Identifying and measuring urban spatial structure is a prerequisite for understanding urban spatial characteristics, formulating urban development strategies and testing urban planning results. As important data sources that can visually reflect the spatial distribution characteristics of urban socio-economic and other physical elements, urban points of interest (POI) and nighttime light data play an important role in the study of urban spatial structure. In this study, the main urban areas of 36 cities of the Three Northeast Provinces (Heilongjiang Province, Jilin Province, Liaoning Province) were selected as the study area, the POI (6,553,294 points of interest) and nighttime light data from 2010, 2016, and 2022 were chosen as the basic research data, and the methods of point kernel density estimation, data griddedness, and multifactor combination mapping were used to analyze the developmental dynamics of the urban spatial structure. The study demonstrated: (1) The spatial coupling consistency of POI and nighttime light data in the main urban areas of the Three Northeast Provinces was high, and both had good applicability in urban spatial structure research; (2) POI and nighttime light values formed the spatial pattern of “axis + core − periphery” with Shenyang, Dalian, Changchun and Harbin as the core, while the coupling relationship between the POI and nighttime light data identified that the main urban areas in the Three Northeast Provinces presented a centralized agglomeration type, a decentralized grouping type, a belt combination type and a radial expansion type urban spatial structure; (3) From the perspective of changes in the coupling relationship between POI and nighttime light, most of the main urban areas of resource-mature cities, resource-regeneration cities and non-resource cities were affected by the regional development agglomeration and the “T” railway network, and the “high/medium–high/medium” area showed an expanding tendency; most of the main urban areas of resource-decline cities were affected by the lower development potential and the deprivation of economic factors by the surrounding core cities, while the “high/medium–high/medium” areas showed a contracting tendency. The results of the study can provide a scientific basis and theoretical reference for the future adjustment of urban spatial structure, planning and construction as well as resource allocation in the main urban areas of the cities in the Three Northeast Provinces.