Solving the map overlay problem with a fuzzy approach

Verstraete, Jörg

doi:10.1007/s10584-014-1053-z

Cited by 10 publications

(4 citation statements)

References 14 publications

(12 reference statements)

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“…The rules in this context were quite intuitive and exhibited parallels with the way an expert reasons about the problem (Verstraete 2014). In addition, the system is better readable, which not only allows for a better understanding but also facilitates adding expert knowledge directly into the rule base.…”

Section: Spatial Disaggregation Using the Fuzzy Rule-based Approachmentioning

confidence: 96%

“…The authors in Bun et al (2018) apply this technique to improve the spatial resolution of a spatial inventory of GHG emission in Poland. In Verstraete (2014), the authors presented the concept of using a rule-based system for grid remapping. Their detailed algorithm to use proxy data to generate a fuzzy rule-based system that performs the spatial disaggregation is elaborated on in Verstraete (2016).…”

Section: Remapping Gridded Datamentioning

confidence: 99%

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Solving the general map overlay problem using a fuzzy inference system designed for spatial disaggregation

Verstraete

2018

Mitig Adapt Strateg Glob Change

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Identification of mitigation and adaptation strategies in any situation has to be a well informed decision. This decision not only has to be based on quantifiable data (e.g. amounts or concentrations of emissions), but it also needs to consider spatial aspects such as the source of emissions, the impact of policies on the population or the identification of responsible parties. As such, it is important that the decisions are based on accurate reports made by experts in the field. Many data are available to the experts, and combining this data tends to increase the inherently contained uncertainty. Novel operations that exhibit a lower increase of uncertainty can yield outcomes that contain less uncertainty, which subsequently improves the accuracy of the resulting reports. At the same time, the decisionmakers are confronted with different reports, and the comparison of the contained spatial aspects requires combining the data, which exhibits similar issues relating to uncertainty. With data usually represented in gridded structures, comparing them often requires a process called regridding: this is the process of mapping one grid onto a second grid, a process which increases spatial uncertainty. In this contribution, a novel regridding algorithm is presented. While mainly intended as a preprocessing tool for the experts, it is also applicable for supporting the comparison of gridded datasets as used by decision-makers. In the context of this article, a grid can be irregular, allowing the presented algorithm to also be used for remapping a grid onto, e.g. administrative borders or vice versa. The presented algorithm for regridding is a modification that is generally applicable on spatial disaggregation algorithms. It was developed in parallel with a novel method that uses artificial intelligence (in the form of fuzzy rule-based systems) to involve proxy data to obtain better results, and it will be demonstrated using this approach for spatial disaggregation. Mitig Adapt Strateg Glob Change to perform regridding using an algorithm designed for spatial disaggregation is detailed in this article and the performance of the combination with the artificial intelligent system for disaggregation is illustrated by means of an example.

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Section: Spatial Disaggregation Using the Fuzzy Rule-based Approachmentioning

confidence: 96%

Section: Remapping Gridded Datamentioning

confidence: 99%

Solving the general map overlay problem using a fuzzy inference system designed for spatial disaggregation

Verstraete

2018

Mitig Adapt Strateg Glob Change

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“…In a new proposed approach presented in [5], additional knowledge (e.g. in the case of a pollutant stemming from car emissions, this can be road traffic information) is used to estimate the underlying spatial distribution.…”

Section: Origin Of the Problemmentioning

confidence: 99%

Algorithm for simultaneous defuzzification under constraints: shifted mean-max

Verstraete¹

2015

Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and

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In this article, we present an algorithm for defuzzifying multiple fuzzy sets simultaneously, where the defuzzified values are bound by a constraint. The algorithm aims at maximizing the lowest membership grade of the defuzzified values in each fuzzy set, while satisfying the constraint. In the examples, MeanOfMax will be used as a starting point, while the constraint is that the sum of the defuzzified values has to match a given crisp value. The article describes the algorithm, experiments and evaluation of the outcome.

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“…These may also differ from the desired target resolution of the gridded emissions. When combined, the task is to determine which portion of the grid cell in one grid relates to the partly overlapping cell of the target grid (Verstraete 2014). These grids can differ in cell size, they can be displaced in any latitude and longitude direction, and they can even be rotated by a certain angle.…”

Section: Introductionmentioning

confidence: 99%

Development of a high-resolution spatial inventory of greenhouse gas emissions for Poland from stationary and mobile sources

Bun

Nahorski

Horabik-Pyzel

et al. 2018

Mitig Adapt Strateg Glob Change

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Greenhouse gas (GHG) inventories at national or provincial levels include the total emissions as well as the emissions for many categories of human activity, but there is a need for spatially explicit GHG emission inventories. Hence, the aim of this research was to outline a methodology for producing a high-resolution spatially explicit emission inventory, demonstrated for Poland. GHG emission sources were classified into point, line, and area types and then combined to calculate the total emissions. We created vector maps of all sources for all categories of economic activity covered by the IPCC guidelines, using official information about companies, the administrative maps, Corine Land Cover, and other available data. We created the algorithms for the disaggregation of these data to the level of elementary objects such as emission sources. The algorithms used depend on the categories of economic activity under investigation. We calculated the emissions of carbon, nitrogen sulfure and other GHG compounds (e.g., CO 2 , CH 4 , N 2 O, SO 2 , NMVOC) as well as total emissions in the CO 2 -equivalent. Gridded data were only created in the final stage to present the summarized emissions of very diverse sources from all categories. In our approach, information on the administrative assignment of corresponding emission sources is retained, which makes it possible to aggregate the final results to different administrative levels including municipalities, which is not possible using a traditional gridded emission approach. We demonstrate that any grid size can be chosen to match the aim of the spatial inventory, but not less than 100 m in this example, which corresponds to the coarsest resolution of the input datasets. We then considered the uncertainties in the statistical data, the calorific values, and the emission factors, with symmetric and asymmetric (lognormal) distributions. Using the Monte Carlo method, uncertainties, expressed using 95% confidence intervals, were estimated for high point-type emission sources, the provinces, and the subsectors. Such an approach is flexible, provided the data are available, and can be applied to other countries.

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Solving the map overlay problem with a fuzzy approach

Cited by 10 publications

References 14 publications

Solving the general map overlay problem using a fuzzy inference system designed for spatial disaggregation

Solving the general map overlay problem using a fuzzy inference system designed for spatial disaggregation

Algorithm for simultaneous defuzzification under constraints: shifted mean-max

Development of a high-resolution spatial inventory of greenhouse gas emissions for Poland from stationary and mobile sources

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