Research on Spatial Differentiation Characteristics of Rural Residential Areas Based on Analysis of Landscape Index Granularity Effects: A Case Study of Hanyuan County

DENGYunsi, LIUZhibin, FANGYingxuan, LIJun, PENGXinghong, WANGWeiwei, MUYu, XIAJianguo, GAOXuesong, YANGBo

Chin Agric Sci Bull ›› 2026, Vol. 42 ›› Issue (17) : 209-218.

PDF(3597 KB)
Home Journals Chinese Agricultural Science Bulletin
Chinese Agricultural Science Bulletin

Abbreviation (ISO4): Chin Agric Sci Bull      Editor in chief: Yulong YIN

About  /  Aim & scope  /  Editorial board  /  Indexed  /  Contact  / 
PDF(3597 KB)
Chin Agric Sci Bull ›› 2026, Vol. 42 ›› Issue (17) : 209-218. DOI: 10.11924/j.issn.1000-6850.casb2026-0198

Research on Spatial Differentiation Characteristics of Rural Residential Areas Based on Analysis of Landscape Index Granularity Effects: A Case Study of Hanyuan County

Author information +
History +

Abstract

This study aims to provide references for rural planning, spatial layout optimization and land use in Hanyuan County. By analyzing the granularity effect of different granularity landscape indices, and based on the determination of the optimal granularity, combined with landscape pattern and spatial analysis methods, the spatial differentiation characteristics of rural settlements in Hanyuan County were studied. The results showed: (1) the appropriate granularity range for the spatial differentiation characteristics of rural settlements in Hanyuan County is 50-70 m, and the optimal spatial granularity is 60m. (2) The distribution of rural settlements in Hanyuan County is in a northwest-southeast direction. The weighted center of the rural settlement patches is located within Tangjia Town, indicating that this area is the center of gravity of the patch area distribution of rural settlements. And there is a clustering distribution phenomenon in the central area of rural settlements. (3) The high-density areas of rural settlements in Hanyuan County are concentrated in Yidong Town, Jiuxiang Town, Tangjia Town, Fulin Town, Fuquan Town, Anle Town and Dashu Town, showing a feature of settlement clustering along the river. (4) Rural settlements in Hanyuan County show a high degree of aggregation. Only Yidong Town, Jiuxiang Town, Dashu Town and Tangjia Town have relatively high separation indices, which are 714.35, 700.02, 451.33 and 350.19 respectively, and the dispersion degree of rural settlement patches in these areas is high. In summary, the spatial distribution of rural settlements in Hanyuan County shows the characteristics of ‘high aggregation, less dispersion’. The spatial distribution pattern is significantly affected by topography and geomorphology, with the dense distribution of low mountain valley areas and the sparse distribution of high mountain areas as the main characteristics. The research results provide valuable reference information for rural development planning and land use management in Hanyuan County.

Key words

rural settlements / granularity effect / spatial differentiation / landscape index

Cite this article

Download Citations
DENG Yunsi , LIU Zhibin , FANG Yingxuan , et al . Research on Spatial Differentiation Characteristics of Rural Residential Areas Based on Analysis of Landscape Index Granularity Effects: A Case Study of Hanyuan County[J]. Chinese Agricultural Science Bulletin. 2026, 42(17): 209-218 https://doi.org/10.11924/j.issn.1000-6850.casb2026-0198

References

[1]
俞斌传, 刘平辉, 吴佳. 基于最佳分析粒度的临川区土地利用景观格局梯度分析[J]. 江西农业学报, 2018, 30(5):110-116.
[2]
刘雪乾, 蔡海生, 张学玲, 等. 基于最佳分析粒度的农村居民点空间格局分析--以万年县为例[J]. 江西农业学报, 2021, 33(5):115-123.
[3]
王竹, 陈潇玮, 王珂. 时空维度下的湖州地区乡村景观格局演变分析[J]. 建筑与文化, 2017(1):172-174.
[4]
张磊, 李娟, 王鹏. 汾河流域景观破碎化时空演变特征[J]. 自然资源学报, 2019, 34(8):1692-1704.
[5]
刘世明, 叶欣, 董伦. 鹤岗市景观格局演变及最佳粒度选择[J]. 国土与自然资源研究, 2024(2):45-49.
[6]
任梅, 王志杰, 王志泰, 等. 黔中喀斯特山地城市景观格局指数粒度效应--以安顺市为例[J]. 贵州农业科学, 2022, 50(7):156-162.
[7]
叶欣, 董伦, 吕利娜, 等. 最佳粒度下的七台河市景观格局分析[J]. 安徽农业科学, 2021, 49(21):227-230.
[8]
谢奎, 程家骅, 张寒野. 县域养殖池塘景观格局指数的粒度效应--以江苏省兴化市为例[J]. 中国渔业科学, 2019, 26(3):513-522.
[9]
王晶晶, 孙玲, 王志明, 等. 基于GF-2影像的江苏耕地破碎地区景观格局空间粒度效应分析[J]. 江苏农业学报, 2020, 36(3):606-612.
[10]
谢萍. 山地型农村居民点空间分布特征及优化研究--以西南山区为例[J]. 山地学报, 2020, 38(4):589-596.
[11]
余忠原. 秦巴山区农村居民点空间分布特征及影响因素[J]. 干旱区资源与环境, 2021, 35(5):132-138.
[12]
王智颖. 扶余市农村居民点空间分异特征及驱动机制[J]. 地域研究与开发, 2019, 38(6):142-146.
[13]
刘立文. 山西省农村居民点空间分布格局及适宜性评价[J]. 中国土地科学, 2020, 34(8):89-97.
[14]
蒋明成, 杨琨, 夏建国. 基于GIS的汉源县农村人居环境适宜性评价[J]. 安徽农业科学, 2023, 51(15):57-62,67.
[15]
官钰, 李泽新, 杨琬铮. 乡村生活圈范围测度方法与优化策略探索--以雅安市汉源县为例[J]. 规划师, 2020, 36(24):21-27.
[16]
孔祥媛, 汪洋, 李帆, 等. 基于主导因素约束的典型西南山地乡村土地资源承载力研究[J]. 农业资源与环境学报, 2025, 42(1):22-32.
[17]
李函洋, 钟秋, 石锦安, 等. 汉源县观光果园景观格局变化及生态系统服务价值估算[J]. 四川农业大学学报, 2015, 33(3):325-331.
[18]
马黛玉, 夏建国, 周玥希, 等. 县域尺度下不同时序茶园景观格局指数的粒度效应分析[J]. 四川农业大学学报, 2021, 39(4):524-531.
[19]
徐涵秋, 何慧. 闽东南沿海地区景观指数粒度效应的高分辨率遥感分析[J]. 地理学报, 2016, 71(6):1011-1022.
[20]
左岍, 周勇, 李晴, 等. 基于最优尺度的鄂西南山区景观生态风险时空变化特征[J]. 生态学杂志, 2023, 42(5):1186-1196.
[21]
周海菊, 刘小英, 胡靓达, 等. 基于最佳分析粒度的广西北部湾经济区景观格局动态变化分析[J]. 生态与农村环境学报, 2022, 38(5):545-555.
[22]
谢萍, 苏昶丞, 雷海荔. 基于景观格局的山地型农村居民点空间分布特征及影响因素研究--以南江县为例[J]. 国土资源科技管理, 2023, 40(5):15-28.
[23]
余忠原, 朱兵. 空间粒度下丘陵山地区农村居民点景观格局指数变化分析--以四川省盐亭县为例[J]. 乡村科技, 2023, 14(23):143-148.
[24]
王智颖, 黄静怡. 基于GIS的农村居民点空间分布特征研究--以扶余市为例[J]. 现代农业科技, 2023(21):205-208.
[25]
刘立文, 段永红, 李丽丽, 等. 山西省农村居民点空间分布特征及其适宜性评价[J]. 中国农业资源与区划, 2022, 43(1):100-109.
[26]
吴未, 许丽萍, 张敏, 等. 不同斑块类型的景观指数粒度效应响应--以无锡市为例[J]. 生态学报, 2016, 36(9):2740-2749.
[27]
徐亚琼, 吴勇, 莫智斌, 等. 农地流转项目区景观格局粒度效应分析--以武胜县桐子岩村为例[J]. 西北民族大学学报(自然科学版), 2016, 37(2):73-79.
[28]
TIAN P, CAO L D, LI J L, et al. Landscape grain effect in Yancheng coastal wetland and its response to landscape changes[J]. International journal of environmental research and public health, 2019, 16(12):2225.
The landscape grain effect reflects the spatial heterogeneity of a landscape and it is used as a research core of landscape ecology. The landscape grain effect can be used to not only explore spatiotemporal variation characteristics of a landscape pattern, but also to disclose variation laws of ecological structures and functions of landscapes. In this study, the sensitivity of landscape pattern indexes to grain sizes 50–1000 m was studied based on landscape data in Yancheng Coastal Wetland acquired in 1991, 2000, 2008, and 2017. Response of the grain effect to landscape changes was analyzed and an optimal grain size for analysis in the study area was determined. Results indicated that: (1) among 27 indexes (12 in a class level and 15 in a landscape level), eight indexes were highly sensitive to grains, ten indexes presented moderate sensitivity, eight indexes presented low sensitivity, and one was unresponsive. It was shown that the area-margin index and the shape index were more sensitive to the different grain sizes. The aggregation index had some differences in the grain size change, and the diversity index had a low response degree to the grain size. (2) Landscape indexes showed six different responses to different grains, including slow reduced response, fast reduced and then slow reduced response, monotonically increased response, fluctuating reduced response, up-down responses, and stable response, which indicated that the landscape index was closely related to the spatial grain. (3) From 1991 to 2017, variation curves of the landscape grain size of different landscape types could be divided into four types: fluctuation rising type, fluctuation type, monotonous decreasing type, and monotonous rising type. Different grain size curves had different interpretations of landscape changes, but in general, Yancheng Coastal Wetland’s landscape tended to be fragmented and complicated, internal connectivity was weakened, and dominant landscape area was reduced. Natural wetlands were more sensitive to grain size effects than artificial wetlands. (4) The landscape index at the 50 m grain size had a strong response to different grain size changes, and the loss of landscape information was the smallest. Therefore, it was determined that the optimal landscape grain size in the study area was 50 m.
[29]
TENG M J, ZENG L X, ZHOU Z X, et al. Responses of landscape metrics to altering grain size in the three gorges reservoir landscape in China[J]. Environmental earth sciences, 2016, 75(13):1-13.
[30]
张晗, 赵小敏, 欧阳真程. 赣东北低山丘陵区农村居民点时空演变格局及影响因素研究--以江西省贵溪市为例[J]. 江西农业大学学报, 2019, 41(2):380-393.
[31]
李静帧, 陈国建. 乡村振兴战略下农村居民点空间分布特征--以麻柳镇为例[J]. 农村经济与科技, 2019, 30(19):16-20.
PDF(3597 KB)

Accesses

Citation

Detail

Sections
Recommended

/