Urban area is the main environment where human are living. The stability of internal ecosystem of a city is highly relevant with its sustainable development. Besides, the connectivity of urban green landscapes is a symbol of the integrity and stability of regional ecological functions. Urbanization has brought a dramatic transformation to urban landscape connectivity. The research on the dynamic changes of landscape connectivity is not only significant to the stability of an urban ecosystem, but also provides a basis for regional biodiversity conservation, urban planning, and land use planning and management. However, current connectivity indicators have obvious limitations, for example, indices over different landscape patterns may show familiar values; graph theory requires a human interpretation because of redundancy data, and research on large-scale landscape may cause data extinction during processing. In this paper, Linear Spectral Mixture Model (LSMM) was integrated into Morphological Spatial Pattern Analysis (MSPA) to evaluate the spatial and temporal dynamics of green landscape connectivity in Shenzhen. According to the urban landscape characteristics and MSPA theory, 7 types of connectivity were defined for urban green landscapes, and then the change features among different urbanization gradients were analyzed. We defined urbanization gradients as three different circle layers based on urbanization density, with a decrease of dense values from the first circle to the third. The main steps followed: 1) LSMM was applied to extract the vegetation coverage information from multi-temporal Landsat TM images. On that, the high and full covered vegetation pixels were defined as the foreground pixels (green landscape) in MSPA approach. 2) 7 types of connectivity were utilized to reveal the temporal and spatial variations of green landscapes in the process of urbanization. The results demonstrated that: 1) over 27% of green landscapes in Shenzhen did not contribute to connectivity during 24a. 2) The transition matrix of connectivity-pattern categories from 1986 to 2010 indicated that the connectivity areas were sharply fluctuated during 24a, and the majority of classes changed into non-green landscapes. Except for the core category, the areas of other connectivity categories showed an upward trend. The connectivity of internal urban landscapes showed different trends between eastern part and western part, and, the Dapeng Peninsula in the third circle showed the best connectivity among the whole city. The peak interval of connected categories showed that the eastern part of Shenzhen had more connectivity providers than the western part. 3) The overall connectivity of Shenzhen's green landscapes followed a change of "decrease-increase" in sequence. Comparing with Shenzhen's urbanization process, it is proved that the quantity and connectivity of green landscapes were affected by the following factors: urbanization level, topographic factor and regional policy. Additionally, it is found that the topographic factor had the greatest influence within the same urbanization level. The results from temporal variations and spatial gradients demonstrated that both vegetation coverage and connectivity showed a downward trend in rapid urbanization process, while the two have been improved in steady urbanization stage. The experimental results prove that the jointly analytical framework is efficiently applied to reveal the spatial and temporal dynamics of connectivity characteristics for urban green landscapes during the process of urbanization. Furthermore it enables us to know the relationship between urbanization and urban green landscape connectivity. This research can be applied in practice and provide benefits for monitoring urban green landscapes.