform and evaluate land use decisions. We have called these approaches ‘lenses’ because they each provide a different perspective on the same problem. The four lenses are (i) power and market gain, (ii) ecosystem services, (iii) place‐based identity and (iv) ecocentric. Each brings a different set of evidence and viewpoints (narrative, qualitative and experiential, as well as quantitative metrics such as monetary) to the decision‐making process and can potentially reveal problems and solutions that others do not.
Considering all lenses together allows dialogue to take place which can reveal the true complexities of landscape decision‐making and can facilitate more effective and more holistic decisions. Employing the lenses requires governance structures that give equal weight to all lenses, enable dialogue and coexistence between top down and bottom‐up approaches, and permit adaptation to local and granular place‐specifics rather than developing “one‐size‐fits‐all” solutions.
We propose that formalising the process of balancing all the lenses requires public participation, and that a lens approach should be used to support landscape decisions alongside a checklist that facilitates transparency in the conversation, showing how all evidence has been considered and critically assessed.
Read the free Plain Language Summary for this article on the Journal blog.
Read the free Plain Language Summary for this article on the Journal blog.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
The quantitative characterization of surface structures captured in scanning electron microscopy (SEM) images has proven to be effective for discerning provenance of an unknown nuclear material. ...Recently, many works have taken advantage of the powerful performance of convolutional neural networks (CNNs) to provide faster and more consistent characterization of surface structures. However, one inherent limitation of CNNs is their degradation in performance when encountering discrepancy between training and test datasets, which limits their use widely. The common discrepancy in an SEM image dataset occurs at low-level image information due to user-bias in selecting acquisition parameters and microscopes from different manufacturers. Therefore, in this study, we present a domain adaptation framework to improve robustness of CNNs against the discrepancy in low-level image information. Furthermore, our proposed approach makes use of only unlabeled test samples to adapt a pretrained model, which is more suitable for nuclear forensics application for which obtaining both training and test datasets simultaneously is a challenge due to data sensitivity. Through extensive experiments, we demonstrate that our proposed approach effectively improves the performance of a model by at least 18% when encountering domain discrepancy, and can be deployed in many CNN architectures.
•Fuzzy Kappa Simulation assesses the predictive accuracy of land use models.•It evaluates model results in terms of land use transitions, instead of land use classes.•At the same time, Fuzzy Kappa ...Simulation is sensitive to geographical nuance.•These properties overcome major limitations of existing map-comparison methods.
The predictive accuracy of land use models is frequently assessed by comparing two data sets: the simulated land use map and the observed land use map at the end of the simulation period. A common statistic for this is Kappa, which expresses the agreement between two categorical maps, corrected for the agreement as can be expected by chance. This chance agreement is based on a stochastic model of random allocation given the distribution of class sizes. Two existing statistics extend Kappa to make it more appropriate for the assessment of land use models: Fuzzy Kappa uses fuzzy set theory to include degrees of similarity, which adds geographical nuance because it distinguishes between small and large disagreement in position and in land use classes. Kappa Simulation, on the other hand, addresses the stochastic model that underlies the expected agreement: when a model starts from an initial land use map and subsequently makes changes to it, a stochastic model of random allocation given the distribution of class sizes has little relevance. The expected accuracy in Kappa Simulation is therefore based on transition probabilities relative to the initial map. This paper presents Fuzzy Kappa Simulation, a statistic that combines the geographical nuance of Fuzzy Kappa with the stochastic model of Kappa Simulation. This new statistic is demonstrated on a case study example and results are compared with other variations of Kappa. The comparison confirms that Fuzzy Kappa Simulation is the only statistic to evaluate models in terms of land use transitions, while also being sensitive to geographical nuance.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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