中文

Journal of Applied Sciences >

2025 , Vol. 43 >Issue 6: 978 - 989

DOI: https://doi.org/10.3969/j.issn.0255-8297.2025.06.007

Signal and Information Processing

Spatial Estimation of Rural Residential Land Vacancy Rate Based on Multivariate Data

  • GUO Lina ,
  • DU Yanlin ,
  • WANG Hao ,
  • JIANG Guanghui ,
  • ZHAO Yanxia ,
  • ZHAO Tingting
Expand
  • 1. College of Mining Engineering, North China University of Science and Technology, Tangshan 063210, Hebei, China;
    2. Tangshan Key Laboratory of Resources and Environment Remote Sensing, Tangshan 063210, Hebei, China;
    3. Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China;
    4. Faculty of Agroforestry and Medicine, The Open University of China, Beijing 100039, China

Received date: 2023-07-27

  Online published: 2025-12-19

Fold

Abstract

To address the issue of rural hollowing and even the expansion of residential land, this paper extracted residential land from GF-1 satellite imagery using the maximum likelihood method, support vector machine method, and neural network classification method. On this basis, the paper superimposed NPP/VIIRS nighttime light data and point of interest (POI) data to estimate the vacancy rate of rural residential land in Fengnan District, Tangshan City. The results indicate: 1) Given the significant gaps in social security between urban and rural areas, rural laborers who take part-time jobs or work in towns and cities still return home to engage in agricultural work during the busy farming season, resulting in differences in the vacancy rate of rural residential land between the busy farming period and the slack farming period. The vacancy rate of residential land in Fengnan District aligns with the seasonality of agricultural production. In October, the busy farming season, the vacancy rate was 25.35%, which was slightly lower than the 26.73% recorded during the slack farming season. This validates the hypothesis proposed in this study and confirms that the idea of selecting remote sensing images for vacancy rate estimation based on the seasonal characteristics of agricultural activities is basically reliable. 2) The variation mechanism of the residential land vacancy rate in Fengnan District is consistent with that of the POI kernel density analysis results. This indicates that the high-precision estimation method for urban housing vacancy rate is applicable to the estimation of rural residential land vacancy rate in plain areas. The vacancy rate estimation results provide a reference for the selection of research areas in subsequent studies and for a deeper understanding of the vacancy phenomenon of rural residential land.

Key words： vacancy rate; nighttime lighting data; phenophase; residential land; supervised classification

Cite this article

GUO Lina , DU Yanlin , WANG Hao , JIANG Guanghui , ZHAO Yanxia , ZHAO Tingting . Spatial Estimation of Rural Residential Land Vacancy Rate Based on Multivariate Data[J]. Journal of Applied Sciences, 2025 , 43(6) : 978 -989 . DOI: 10.3969/j.issn.0255-8297.2025.06.007

References

[1] 王永生, 刘彦随. 中国乡村生态环境污染现状及重构策略[J]. 地理科学进展, 2018, 37(5): 710-717. Wang Y S, Liu Y S. Pollution and restructuring strategies of rural ecological environment in China [J]. Progress in Geography, 2018, 37(5): 710-717. (in Chinese)
[2] Siciliano G. Urbanization strategies, rural development and land use changes in China: a multiple-level integrated assessment [J]. Land Use Policy, 2012, 29(1): 165-178.
[3] Li Y H, Westlund H, Liu Y S. Why some rural areas decline while some others not: an overview of rural evolution in the world [J]. Journal of Rural Studies, 2019, 68: 135-143.
[4] Jin X B, Long Y, Sun W, et al. Evaluating cities’ vitality and identifying ghost cities in China with emerging geographical data [J]. Cities, 2017, 63: 98-109.
[5] 邱生荣, 梁康迳. 闽侯县闲置农地生态安全评价研究[J]. 中国农业资源与区划, 2018, 39(6): 93-98, 159. Qiu S R, Liang K J. Study on ecological security evaluation of idle farmland in Minhou county [J]. Chinese Journal of Agricultural Resources and Regional Planning, 2018, 39(6): 93-98, 159. (in Chinese)
[6] 宋才发. 关于闲置土地依法处置的再探讨[J]. 河北法学, 2018, 36(6): 18-29. Song C F. Discussion on the disposal of idle land according to law [J]. Hebei Law Science, 2018, 36(6): 18-29. (in Chinese)
[7] 刘彦随, 严镔, 王艳飞. 新时期中国城乡发展的主要问题与转型对策[J]. 经济地理, 2016, 36(7): 1-8. Liu Y S, Yan B, Wang Y F. Urban-rural development problems and transformation countermeasures in the new period in China [J]. Economic Geography, 2016, 36(7): 1-8. (in Chinese)
[8] Beeton R J S, Lynch A J J. Most of nature: a framework to resolve the twin dilemmas of the decline of nature and rural communities [J]. Environmental Science & Policy, 2012, 23: 45-56.
[9] 张栋, 李德平, 周亮, 等. 利用高分影像和珞珈一号数据进行住房空置率高精度空间估算[J]. 测绘通报, 2021(1): 41-46, 52. Zhang D, Li D P, Zhou L, et al. High precision space estimation of housing vacancy rate using high resolution image and Luojia-1[J]. Bulletin of Surveying and Mapping, 2021(1): 41-46, 52. (in Chinese)
[10] 姜萌, 谢臻, 张凤荣, 等. 黄土丘陵区乡村“人、 境、 地” 演变特征及迁并村庄诊断分类——以陕西省米脂县为例[J]. 中国农业大学学报, 2022, 27(2): 214-229. Jiang M, Xie Z, Zhang F R, et al. Evolution characteristics of “person, environment and land” in Loess Hilly Region and the classification of moving and merging villages: a case study of Mizhi County, Shaanxi Province [J]. Journal of China Agricultural University, 2022, 27(2): 214-229. (in Chinese)
[11] Gan L, Yin Z, Jia N, et al. Analysis of urban housing vacancy of China in 2017[J]. Southwestern University of Finance and Economics Press, 2018: 1-34.
[12] 张丽萍. 中国人口城镇化过程中的住房问题研究[J]. 北京工业大学学报(社会科学版), 2022, 22(4): 133-150. Zhang L P. Research on the housing problem in the process of population urbanization in China [J]. Journal of Beijing University of Technology (Social Sciences Edition), 2022, 22(4): 133-150. (in Chinese)
[13] Green T L. Evaluating predictors for brownfield redevelopment [J]. Land Use Policy, 2018, 73: 299-319.
[14] Zheng Q M, Deng J S, Jiang R W, et al. Monitoring and assessing “ghost cities” in Northeast China from the view of nighttime light remote sensing data [J]. Habitat International, 2017, 70: 34-42.
[15] Lu H L, Zhang C R, Liu G F, et al. Mapping China’s ghost cities through the combination of nighttime satellite data and daytime satellite data [J]. Remote Sensing, 2018, 10(7): 1037.
[16] 厉飞, 闫庆武, 邹雅婧, 等. 利用夜间灯光POI的城市建成区提取精度研究——以珞珈一号01星和NPP/VIIRS夜间灯光影像为例[J]. 武汉大学学报(信息科学版), 2021, 46(6): 825-835. Li F, Yan Q W, Zou Y J, et al. Extraction accuracy of urban built-up area based on nighttime light data and POI: a case study of Luojia 1-01 and NPP/VIIRS nighttime light images [J]. Geomatics and Information Science of Wuhan University, 2021, 46(6): 825-835. (in Chinese)
[17] Chen Z Q, Yu B L, Hu Y J, et al. Estimating house vacancy rate in metropolitan areas using NPP-VIIRS nighttime light composite data [J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2015, 8(5): 2188-2197.
[18] Wang L Y, Fan H, Wang Y K. An estimation of housing vacancy rate using NPP-VIIRS night-time light data and OpenStreetMap data [J]. International Journal of Remote Sensing, 2019, 40(22): 8566-8588.
[19] Du M Z, Wang L, Zou S Y, et al. Modeling the census tract level housing vacancy rate with the Jilin1-03 satellite and other geospatial data [J]. Remote Sensing, 2018, 10(12): 1920.
[20] 张霖, 李熙. 夜光遥感视角下的巴基斯坦区域发展差异分析[J]. 武汉大学学报(信息科学版), 2022, 47(2): 269-279. Zhang L, Li X. Analysis on disparity of regional development in Pakistan under perspective of nighttime light remote sensing [J]. Geomatics and Information Science of Wuhan University, 2022, 47(2): 269-279. (in Chinese)
[21] Gong P, Chen B, Li X C, et al. Mapping essential urban land use categories in China (EULUC-China): preliminary results for 2018[J]. Science Bulletin, 2020, 65(3): 182-187.
[22] 闫夏, 马安青, 王云霞, 等. 基于多源大数据和人口分布视角的青岛市中心城区空间结构研究[J]. 地域研究与开发, 2023, 42(2): 67-72, 79. Yan X, Ma A Q, Wang Y X, et al. Spatial structure of central urban area of Qingdao City based on multi-source big data and population distribution perspective [J]. Areal Research and Development, 2023, 42(2): 67-72, 79. (in Chinese)
[23] 马雯秋, 何新, 姜广辉, 等. 基于土地功能的农村居民点内部用地结构分类[J]. 农业工程学报, 2018, 34(4): 269-277. Ma W Q, He X, Jiang G H, et al. Land use internal structure classification of rural settlements based on land use function [J]. Transactions of the Chinese Society of Agricultural Engineering, 2018, 34(4): 269-277. (in Chinese)
[24] 张佰林, 张凤荣, 周建, 等. 农村居民点功能演变的微尺度分析——山东省沂水县核桃园村的实证[J]. 地理科学, 2015, 35(10): 1272-1279. Zhang B L, Zhang F R, Zhou J, et al. Functional evolution of rural settlement based on micro-perspective: a case study of hetaoyuan village in Yishui County, Shandong Province [J]. Scientia Geographica Sinica, 2015, 35(10): 1272-1279. (in Chinese)
[25] 焦林申, 张敏, 秦萧, 等. 城乡空置住房的识别、 特征与成因——基于华北平原X县用电量等多源数据 [J]. 自然资源学报, 2022, 37(8): 2004-2017. Jiao L S, Zhang M, Qin X, et al. Identification, characters and causes of housing vacancy: a perspective from multi-source data [J]. Journal of Natural Resources, 2022, 37(8): 2004-2017. (in Chinese)
Options
Outlines

/

〈 〉