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Spatial modelling of knowledge
Published in Ramesh S. V. Teegavarapu, Elpida Kolokytha, Carlos de Oliveira Galvão, Climate Change-Sensitive Water Resources Management, 2020
Iana A. A. Rufino, Carlos de Oliveira Galvão, Vajapeyam Srinivasan
The spatial variability identified in all data makes it possible to convert the data into thematic layers. Map algebra models represent all decision-making processes, in addition to multicriteria decision analysis (MCDA) equations, weightage allocations, and spatial inferences using Boolean Logic, Fuzzy Sets, and site-suitability analysis.
Geographical Information System for Land and Water Development in Lowland Areas
Published in Fransiscus Xaverius Suryadi, Soil and Water Management Strategies for Tidal Lowlands in Indonesia, 2020
Map algebra refers to the use of image files as variables in normal arithmetic operations. This is also an advantage of a GIS where full algebraic operations on a set of images are possible. In this case the main modules are: - overlay’thematic mapping’ consists of overlaying maps of different attributes but corresponding to a same area of interest (Fabbri, 1991). Overlaying of maps will result in the creation of new spatial entities which undertake mathematical operations between two images files. The values assigned to a certain location are computed as a function in one or more of the existing maps. By overlaying, a new data set containing new areas is formed. Three types of overlay operations are available i.e. arithmetical, logical and conditional. This capability has perhaps the greatest attraction of GIS and the most important one is in defining procedures, rules or algorithms which lead to a meaningful combination of several different spatial data;- scalarcan be used to mathematically change every pixel in an image file by a constant (for example to change from feet to meters);- reclassification and transformationare used to reassignment and modify thematic values of every pixel in an existing image (for example to take the inverse for the whole image or to transform all pixel values into logarithmic values). The process involves looking at the attribute for a single data layer and assigning an additional attribute. Typical examples of reclassification and transformation are classifying an elevation map with a certain interval (for example every 1 m) and reclassifying a soil map;- cross-table calculationwhich performs ’condition-implied action’, in case combination plays an important role, this module will often be used in a modelling with GIS.
Spatial relationships-based data inconsistency detection for raster land cover
Published in Journal of Spatial Science, 2023
Shun Kang, Shu Peng, Shanshan Qu
According to the prejudgement rules above, in single-period land cover update, we extracted the target land cover object Ou with a type A as the foreground, and the rest of the land cover as background BG. Through dilation operator ® and map algebra ⊕, the relational violation can be decided. If the rule is that land cover object Ou with a land cover type A disjoint with land cover object Pu with a land cover type B, namely is_a(Ou,A)∧is_a(Pu,B)∧fre(disjoint(Ou,Pu)∉CIA-B)21D2;is_a(disjoint(Ou,Pu),ab_asso) (p), this means Pu should exist around Ou. If not, then it is a relational violation, as expressed in Equation (11), and the location of object Ou, as well as its geometry gu and type tu, labelled by a point, is stored in a shapefile id_u.
Mapping of the cost of atmospheric corrosion of zinc and galvanised steel due to the effect of atmospheric pollution in the Mexico City Metropolitan area
Published in Corrosion Engineering, Science and Technology, 2022
J. O. Castillo-Miranda, F. J. Rodríguez-Gómez
The layers of sulfur dioxide (SO2), hydronium ion concentration [H+], temperature (T), precipitation (PP), relative humidity (RH), and surface recession for zinc are reported in Figures 2–7, respectively. They are used for the construction of the maintenance interval layer in contaminated areas (Lp) (Figure 8). Likewise, the maintenance interval in clean areas (Lc) is always a reference point that should be used since corrosion takes place even in the absence of contaminants. This antecedent scenario is taken as the ideal situation that could occur if the SO2 concentration is reduced to 1 μg/m3 and the pH is increased to 7 in all areas [44]. These SO2 and pH values combined with the layers of temperature (T), precipitation (PP), relative humidity (RH), and surface recession for zinc reported in Figures 4–7, respectively; They are used for the construction of the maintenance interval layer in clean areas (Figure 9). In the same way, as mentioned above, the map algebra operation applied Equation (7) to obtain the maintenance interval layers in contaminated and clean areas.
Water shortage risk mapping: a GIS-MCDA approach for a medium-sized city in the Brazilian semi-arid region
Published in Urban Water Journal, 2020
Maria José de Sousa Cordão, Iana Alexandra Alves Rufino, Priscila Barros Ramalho Alves, Mauro Normando Macêdo Barros Filho
The group of stakeholders agreed to a set of criteria. During the meetings and interviews with stakeholders, it was agreed to apply seven qualitative and quantitative criteria in the GIS-based MCDA: Population (C1), Topography (C2), Distance to the water reservoirs (C3), Distance to Pumping Station (C4), Proximity to the main pipelines (C5), Households supplied by the UWSS (C6), and Monthly Income (C7). All data (even non-spatial) were turned on layers’ grids (driving factors or criteria) with cells of 5 × 5 meters (spatial resolution). The GIS-MCDA environment and tools of ArcGIS 10.2 supported the modelling, map algebra, and the MCDA functions. Table 1 describes each criterion and its boundary conditions, as well as the referred literature, to explain the criteria. Figure 4 shows a general view of the spatial modelling and the MCDA towards a water shortage mapping methodology. The criteria selection, the standardisation process, the weightage allocation, and the criteria combination are represented in the conceptual model and described in details in the next sections of this paper.