基于多元数据的农村居住用地空置率空间估算

doi:10.3969/j.issn.0255-8297.2025.06.007

Abstract

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

CLC Number:

P237

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.

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

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