scholarly journals Structural analysis, measurement of a spatial distribution model and classification of the construction of urban areas based on the benefit from urban services: case study – five districts of Zahedan

2016 ◽  
Author(s):  
B. Darvish ◽  
R. Sarvar ◽  
F. Sh. Moghaddam
Keyword(s):  
Spatial Distribution ◽  
Structural Analysis ◽  
Urban Areas ◽  
Distribution Model ◽  
Urban Services ◽  
Analysis Measurement ◽  
Spatial Distribution Model

scholarly journals Assessment of Spatial Distribution Model of Urban-Social Vulnerability in Natural Hazards (A case study of Seven Municipality of Tehran)

2019 ◽  
Vol 6 (3) ◽  
pp. 49-70
Author(s):  
ABOLFAZL MESHKINI ◽  
ali mohammad mansourzadeh ◽  
zeynab shahrokhy far ◽  
شهربانو موسوی ◽  
◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Natural Hazards ◽  
Social Vulnerability ◽  
Distribution Model ◽  
Spatial Distribution Model

scholarly journals Classification of Landforms for Digital Soil Mapping in Urban Areas Using LiDAR Data Derived Terrain Attributes: A Case Study from Berlin, Germany

Land ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 319 ◽  
Author(s):  
Mohamed Ali Mohamed
Keyword(s):  
Urban Areas ◽  
Human Impacts ◽  
Soil Mapping ◽  
Fuzzy Classification ◽  
Small Scale ◽  
Ground Truth Data ◽  
Terrain Attributes ◽  
Lidar Dem

In this study, a knowledge-based fuzzy classification method was used to classify possible soil-landforms in urban areas based on analysis of morphometric parameters (terrain attributes) derived from digital elevation models (DEMs). A case study in the city area of Berlin was used to compare two different resolution DEMs in terms of their potential to find a specific relationship between landforms, soil types and the suitability of these DEMs for soil mapping. Almost all the topographic parameters were obtained from high-resolution light detection and ranging (LiDAR)-DEM (1 m) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER)-DEM (30 m), which were used as thresholds for the classification of landforms in the selected study area with a total area of about 39.40 km2. The accuracy of both classifications was evaluated by comparing ground point samples as ground truth data with the classification results. The LiDAR-DEM based classification has shown promising results for classification of landforms into geomorphological (sub)categories in urban areas. This is indicated by an acceptable overall accuracy of 93%. While the classification based on ASTER-DEM showed an accuracy of 70%. The coarser ASTER-DEM based classification requires additional and more detailed information directly related to soil-forming factors to extract geomorphological parameters. The importance of using LiDAR-DEM classification was particularly evident when classifying landforms that have narrow spatial extent such as embankments and channel banks or when determining the general accuracy of landform boundaries such as crests and flat lands. However, this LiDAR-DEM classification has shown that there are categories of landforms that received a large proportion of the misclassifications such as terraced land and steep embankments in other parts of the study area due to the increased distance from the major rivers and the complex nature of these landforms. In contrast, the results of the ASTER-DEM based classification have shown that the ASTER-DEM cannot deal with small-scale spatial variation of soil and landforms due to the increasing human impacts on landscapes in urban areas. The application of the approach used to extract terrain parameters from the LiDAR-DEM and their use in classification of landforms has shown that it can support soil surveys that require a lot of time and resources for traditional soil mapping.

Non-linear interactions of urban and freshwater systems: Exploring implications for sustainability and water planning and management

2020 ◽  
Author(s):  
Héctor Angarita ◽  
Vishal Mehta ◽  
Efraín Domínguez
Keyword(s):  
Spatial Distribution ◽  
Urban Areas ◽  
Human Population ◽  
Urban Population ◽  
Urban Systems ◽  
Resource Base ◽  
Freshwater Systems ◽  
Non Linear ◽  
Freshwater System

<p>Human population is progressing into a predominantly urban configuration. Currently, 3.5 billion people – 55% of the total human population – live in urban areas, with an increase to 6.68 billion (68%) projected by 2050. In this progressively more populated world, a central issue of sustainability assessments is understanding the role of cities as entities that, despite their comparatively small physical footprint (less than 0.5% of the global area) demand resources at regional and global scales.</p><p>Many of the resources that sustain urban population directly depend on the freshwater system: from direct fluxes from/to the immediate environment of cities for water supply or waste elimination, to water-dependent activities like biomass (food, biofuels, fibers) and energy production. Urban and freshwater system interactions are subject to multiple sources of non-linearity. Factors like the patterns of size or spatial distribution and interconnection of groups of cities; or the nested and hierarchical character of freshwater systems, can vastly influence the amount of resources required to sustain and grow urban population; likewise, equivalent resource demands can be met through different management strategies that vary substantially in their cumulative pressure exerted on the freshwater system.</p><p>Here we explore the non-linear character of those interactions, to i. identify water management options to avoid, minimize or offset regional impacts of growing urban populations, and ii. explore long term implications of such non-linearities in sustained resource base of urban areas. We propose a framework integrating three elements: 1. properties of the size and spatial distribution of urban center sizes, 2. scaling regime of urban energy resource dependencies, and 3. scaling regime of associated physical and ecological impacts in freshwater systems.</p><p>An example of this approach is presented in a case study in the Magdalena River Basin – MRB (Colombia). The basin covers nearly one quarter of Colombia’s national territory and provides sustenance to 36 million people, with three quarters of basin inhabitants living in medium to large urban settlements of populations of 12 000 or more inhabitants and 50% concentrated in the 15 largest cities. The case study results indicate that freshwater-mediated resource dependencies of urban population are described by a linear or super-linear regime that indicates a lack of scale economies, however, freshwater systems’ capacity to assimilate those resource demands is characterized by a sublinear regime. As a result, current practices and technological approaches to couple freshwater and urban systems will not be able to withstand the resource demands of mid-term future population scenarios.  Our approach allows to quantify the projected gaps to achieve a sustained resource base for urban systems in MRB.</p>

scholarly journals Computing spatial distribution of tube and louvre luminaires efficiency from their description

2020 ◽  
Vol 22 (1) ◽  
pp. 12-27
Author(s):  
Jean-Marc DENIEL
Keyword(s):  
Spatial Distribution ◽  
In Situ Measurement ◽  
Distribution Model ◽  
Spatial Distributions ◽  
Experimental Range ◽  
Spatial Distribution Model ◽  
Measured Efficiency ◽  
Model Fits

Lighting computation requires photometry data that are not always available. Lacking photometry data limits lighting study to in situ measurement, luminaire measurement or use of similar luminaire photometry. This is not satisfactory, neither for convenience nor cost and accuracy reasons. Fitting the spatial distribution of luminaire efficiency to their description would allow lighting computations in this kind of situation. An efficiency spatial distribution model is proposed for grid and louvre tube luminaires, taking optic width, louvre between-axis and gloss as parameters. It is constructed over 12 measured efficiency spatial distributions and the corresponding luminaire descriptors. Even if optic and louvre gloss cannot be differentiated, this model fits to measurements and allows for computed irradiance close to experiments within −5% to +19%. In addition, luminaire descriptors can freely vary inside their experimental range and even be extrapolated.

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