Remote mountainous villages are at risk of falling back into poverty, despite having been lifted out of extreme poverty. However, there has been a lack of focus on the factors contributing to poverty-return in these villages, which making it difficult to understand the risks and their underlying causes. This study investigates the spatial distribution of 546 key assistance villages (KAVs) in the Liangshan mountainous region, a former poverty-stricken area, using the average nearest neighbor (ANN) and kernel density estimation (KDE) methods. Linear regression and geographically weighted regression (GWR) models are then employed to analyze the relationship between the KAVs' economy and potential poverty-returning factors. The results show that KAVs are primarily located in elevation ranges of 1800-2500 m (31.87%), with slopes of 6 degrees-15 degrees (42.67%) and 2-3 km from the township (28.94%). The distribution of KAVs exhibits distinct spatial clustering, forming four gathering areas. Several factors impact the KAVs' economy positively, including the normalized difference vegetation index (NDVI), built-up area, grassland, and education facilities, while elevation has a negative effect. The built-up area has the most critical impact on the rural economy, followed by NDVI and elevation. Additionally, education facilities and grassland areas also have significant effects. The study suggests promoting the Ex-situ Poverty Alleviation Relocation Program (ESPARP) and increasing rural built-up areas, grasslands, and educational facilities as practical measures for preventing poverty return and promoting economic development promotion in remote mountain villages.
