Based on SPOT-5 images, 1:1 million topographic maps, the maps of the returning farmland to forest project and the Chongqing forest project, social and economic statistics, etc., this paper identifies the features and factors influencing farmland marginalization. The results showed:(1) During 2002–2012, the rate of farmland marginalization was 16.18%, which was mainly found in the high areas of northern Qiyao mountains and the medium-altitude areas of southern Qiyao mountains. And this farmland marginalization will increase, associated with non-agriculturalization of rural labourers and aging of the remaining labourers.(2) Elevation, distance radius from villages and road connections had a great influence on farmland marginalization. Farmland marginalization rates showed an increasing trend with the increase of elevation, and 60.88% of the total farmland marginalization area is found at an altitude greater than 1000 m above sea level. The marginalization trend also increases with slope and distance from the distribution network.(3) Farmland area per labourer and the average age of farm labourers were major factors driving farmland marginalization. Farmland transfer and small agricultural machinery sets affect farmland marginalization with respect to management and productivity efficiency.(4) Farmland with “comparative- disadvantage-dominated marginalization” accounted for 55.32% of the total farmland marginalization area, followed by “location-dominated marginalization”(33.80%).(5) According to the specifics of each real situation, different policies are suggested to mitigate the marginalization. A “continuous marginalization” policy will encourage the return of farmland to forest in “terrain-dominated marginalization”. An “anti-marginalization” policy is suggested to create new rural accommodation and improve the rural road system to counteract “terrain-dominated marginalization”. And another “anti-marginalization” policy is planned to improve management and micro-mechanization for “comparative-disadvantage-dominated marginalization”. A new idea was developed to integrate high resolution remote sensing and statistical data with survey information to identify land marginalization and its driving forces in mountainous areas. Based on SPOT-5 images, 1: 1 million topographic maps, the maps of the returning farmland to forest project and the Chongqing forest project, social and economic statistics, etc., this paper identifies the features and factors influencing farmland marginalization. The results showed: (1) During 2002-2012, the rate of farmland marginalization was 16.18%, which was mainly found in the high areas of northern Qiyao mountains and the medium-altitude areas of southern Qiyao mountains. And this farmland marginalization will increase, associated with non-agriculturalization of rural labourers and aging of the remaining labourers. (2) Elevation, distance radius from villages and road connections had a great influence on farmland marginalization. Farmland marginalization rates showed an increasing trend with the increase of elevation, and 60.88% of the total farmland marginalization area is found at an altitude greater than 1000 m above sea level. The marginalization trend also increases with slo (3) Farmland area per labourer and the average age of farm labourers were major factors driving farmland marginalization. Farmland transfer and small agricultural machinery sets affect farmland marginalization with respect to management and productivity efficiency. (4) Farmland with “comparative-disadvantage-dominated marginalization ” accounted for 55.32% of the total farmland marginalization area, followed by “location-dominated marginalization ” (33.80%). (5) According to the specifics of each real situation, different policies are suggested to mitigate the marginalization. A “continuous marginalization ” policy will encourage the return of farmland to forest in “terrain-dominated marginalization ”. An “anti-marginalization ” policy is suggested to create new rural accommodation and improve the rural road system to counteract “terrain-dominated marginalization ”. And another “anti-marginalization ” policy is planned to improve manag ement and micro-mechanization for “comparative-disadvantage-dominated marginalization ”. A new idea was developed to integrate high resolution remote sensing and statistical data with survey information to identify land marginalization and its driving forces in mountainous areas.