scholarly journals INVESTIGATION AND EVALUATION OF SPATIAL PATTERNS IN TABRIZ PARKS USING LANDSCAPE METRICS

2017 ◽  
Vol 10 (2) ◽  
pp. 263-269
Author(s):  
Ali Majnouni Toutakhane ◽  
Mojtaba Mofareh
Keyword(s):  
Spatial Distribution ◽  
Spatial Patterns ◽  
Landscape Metrics ◽  
Shape Index ◽  
Quantitative Information ◽  
Green Spaces ◽  
Quantitative Results ◽  
Patch Density ◽  
Distribution Composition ◽  
Nearest Neighborhood

Nowadays, the green spaces in cities and especially metropolises have adopted a variety of functions. In addition to improving the environmental conditions, they are suitable places for spending free times and mitigating nervous pressures of the machinery life based on their distribution and dispersion in the cities. In this research, in order to study the spatial distribution and composition of the parks and green spaces in Tabriz metropolis, the map of Parks prepared using the digital atlas of Tabriz parks and Arc Map and IDRISI softwares. Then, quantitative information of spatial patterns of Tabriz parks provided using Fragstats software and a selection of landscape metrics including: the area of class, patch density, percentage of landscape, average patch size, average patch area, largest patch index, landscape shape index, average Euclidean distance of the nearest neighborhood and average index of patch shape. Then the spatial distribution, composition, extent and continuity of the parks was evaluated. Overall, only 8.5 percent of the landscape is assigned to the parks, and they are studied in three classes of neighborhood, district and regional parks. Neighborhood parks and green spaces have a better spatial distribution pattern compared to the other classes and the studied metrics showed better results for this class. In contrast, the quantitative results of the metrics calculated for regional parks, showed the most unfavorable spatial status for this class of parks among the three classes studied in Tabriz city.

scholarly journals INVESTIGATION AND EVALUATION OF SPATIAL PATTERNS IN TABRIZ PARKS USING LANDSCAPE METRICS

2017 ◽  
Vol 10 (2) ◽  
pp. 263-269 ◽  
Author(s):  
Ali Majnouni Toutakhane ◽  
Mojtaba Mofareh
Keyword(s):  
Spatial Distribution ◽  
Spatial Patterns ◽  
Landscape Metrics ◽  
Shape Index ◽  
Quantitative Information ◽  
Green Spaces ◽  
Quantitative Results ◽  
Patch Density ◽  
Distribution Composition ◽  
Nearest Neighborhood

Nowadays, the green spaces in cities and especially metropolises have adopted a variety of functions. In addition to improving the environmental conditions, they are suitable places for spending free times and mitigating nervous pressures of the machinery life based on their distribution and dispersion in the cities. In this research, in order to study the spatial distribution and composition of the parks and green spaces in Tabriz metropolis, the map of Parks prepared using the digital atlas of Tabriz parks and Arc Map and IDRISI softwares. Then, quantitative information of spatial patterns of Tabriz parks provided using Fragstats software and a selection of landscape metrics including: the area of class, patch density, percentage of landscape, average patch size, average patch area, largest patch index, landscape shape index, average Euclidean distance of the nearest neighborhood and average index of patch shape. Then the spatial distribution, composition, extent and continuity of the parks was evaluated. Overall, only 8.5 percent of the landscape is assigned to the parks, and they are studied in three classes of neighborhood, district and regional parks. Neighborhood parks and green spaces have a better spatial distribution pattern compared to the other classes and the studied metrics showed better results for this class. In contrast, the quantitative results of the metrics calculated for regional parks, showed the most unfavorable spatial status for this class of parks among the three classes studied in Tabriz city.

scholarly journals Quantifying how urban landscape heterogeneity affects land surface temperature: A comparison of discrete and continuous approaches

2021 ◽  
Author(s):  
ehsan Rahimi ◽  
Shahindokht Barghjelveh ◽  
Pinliang Dong
Keyword(s):  
Surface Temperature ◽  
Spatial Patterns ◽  
Land Surface Temperature ◽  
Landscape Metrics ◽  
Land Surface ◽  
Urban Landscape ◽  
Landscape Heterogeneity ◽  
Alternative Measures ◽  
Heterogeneity Effects ◽  
Patch Density

Abstract The present study examines the efficiency of discrete and continuous approaches to measuring urban heterogeneity effects on land surface temperature (LST). In the discrete approach, landscape metrics have been widely applied to quantifying the relationship between land surface temperature and urban spatial patterns and have received acceptable verification from landscape ecologists but some studies have shown their inaccurate results. The objective of the study is to compare landscape metrics and alternative approaches to measuring urban heterogeneity effects on LST. We compared landscape metrics results with nine texture-based measures, and two local spatial autocorrelation indices (local Moran’s I and Gi statistics) applied to NDVI and BAI indices as a proxy of the spatial patterns of Tehran vegetation and built-up classes. The statistical results showed that urban landscape heterogeneity had significant impacts on the LST variations, and there was a compatibility between landscape metrics and alternative measures results. Overall results showed that the less-fragmented, the more complex, larger, and the higher number of patches, the lower LST. The most significant relationship was between patch density (PD) and LST (r= -0.71). Higher values of PD have mostly been interpreted to show higher fragmentation, but other landscape metrics and alternative measures declined this conclusion. Our study demonstrated that PD was not a reliable metric and presented no information about the spatial distribution of landscape elements. This study confirms alternative measures for overcoming landscape metrics shortcomings in estimating the effects of landscape heterogeneity on LST variations and gives land managers and urban planners new insights into the urban design.

scholarly journals Relevance of the Cell Neighborhood Size in Landscape Metrics Evaluation and Free or Open Source Software Implementations

2019 ◽  
Vol 8 (12) ◽  
pp. 586
Author(s):  
Paolo Zatelli ◽  
Stefano Gobbi ◽  
Clara Tattoni ◽  
Maria Giulia Cantiani ◽  
Nicola La Porta ◽  
...  
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Landscape Metrics ◽  
Shape Index ◽  
Edge Density ◽  
Patch Area ◽  
Aggregation Index ◽  
Use Values ◽  
Software Implementations ◽  
Patch Density

Landscape metrics constitute one of the main tools for the study of the changes of the landscape and of the ecological structure of a region. The most popular software for landscape metrics evaluation is FRAGSTATS, which is free to use but does not have free or open source software (FOSS). Therefore, FOSS implementations, such as QGIS’s LecoS plugin and GRASS’ r.li modules suite, were developed. While metrics are defined in the same way, the “cell neighborhood” parameter, specifying the configuration of the moving window used for the analysis, is managed differently: FRAGSTATS can use values of 4 or 8 (8 is default), LecoS uses 8 and r.li 4. Tests were performed to evaluate the landscape metrics variability depending on the “cell neighborhood” values: some metrics, such as “edge density” and “landscape shape index”, do not change, other, for example “patch number”, “patch density”, and “mean patch area”, vary up to 100% for real maps and 500% for maps built to highlight this variation. A review of the scientific literature was carried out to check how often the value of the “cell neighborhood” parameter is explicitly declared. A method based on the “aggregation index” is proposed to estimate the effect of the uncertainty on the “cell neighborhood” parameter on landscape metrics for different maps.

scholarly journals Urban Green Space Fragmentation and Urbanization: A Spatiotemporal Perspective

Forests ◽  
2019 ◽  
Vol 10 (4) ◽  
pp. 333 ◽  
Author(s):  
Fangzheng Li ◽  
Wei Zheng ◽  
Yu Wang ◽  
Junhui Liang ◽  
Shuang Xie ◽  
...  
Keyword(s):  
Spatial Patterns ◽  
Shape Index ◽  
Green Spaces ◽  
Rapid Urbanization ◽  
Urban Green ◽  
Urban Green Spaces ◽  
Geographically Weighted Regression Model ◽  
Nighttime Light Data ◽  
Green Areas ◽  
High Level

Urbanization leads to the occupation of green areas, directly contributing to a high level of fragmentation of urban green spaces, which, in turn, results in numerous socioeconomic and environmental problems. Consequently, an understanding of the relationships between patterns of urban green spaces and urbanization processes is essential. Although previous quantitative studies have examined this relationship, they have not included an exploration of spatial heterogeneities in the effects of urbanization on the spatial patterns of urban green areas. We therefore applied a spatiotemporal perspective to examine the above relationship, while considering the wider planning context. First, we quantified the extent of fragmentation of urban green spaces using landscape metrics comprising the largest patch index (LPI) and landscape shape index (LSI). Next, using the calculated spatial metrics and nighttime light data (NTL) for central Beijing for the period 1992–2016, we applied a geographically weighted regression model to assess variations in the spatiotemporal effects of urbanization on the fragmentation of urban green spaces. The results showed that urbanization initially occurred mainly in the northern parts of Beijing, whereas urbanization of southern urban fringe areas occurred after 2008. The reduction in green spaces along with increasing fragmentation and complex spatial patterns are indicative of issues relating to Beijing’s rapid urbanization and planning policies. This study contributes to an understanding of how urbanization influences fragmentation of urban green spaces and offers insights for the planning of urban green spaces from the perspective of promoting sustainability.

Spatial Patterns of Urban Innovation and Their Evolution from Perspectives of Capacity and Structure: Taking Shenzhen as an Example

2021 ◽  
Vol 11 (1) ◽  
pp. 7
Author(s):  
Erjie Hu ◽  
Di Hu ◽  
Handong He
Keyword(s):  
Spatial Distribution ◽  
Spatial Pattern ◽  
Distribution Pattern ◽  
Spatial Patterns ◽  
Spillover Effect ◽  
Tertiary Industry ◽  
Innovation Capacity ◽  
Structure Index ◽  
Secondary Industry ◽  
Spatial Spillover Effect

Innovation is a key factor for a country’s overall national strength and core competitiveness. The spatial pattern of innovation reflects the regional differences of innovation development, which can provide guidance for the regional allocation of innovation resources. Most studies on the spatial pattern of innovation are at urban and above spatial scale, but studies at urban internal scale are insufficient. The precision and index of the spatial pattern of innovation in the city needs to be improved. This study proposes to divide spatial units based on geographic coordinates of patents, designs the innovation capability and innovation structure index of a spatial unit and their calculation methods, and then reveals the spatial patterns of innovation and their evolutionary characteristics in Shenzhen during 2000–2018. The results show that: (1) The pattern of innovation capacity of secondary industry exhibited a pronounced spatial spillover effect with a positive spatial correlation. The innovation capacity and innovation structure index of the secondary industry evolved in a similar manner; i.e., they gradually extended from the southwest area to the north over time, forming a tree-like distribution pattern with the central part of the southwest area as the “root” and the northwest and northeast areas as the “canopy”. (2) The pattern of innovation capacity of tertiary industry also had a significant spatial spillover effect with a positive spatial correlation. There were differences between the evolutions of innovation capacity and innovation structure index of tertiary industry. Specifically, its innovation capacity presented a triangular spatial distribution pattern with three groups in the central and eastern parts of the southwest area and the south-eastern part of the northwest area as the vertices, while its innovative structure showed a radial spatial distribution pattern with the southwestern part of the southwest area as the source and a gradually sparse distribution toward the northeast. (3) There were differences between the evolution modes of secondary and tertiary industries. Areas with high innovation capacity in the secondary industry tended to be more balanced, while areas with high innovation capacity in the tertiary industry did not necessarily have a balanced innovation structure. Through the method designed in this paper, the spatial pattern of urban innovation can be more precise and comprehensive revealed, and provide useful references for the development of urban innovation.

scholarly journals Amplification and Suppression of Distinct Brain-wide Activity Patterns by Catecholamines

2018 ◽  
Author(s):  
RL van den Brink ◽  
S Nieuwenhuis ◽  
TH Donner
Keyword(s):  
Spatial Distribution ◽  
Human Brain ◽  
Spatial Patterns ◽  
Large Scale ◽  
Network Dynamics ◽  
Brain Network ◽  
Heterogeneous Distribution ◽  
Neurotransmitter Systems ◽  
The Brain ◽  
Catecholamine Levels

ABSTRACTThe widely projecting catecholaminergic (norepinephrine and dopamine) neurotransmitter systems profoundly shape the state of neuronal networks in the forebrain. Current models posit that the effects of catecholaminergic modulation on network dynamics are homogenous across the brain. However, the brain is equipped with a variety of catecholamine receptors with distinct functional effects and heterogeneous density across brain regions. Consequently, catecholaminergic effects on brain-wide network dynamics might be more spatially specific than assumed. We tested this idea through the analysis of functional magnetic resonance imaging (fMRI) measurements performed in humans (19 females, 5 males) at ‘rest’ under pharmacological (atomoxetine-induced) elevation of catecholamine levels. We used a linear decomposition technique to identify spatial patterns of correlated fMRI signal fluctuations that were either increased or decreased by atomoxetine. This yielded two distinct spatial patterns, each expressing reliable and specific drug effects. The spatial structure of both fluctuation patterns resembled the spatial distribution of the expression of catecholamine receptor genes: α1 norepinephrine receptors (for the fluctuation pattern: placebo > atomoxetine), ‘D2-like’ dopamine receptors (pattern: atomoxetine > placebo), and β norepinephrine receptors (for both patterns, with correlations of opposite sign). We conclude that catecholaminergic effects on the forebrain are spatially more structured than traditionally assumed and at least in part explained by the heterogeneous distribution of various catecholamine receptors. Our findings link catecholaminergic effects on large-scale brain networks to low-level characteristics of the underlying neurotransmitter systems. They also provide key constraints for the development of realistic models of neuromodulatory effects on large-scale brain network dynamics.SIGNIFICANCE STATEMENTThe catecholamines norepinephrine and dopamine are an important class of modulatory neurotransmitters. Because of the widespread and diffuse release of these neuromodulators, it has commonly been assumed that their effects on neural interactions are homogenous across the brain. Here, we present results from the human brain that challenge this view. We pharmacologically increased catecholamine levels and imaged the effects on the spontaneous covariations between brain-wide fMRI signals at ‘rest’. We identified two distinct spatial patterns of covariations: one that was amplified and another that was suppressed by catecholamines. Each pattern was associated with the heterogeneous spatial distribution of the expression of distinct catecholamine receptor genes. Our results provide novel insights into the catecholaminergic modulation of large-scale human brain dynamics.

scholarly journals Impacts of spatial mismatch on commuting time of urban residents in China

2014 ◽  
Vol 26 (3) ◽  
pp. 227-233 ◽  
Author(s):  
Danwen Bao ◽  
Tangyi Guo ◽  
Hongshan Xia
Keyword(s):  
Spatial Distribution ◽  
Spatial Patterns ◽  
Measurement Methods ◽  
Urban Residents ◽  
Spatial Mismatch ◽  
Chinese Cities ◽  
Job Accessibility ◽  
Nanjing City ◽  
Commuting Time ◽  
Job Opportunity

In much of studies on spatial mismatch between residential and employer locations, job accessibility has been measured. However, the apparent disadvantages of the traditional measurement methods on the studies of Chinese cities have been noted.  This paper proposed an optimized method for job accessibility measurement by introducing the weigh coefficient of job opportunity, which quantifies the degree of uneven distribution of job opportunity in the Chinese cities. Take Nanjing city for example, this new method was used to measure the spatial distribution of job opportunity, investigate the spatial patterns and analyze the influences of job accessibility on commuting behavior. The results show that the distribution of job accessibility in Nanjing exhibits the different spatial patterns and mechanisms compared with US cases.

Mining Spatial Patterns of Distribution of Uranium in Surface and Ground Waters in Ukraine

2017 ◽  
pp. 520-546
Author(s):  
Michael Govorov ◽  
Viktor Putrenko ◽  
Gennady Gienko
Keyword(s):  
Factor Analysis ◽  
Spatial Distribution ◽  
Spatial Patterns ◽  
Large Scale ◽  
Chemical Elements ◽  
Environmental Indicators ◽  
Local Factor ◽  
Correlation And Regression Analysis ◽  
Weighted Factor ◽  
Major Factors

A variety of geovisualization and spatial statistical methods can reveal spatial patterns in the distribution of chemical elements in surface and groundwater, and also identify major factors which define those patterns. This chapter describes a combination of modeling techniques to enhance understanding of large-scale spatial distribution of uranium in groundwater in Ukraine, by linking spatial patterns of several indicators and predictors. Factor, correlation, and regression analysis, including their spatial implementations, were used to describe the impacts of several environmental variables on spatial distribution of uranium. Local factor analysis (or Geographically Weighted Factor Analysis, GWFA) was proposed to identify major environmental factors which define the distribution of uranium, and to discover and map their spatial relationships. The study resulted in a series of maps to help visualize and explore the relationships between uranium and several environmental indicators.

scholarly journals Spaces of Islamophobia and spaces of inequality in Greater Paris

2020 ◽  
pp. 239965442094152
Author(s):  
Kawtar Najib
Keyword(s):  
Spatial Distribution ◽  
Spatial Analysis ◽  
Spatial Patterns ◽  
Quantitative Data ◽  
Statistical Data ◽  
Great Majority ◽  
Demographic Variables ◽  
Public Institutions ◽  
Terrorist Attacks ◽  
Population Census

This paper draws upon quantitative data collected from one of the principal associations fighting Islamophobia in France along with the population census, and provides a step forward in understanding the operation and distribution of Islamophobia. It presents a geography of Islamophobia in Paris based on statistical data, and aims to observe whether or not this geography corresponds or contrasts with geographies of inequality (such as those associated with gentrification, deprivation and marginalisation), by analysing the various spatial patterns stemming from the maps. This socio-spatial analysis of anti-Muslim discrimination is important in Paris because since the terrorist attacks in 2015, anti-Muslim sentiment has increased sharply. The mapping of Islamophobia and its association with the spatial distribution of different socioeconomic and demographic variables synthetized in a typological map display significant forms, relations and diversities within Paris. This cartographic analysis demonstrates that the geography of Islamophobia does not necessarily refer to spaces where ‘Muslims’ and the victims of Islamophobia live in great majority, and rather refers to more privileged and central areas such as Paris intra-muros. Victims mostly experience anti-Muslim incidents outside their everyday spaces away from their homes, such as public institutions and workplaces. Indeed, the findings raise the significance of the exact place where incidents occur as well as societal attitudes to these ‘hierarchical’ places where the perpetrator probably feels more comfortable in behaving in an antisocial and sometimes violent way.

Sign in / Sign up

Export Citation Format

Share Document