## 1 Introduction
applied annual Random Forest classification to analyze the land use trajectory of each pixel and distinguish abandoned land, testing the method across 14 regions globally [34]. They found that the accuracy of abandoned farmland extraction depends on the resolution of remote-sensing images [35]. [PERSON] et al. and [PERSON] et al. used GaoFen-1 (GF-1) and GaoFen-6 (GF-6) satellite images as their data sources. Their results showed that high-resolution remote sensing images had higher accuracy than medium- and low-resolution images [36; 37]. Compared to MODIS images, high-resolution satellite images offer higher spatial resolution, improving the accuracy of detecting land abandonment in areas with smallholder farming structures. High-resolution images more effectively address existing issues and provide reliable methods for farmland mapping. Therefore, this study uses high-resolution images from the GF-1 and GF-2 satellites to extract abandoned farmland data. The primary goal of the Gaofen satellite constellation is to provide users with high spatial resolution remote sensing images. Farmland abandonment is a common socio-economic phenomenon worldwide, and research into its driving mechanisms has become a key area of interest in fields such as geography, economics, and ecology [38; 39; 40; 41]. To better manage abandoned farmland, this study builds on farmland abandonment extraction results and further analyzes its causes in relation to driving factors. Studies show that farmland abandonment is particularly prevalent in areas with high elevation, steep slopes, poor soil conditions, inadequate infrastructure, inconvenient transportation, scattered plots, far from residential areas, and an average residential area of 0.48 hm2[42]. These factors vary by region, and a variety of factors influence farmland abandonment in any given area. The driving factors behind farmland abandonment can be divided into natural and human factors. Natural factors include terrain, proximity to water systems, and distance from forests, while human factors include transportation accessibility and distance from residential areas [43; 44]. Farming relies on land but is also constrained by its limitations. Long distances required for farming can lead to low cultivation willingness, poor irrigation conditions, and other challenges, resulting in seasonal abandonment of farmland [18; 45; 46; 47]. Excessive slopes pose challenges for mechanization, and poor land conditions hinder cultivation. High altitudes and low mechanization levels contribute to frequent farmland abandonment in hilly and plateau areas, leading to perennial abandonment [47]. This study analyzes the driving mechanisms of farmland abandonment using two natural factors (slope and distance to water systems) and two human factors (distance to residential areas and road network density). By examining these factors, the research identifies the varying degrees of impact each has on farmland abandonment. Based on these findings, targeted management measures can be proposed to address the issue more effectively. The study addresses three key aspects: (1) the extent of abandoned cultivated land in the study area, (2) the spatial distribution characteristics of abandoned cultivated land, and (3) the driving factors behind land abandonment. The goal is to provide valuable insights for the protection and sustainable use of farmland resources and to support large-scale surveys of abandoned cultivated land in the future.