Identification and spatial pattern analysis of abandoned farmland in Jiangxi Province of China based on GF-1 satellite image and object-oriented technology

Introduction Industrialization, urbanization, wars, and conflicts have caused farmland abandonment and exacerbated food security issues, posing a major challenge to global food security. Therefore, it is of great significance to monitor the status of crop abandonment in major grain-producing areas. Most of previous studies using remote sensing technology to extract abandoned farmland have small scale and low accuracy, and there was lack of large-scale studies using GF-1 image. Particularly in the Jiangxi Province, as the main grain-producing area of China, the situation of farmland abandonment is still unknown. Methods In this paper, GF-1 WFV remote sensing images are used as the main data source. A binary decision tree process based on the object-oriented technology classification and vector similarity function change detection methods are adopted to extract abandoned farmland information in Jiangxi Province during 2020–2022 and to describe its spatial pattern. Results The results show that the overall accuracy of GF-1 remote sensing image extraction based on object-oriented technology is 93%, and the Kappa coefficient is 0.89. The abandoned farmland in Jiangxi Province covers an extensive area of 3.41 × 10 5 hm 2 , with an abandonment rate of 9.87%. Abandonment is greater in the north and less in the south, with a spatial distribution pattern characterized by sparse coverage in mountainous areas and aggregation in plains areas. Farmland abandonment is most severe in the areas surrounding the northern Poyang Lake Plain, and the degree of farmland abandonment varies significantly among various prefecture cities as well as among different counties. The highest rate of farmland abandonment in prefecture cities was 13.18% and the lowest was 7.13%. The highest rate of farmland abandonment in the county was 24.22%, and the lowest was 1.99%. Discussion The results are helpful in understanding the status of abandoned farmland in major grain-producing areas. It is believed they are significant for farmland protection and real-time national food security strategy.