Landsat-based assessment of the quantitative and qualitative dynamics of the pasture areas in rural settlements in the Cerrado biome, Brazil

Gosch, Marcelo Scolari; Parente, Leandro; Santos, Claudinei Oliveira dos; Mesquita, Vinícius Vieira; Ferreira, Laerte Guimarães

doi:10.1016/j.apgeog.2021.102585

Cited by 10 publications

(10 citation statements)

References 26 publications

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“…Because of the obvious economic advantages of township centers, they have a "gravitational" effect on neighboring rural settlements and can attract manpower, material, financial resources, and so forth from surrounding areas. There is a fact that, the closer to the township center, the larger the size and the greater the number of settlements, which is consistent with the findings of Marcelo Scolari Gosch et al [59].…”

Section: Analysis Of the Influence Of The Spatial Patternsupporting

confidence: 87%

“…The distance from major roads had the greatest impact. This is because the road traffic infrastructure serves as a spatial material carrier as well as a link between regions, between cities, and between cities and villages [59]. Transportation development has promoted the expansion of rural settlement space and changed the external form of the countryside.…”

Section: Analysis Of the Influence Of The Spatial Patternmentioning

confidence: 99%

“…In addition, there is a need to enhance infrastructure and encourage high-quality rural development. To achieve rural revitalization in southern Shaanxi, local decision-makers should rely on a variety of policies to improve the construction of urban and rural road networks from gathering centers for rural residential areas and encourage residents with poor living conditions to relocate to areas with relatively better environments [59], in order to achieve high-quality rural development in southern Shaanxi.…”

Section: Implications For Rural Settlementsmentioning

confidence: 99%

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Spatial Pattern and Influencing Factors of Rural Settlements in Qinba Mountains, Shaanxi Province, China

et al. 2022

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Spatial patterns and the influencing determinants of rural settlements are the most important indicators for understanding the constituent structure of rural regional systems. However, there is little knowledge addressing the characteristics from the settlement perspective by realizing the spatial reconstruction and sustainable development of rural settlements. Therefore, in this study, we analyzed the geographical, size, and morphological properties of rural settlement patterns in the Qinba Mountains in southern Shaanxi Province, China, using rural settlement and remote sensing data through spatial measurement index, gradient transects, demographic-economic index, and geodetector analysis. The results show the following: (1) Overall, rural settlements have spatial characteristics of “high-density multi-core clusters (0.8–1.6/km2) and low-density broadly scattered (<0.08/km2)”. There is a significant positive correlation between the scale of rural settlement density and the characteristics of high-value agglomeration. (2) The spatial disparities of morphological traits of settlement shapes are significant. Furthermore, 1840 NP/piece of plain basin landform types provide high-value areas for each settlement feature value, and locations with moderate slopes are best for settlement dispersal. Moreover, rivers, roads, and distance from township centers are all examples of beneficial directivity. There is consistency between the spatial differentiation of rural settlement areas per capita and the distribution of settlement scale. Conversely, the settlement density is inconsistent with the agricultural production value density’s spatial distribution features. (3) The impact of geographical factors on the diversification of settlement characteristics has significant spatial differences. Moreover, natural ecological characteristics such as elevation and landform and the distribution of cultivated land strongly influence the spatial pattern of the study region. Finally, the study findings can be beneficial for land and space planning and rural governments to develop sustainable rural settlements.

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Section: Analysis Of the Influence Of The Spatial Patternsupporting

confidence: 87%

Section: Analysis Of the Influence Of The Spatial Patternmentioning

confidence: 99%

Section: Implications For Rural Settlementsmentioning

confidence: 99%

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Spatial Pattern and Influencing Factors of Rural Settlements in Qinba Mountains, Shaanxi Province, China

et al. 2022

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“…Identifying the changes in residential places requires relatively rich data support, while rural areas with sparse populations were often thought to be lacking this data. Recently, the application of machine learning methods to explore the growth of rural settlements is considered promising [20,21], and the open remote sensing data platform has been widely used [22].…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Changes and Influencing Factors of Rural Settlements in the Middle Reaches of the Yangtze River Region, 1990–2020

Yao,

2023

Land

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China has experienced rapid urbanization, causing dramatic changes to the patterns of urban and rural land use relationships. This paper analyzes the spatiotemporal characteristics of rural settlements in the middle reaches of the Yangtze River region (MRYRR) using remote sensing monitoring data from 1990 to 2020 and reveals the influencing factors of spatiotemporal changes. The research found that (1) the overall increase in the quantity of rural settlements in the MRYRR between 1990 and 2020 was 504.70 km2. The area of transfer of other land use types to rural settlement was 1382.57 km2, of which 78.55% came from arable land and 16.62% came from forests; the area of rural settlement transfer to other land use types was 867.24 km2, of which 66.27% was reclaimed as arable land and 8.48% was transferred into urban built-ups. Changes in different stages and regions are diversified. (2) The spatial layout of rural settlements showed no significant differences in the MRYRR between 1990 and 2020, with a cluster distribution of “five main nuclei and many secondary nuclei” and a spatial distribution of “gathering in the north and east, while scattered in the south and west”. (3) The level of fragmentation of rural settlements in the MRYRR has greatly decreased since 1990, with the average patch size expanding significantly. The patch complexity of rural settlements fluctuated moderately, but the connectivity between patches continued to increase, and their distribution became more clustered. (4) Social and economic factors, including rural electricity consumption, the output value of the primary industry, net income per rural resident, urbanization rate, and the effective irrigated area, most strongly impacted the changes in rural settlements in the MRYRR. The research can be utilized as a guide for reconstructing the pattern of rural land use to promote sustainable rural revitalization.

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“…Moreover, the research on RRL also presents different research scales, including mainly analyses of the overall evolution and driving mechanism of RRL at the macroscale, explorations of the structure, function, and spatial layout optimization of RRL, and the gradual transformation from the national and provincial macroscale to the shrinking of the county, town, and even village at the microscale Chirisa, 2021). In addition, the research methods on rural settlements are diverse, mainly involving multifactor comprehensive evaluation methods, spatial econometric analysis, spatial autocorrelation, geographic information systems, geographic detectors, and other methods and models, revealing the general or local characteristics of the research content of rural settlements (Yang et al, 2019a;Gosch et al, 2021;Kong et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

What Is the Impact of the Establishment of Natural Reserves on Rural Residential Land? An Empirical Study From Hunan Province, China

Tang

Jiang

et al. 2022

Front. Environ. Sci.

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The rural residential land (RRL) in natural reserves has been deeply transformed due to the disturbance constrained by ecological protection policies. Exploring the distribution characteristics and driving factors of RRL in natural reserves and non-natural reserves will help to promote the governance of land space and alleviate the contradiction of land use. Therefore, taking 122 county-level administrative regions in Hunan Province as an example, this article analyzes and compares the spatiotemporal distribution characteristics of RRL in natural reserves and non-natural reserves by using land use change dynamics, nuclear density analysis, the transfer matrix model, and the ordinary least-squares model and explores how the establishment of natural reserves affects the RRL area change. The results show that (1) the overall RRL area in Hunan changed from 171,162.27 hm2 in 2000 to 169,914.6 hm2 in 2020, with a total reduction of 1,247.67 hm2 and a decrease of 0.73%, and the distribution of the RRL area change presented a hot trend in the northeast and a cold trend in the southwest. (2) The occupation of urban construction land is the main reason for the reduction in RRL area, and the transformation of cultivated land and forestland into RRL is the main source of the increase in RRL area. (3) During 2000–2020, the overall RRL in natural reserves increased by 1,538.37 hm2, with an increase of 0.11%, while the overall RRL in non-natural reserves decreased by 2,786.04 hm2, with a decrease of 0.14%. (4) The establishment of natural reserves has a significant negative correlation with the area of RRL in 2000, 2010, and 2020, indicating that the establishment of natural reserves can limit the growth speed of the RRL area to a certain extent, but is affected by factors such as economic development and rural population growth; it cannot directly promote the overall reduction of RRL area. The results of this study can provide a reference for decision-making related to the spatial structure optimization of natural reserves and non-natural protected RRL and the coordinated development of urban and rural areas.

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Landsat-based assessment of the quantitative and qualitative dynamics of the pasture areas in rural settlements in the Cerrado biome, Brazil

Cited by 10 publications

References 26 publications

Spatial Pattern and Influencing Factors of Rural Settlements in Qinba Mountains, Shaanxi Province, China

Spatial Pattern and Influencing Factors of Rural Settlements in Qinba Mountains, Shaanxi Province, China

Spatiotemporal Changes and Influencing Factors of Rural Settlements in the Middle Reaches of the Yangtze River Region, 1990–2020

What Is the Impact of the Establishment of Natural Reserves on Rural Residential Land? An Empirical Study From Hunan Province, China

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