his paper analyzes the spatially differentiated agglomeration of Wuhan's industries and marks Wuhan's industrial zoning structure so as to  provide references for Wuhan's industrial structural optimization and sustainable development. POI data is used for industrial classification. ArcGIS is applied to study Wuhan's industrial agglomerating features with its spatial core density method. Standard variance eclipse is used to estimate industrial center and development direction. Industrial spatial pattern is used to mark Wuhan's industrial zoning structure. Wuhan's agriculture and forestry show an agglomerating trend of "two cores, multiple points"; mining shows a massive with multiple points agglomerating trend in Huangpi and Jiangxia districts; other industries show "downtown core, rural multiple points" agglomerating trend, with subcenter of the third industry being around the new town. Industrial development is NE-SW oriented, of which the manufacturing, construction and the third industry are outbound along Yangtze River in the downtown areas. Wuhan's industrial development is of typical zonation. The outer zone is composed of the first industry and mining; the middle zone is composed of the 2^nd industry(except mining), public administration, social security, social organization, education, information transmission, software and information technology service; and the inner zone is composed of medical, water, environment and public service. Wuhan may rely on land and air transportation centers and technical advantages in the future, and lead industries to NE-SW as clusters in a pattern of "one core, multiple points, three zones" with the core of high-quality servicing, the middle zone of modern specific servicing and advanced manufacturing, the outer zone of rural new industries. This paper presents suggestions on keeping optimizing industrial structure and pushing high-quality industrial development.

Urban land intensive use (ULIU) is the breakthrough to economic growth quality (TFP). This paper, based on China's 30 provinces' information, discusses the influence of ULIU on TFP, in consideration of temporal lagging effect, uses spatial econometric model to measure the affection and influence of ULIU on TFP. ULIU can influence TFP from micro-, medium- and macroscopic mechanism. TFP rises across eastern, central to western provinces during 2003 to 2015. ULIU drives TFP, with its influence diminishing and rising across the whole country, also varying with locations, generally descending toward western provinces. This paper presents suggestions on industries-to-economic servicing, innovating public services and boosting regional spatial connection so as to promote the effective integration of ULIU and TFP.