Study on Spatial Pattern of Rural Settlements in Wuling Mountainous Area Based on GIS

2018 ◽  
Vol 102 (4) ◽  
pp. 2745-2757
Author(s):  
Nanjie Li ◽  
Shuhui Jiang
2020 ◽  
Vol 5 (3) ◽  
pp. 479-488
Author(s):  
Yohanes Basuki Dwisusanto ◽  
Hermawan

Spatial patterns are formed based on local wisdom and Karangtengah Hamlet settlement which is located in the cold climate of the mountainous area in Banjarnegara Regency, Central Java has been discovered to have a uniqueness in using the fireplace as the center of its activities. Therefore, this research was conducted to uncover the basic concept of fireplace-based house spatial pattern in this settlement using a qualitative method which involves combining interview, observation, and documentation. The process also involved using 33 houses as the case study with the criterion for selection being the active use of the fireplace. The results showed the placement of fireplace in these houses was influenced by the kinship system and the purpose was to have spatial patterns designed to reduce migration from these settlements to cities.


2021 ◽  
Vol 36 (3) ◽  
pp. 659
Author(s):  
Yan-bo QU ◽  
Min LIU ◽  
Wei-ya ZHU ◽  
Ling-yun ZHAN ◽  
Zong-li PING

Geoderma ◽  
2020 ◽  
Vol 360 ◽  
pp. 114016 ◽  
Author(s):  
Xiaoming Lai ◽  
Qing Zhu ◽  
Zhiwen Zhou ◽  
Kaihua Liao ◽  
Ligang Lv

2020 ◽  
Vol 12 (5) ◽  
pp. 1818 ◽  
Author(s):  
Guanglian Luo ◽  
Bin Wang ◽  
Dongqi Luo ◽  
Chaofu Wei

The rural settlements in poverty-stricken mountainous areas are the "living fossils" of an economic society with the characteristics of spatial dispersion and are slowly changing. Spatial agglomeration is the development direction of rural settlements. In-depth exploration of the spatial agglomeration characteristics and influencing factors of rural settlements in poverty-stricken mountainous areas is a way to provide a basis for rural settlement restructuring. We selected Pengshui County, a national poverty-stricken county in the southwestern mountainous area of China, as the research area. Spatial buffer and kernel density analysis were used to analyze the agglomeration characteristics of rural settlements and influencing factors. The results show that: (1) The rural settlements are small in scale and the space is evenly dispersed. 55.63% of the rural settlements’ sizes are less than 1000 m2, 84.15% of the rural settlements’ sizes are less than 2500 m2, and 92.81% of the rural settlements are within 200 m. (2) The elevation and slope of topographic factors have a significant agglomeration effect on rural settlements. However, the slope direction has no agglomeration effect. 85.41% of rural settlements (52.75% of rural settlements are gathered between 400 and 800 m above sea level) are gathered at an altitude of 1000 m or less, and 77.59% of rural settlements are gathered with a slope of 6~25°. Additionally, there are few rural settlements with a slope of 0~2°. Moreover, the distribution of residential areas has no agglomeration effect on rural settlements. (3) The cultivated land exerts the most significant effect on rural settlements followed by roads and water sources, while the role of urban land is weak. 99.48% of rural settlements are concentrated in the 100 m area of cultivated land. Therefore, in the poverty-stricken mountainous areas in the southwestern mountainous areas of China, convenient farming is the primary condition for production and living. Rural settlements are highly correlated with cultivated land. Rural settlements are scattered and concentrated with the scattered cultivated land. The rural settlements were leaded by the distribution of cultivated land. Less high-quality cultivated land with less slope were occupied or not by rural residential areas’ people.


2019 ◽  
Vol 8 (5) ◽  
pp. 222 ◽  
Author(s):  
Beata Calka ◽  
Elzbieta Bielecka

The issue of population dataset reliability is of particular importance when it comes to broadening the understanding of spatial structure, pattern and configuration of humans’ geographical location. The aim of the paper was to estimate the reliability of LandScan based on the official Polish Population Grid. The adopted methodology was based on the change detection approach, spatial pattern and continuity analysis, as well as statistical analysis at the grid-cell level. Our results show that the LandScan data can estimate the Polish population very well. The number of grid cells with equal people counts in both datasets amounts to 10.5%. The most and highly reliable data cover 72% of the country territory, while less reliable ones cover only 4.3%. The LandScan algorithm tends to underestimate people counts, with a total value of 79,735 people (0.21%). The highest underestimation was noticed in densely populated areas as well as in the transition areas between urban and rural, while overestimation was observed in moderately populated regions, along main roads and in city centres. The underestimation results mainly from the spatial pattern and size of Polish rural settlements, namely a big number of shadowed single households dispersed over agricultural areas and in the vicinity of forests. An excessive assessment of the number of people may be a consequence of the well-known blooming effect.


Los Romeros ◽  
2018 ◽  
pp. 13-20
Author(s):  
Walter Aaron Clark

The Romero family was from the mountainous area north of the seaport of Málaga, in the province of the same name. This chapter surveys the origins and history of the city and traces the family’s beginnings as agricultural workers in the rural settlements of Jotrón, Totalán, and Moclinejo and its eventual movement to urban centers on the coast, especially Gibraltar, where they worked in the building trades.


2013 ◽  
Vol 23 (4) ◽  
pp. 482-491 ◽  
Author(s):  
Xiaodong Ma ◽  
Fangdao Qiu ◽  
Quanlin Li ◽  
Yongbin Shan ◽  
Yong Cao

2018 ◽  
Vol 228 ◽  
pp. 05001
Author(s):  
Qi Liu ◽  
Yiwei Zhang

Rural settlements of China are in the era of rapid information development, experiencing revolutionary changes and cultural breakthroughs. This article takes the main rural settlements in Diqing as examples and uses GIS technology as the main method, analyses spatial distribution and assembling characteristics of rural settlements. Based on this, the article extracts the spatial assembling pattern of Diqing rural settlements. Take the topography, rivers, roads and other factors, this article analyzes the causes of the spatial distribution pattern of contemporary rural settlements. The article argues that it has a great theoretical and practical significance to study the spatial pattern of rural settlements, and points out the necessity of using modern GIS technology in the rural settlement research. This method cannot be only maximum the precise analytical ability of contemporary traditional rural settlement space, but also better serve the adjustment, control and optimization design of contemporary settlements.


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