scholarly journals Spatial-Temporal Analysis of Human Dynamics on Urban Land Use Patterns Using Social Media Data by Gender

2018 ◽  
Vol 7 (9) ◽  
pp. 358 ◽  
Author(s):  
Chengcheng Lei ◽  
An Zhang ◽  
Qingwen Qi ◽  
Huimin Su ◽  
Jianghao Wang
Keyword(s):  
Land Use ◽  
Urban Land Use ◽  
Moran’S I ◽  
Land Use Patterns ◽  
Moran's I ◽  
Residential Land ◽  
Human Dynamics ◽  
Use Patterns ◽  
Land Use Types ◽  
Olympic Village

The relationship between urban human dynamics and land use types has always been an important issue in the study of urban problems in China. This paper used location data from Sina Location Microblog (commonly known as Weibo) users to study the human dynamics of the spatial-temporal characteristics of gender differences in Beijing’s Olympic Village in June 2014. We applied mathematical statistics and Local Moran’s I to analyze the spatial-temporal distribution of Sina Microblog users in 100 m × 100 m grids and land use patterns. The female users outnumbered male users, and the sex ratio ( S R varied under different land use types at different times. Female users outnumbered male users regarding residential land and public green land, but male users outnumbered female users regarding workplace, especially on weekends, as the S R on weekends ( S R was 120.5) was greater than that on weekdays ( S R was 118.8). After a Local Moran’s I analysis, we found that High–High grids are primarily distributed across education and scientific research land and residential land; these grids and their surrounding grids have more female users than male users. Low–Low grids are mainly distributed across sports centers and workplaces on weekdays; these grids and their surrounding grids have fewer female users than male users. The average number of users on Saturday was the highest value and, on weekends, the number of female and male users both increased in commercial land, but male users were more active than female users ( S R was 110).

scholarly journals Variation in the Continuity of Land-Use Patterns through the First Millennium AD in Lowland Britain

2015 ◽  
Vol 11 (1) ◽  
pp. 135-154
Author(s):  
Stephen Rippon ◽  
Ralph Fyfe
Keyword(s):  
Land Use ◽  
Roman Empire ◽  
Causal Effect ◽  
Anglo Saxon ◽  
Land Use Patterns ◽  
Profound Change ◽  
Use Patterns ◽  
Land Use Types ◽  
First Millennium

AbstractThis paper explores the contribution that palaeoenvironmental evidence, and in particular palynology, is making to our understanding of landscape evolution in Britain during the 1st millenniumAD. This was a period of profound social and economic change including a series of invasions, some associated with a mass folk migration. Archaeologists and historians continue to debate the significance of these events, and palaeoenvironmental evidence is now starting to provide an additional perspective. Key to this has been obtaining pollen sequences, although there remains a need for more evidence from lowland areas, alongside higher resolution sampling and improved dating. It is suggested that although the 1st millenniumADsaw some significant long-term shifts in climate, these are unlikely to have had a significant causal effect on landscape change in lowland areas (both in areas with and without significant Anglo-Saxon immigration). The analysis of pollen data from across Britain shows very marked regional variations in the major land-use types (arable, woodland, improved pasture, and unimproved pasture) throughout the Roman and Early Medieval periods. While Britain ceasing to be part of the Roman empire appears to have led to a decline in the intensity of agriculture, it was the ‘long 8th c.’ (the later 7th to early 9th c.) that saw a more profound change, with a period of investment, innovation, and intensification, including an expansion in arable cultivation.

scholarly journals A comparison between soil loss evaluation index and the C-factor of RUSLE: a case study in the Loess Plateau of China

2012 ◽  
Vol 16 (8) ◽  
pp. 2739-2748 ◽  
Author(s):  
W. W. Zhao ◽  
B. J. Fu ◽  
L. D. Chen
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Soil Loss ◽  
Drainage Network ◽  
Land Use Patterns ◽  
Low Area ◽  
Use Patterns ◽  
High Area ◽  
Land Use Types

Abstract. Land use and land cover are most important in quantifying soil erosion. Based on the C-factor of the popular soil erosion model, Revised Universal Soil Loss Equation (RUSLE) and a scale-pattern-process theory in landscape ecology, we proposed a multi-scale soil loss evaluation index (SL) to evaluate the effects of land use patterns on soil erosion. We examined the advantages and shortcomings of SL for small watershed (SLsw) by comparing to the C-factor used in RUSLE. We used the Yanhe watershed located on China's Loess Plateau as a case study to demonstrate the utilities of SLsw. The SLsw calculation involves the delineations of the drainage network and sub-watershed boundaries, the calculations of soil loss horizontal distance index, the soil loss vertical distance index, slope steepness, rainfall-runoff erosivity, soil erodibility, and cover and management practice. We used several extensions within the geographic information system (GIS), and AVSWAT2000 hydrological model to derive all the required GIS layers. We compared the SLsw with the C-factor to identify spatial patterns to understand the causes for the differences. The SLsw values for the Yanhe watershed are in the range of 0.15 to 0.45, and there are 593 sub-watersheds with SLsw values that are lower than the C-factor values (LOW) and 227 sub-watersheds with SLsw values higher than the C-factor values (HIGH). The HIGH area have greater rainfall-runoff erosivity than LOW area for all land use types. The cultivated land is located on the steeper slope or is closer to the drainage network in the horizontal direction in HIGH area in comparison to LOW area. The results imply that SLsw can be used to identify the effect of land use distribution on soil loss, whereas the C-factor has less power to do it. Both HIGH and LOW areas have similar soil erodibility values for all land use types. The average vertical distances of forest land and sparse forest land to the drainage network are shorter in LOW area than that in HIGH area. Other land use types have shorter average vertical distances in HIGH area than that LOW area. SLsw has advantages over C-factor in its ability to specify the subwatersheds that require the land use patterns optimization by adjusting the locations of land uses to minimize soil loss.

scholarly journals Exploring the Spatial and Temporal Relationship between Air Quality and Urban Land-Use Patterns Based on an Integrated Method

2020 ◽  
Vol 12 (7) ◽  
pp. 2964 ◽  
Author(s):  
Chia-An Ku
Keyword(s):  
Land Use ◽  
Air Quality ◽  
Urban Areas ◽  
Temporal Relationship ◽  
Urban Land ◽  
Urban Land Use ◽  
Air Pollutant ◽  
Land Use Patterns ◽  
Use Patterns ◽  
Mitigation Planning

The deterioration of air quality in urban areas is often closely related to urbanization, as this has led to a significant increase in energy consumption and the massive emission of air pollutants, thereby exacerbating the current state of air pollution. However, the relationship between urban development and air quality is complex, thus making it difficult to be analyzed using traditional methods. In this paper, a framework integrating spatial analysis and statistical methods (based on 170 regression models) is developed to explore the spatial and temporal relationship between urban land use patterns and air quality, aiming to provide solid information for mitigation planning. The thresholds for the influence of urban patterns are examined using different buffer zones. In addition, the differences in the effects of various types of land use pattern on air quality were also explored. The results show that there were significant differences between 1999 and 2013 with regards to the correlations between land use patterns and air pollutant concentrations. Among all land uses, forest, water and built-up areas were proved to influence concentrations the most. It is suggested that the developed framework should be applied further in the real-world mitigation planning decision-making process

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