Abstract: Abstract: Agricultural space is one of the most complex territorial systems with a fixed physical carrier (i.e. farmland) and the mobile factors of production. These mobile factors can be transmitted and radiated between different units during spatial planning. As such, the total-factor productivity of the indigenous farmland can be facilitated by the modernization of agriculture. Previous studies have demonstrated that the modernization process of agriculture in northeast China is later than elsewhere, due mainly to the server mismatch of basic factors in agricultural production. Taking the Harbin-Changchun Urban Agglomeration (HCUA) as a representative region, this study aims to conduct the network analysis of the key factors with the agricultural space and allocation optimization. Modified gravity model and social network analysis were adopted to identify the distributional structure of mobile factors in each prefectural unit, including the labor forces, capital investments, agricultural techniques, and managing policies. In addition, the farmland factor was represented by the scale, quality, and indexes, indicating the sustainable level of farmland use in each unit. A coupling coordination analysis was eventually introduced to measure whether these mobile factors were adapted to the farmland factor, and if not, some suggestions were made to reallocate these factors, in order to narrow down the gaps between these two systems. The results indicated that: 1) There was a prominent hierarchical network of mobile factors between the agricultural space of the prefectural units in HCUA, in which the central area was provided with the higher control and connectivity of factors. Moreover, Changchun City was identified as a pivot point to reallocate these mobile factors of production. Even though Harbin City was assumed as another pivot in most regional agricultural planning, the centrality in the entire network still needed to be promoted, especially for the labor forces, capital investments, and managing policies. 2) Both the scale and quality of farmlands were low in the eastern areas, while much higher in the western areas. But the units with the higher sustainable level of farmland use were concentrated in the central area, where the indexes were all higher than 0.65 in the Changchun, Siping, and Daqing. 3) A better performance of the indigenous farmland factor was achieved in the centrality of mobile factors in Changchun, Siping, and Songyuan. The core then served as the mobile factors eastward. Therefore, the other pivot-Harbin was activated first to optimize the factor allocation in HCUA. Then, the double-pivot system was developed to exert some influences northward, particularly for the places with abundant and fertile farmlands but deficient factors of production, such as Suihua, Daqing, and Qiqihar. Unfortunately, the hilly areas including Mudanjiang and Yanbian were found to be almost excluded from the network, and also difficult to be affected by the spillover effect. The characteristic agriculture can be expected for the highlights of the other services, except for the supplying services of agroecosystems. This finding can enrich the allocating factors of production in the agricultural space within a given region. Some statistics can also be used to promote the modernization of agriculture under industrial planning in northeast China.