This paper aims to explore the algorithmic design thinking for the landscape through a generative modeling approach to urban open space. Focusing on dynamic interactions between spatial dispersion of hard-soft surfaces, shadow elements like tree locations and their impacts such as microclimatic condition changes with human behaviors, were the primary inputs of the process. Using a case study from Turkey/Istanbul-Kadıköy, the reciprocal relations between social (human movement), physical (hard-soft structures) and ecological (surface radiation and microclimate analysis) parameters were studied, and how these relations formed the design was shown. The modeling process was defined in 4 algorithmically associated stages: firstly, field observations were conducted to collect data on vegetation and user behaviors, for site digitalization. After that, algorithmic parameters were defined in the second phase; and design constraints, as the first initiator of the interactive process, were identified. At the last stage, by the evaluation of all parameters with constraints, final design set-up was originated via a Quadtree algorithm. During these phases, user simulation data, surface radiation and outdoor microclimate analysis findings were shown for comparison. Therefore, this study underlines the importance of the data for landscape design, and its process, rather than the final design solution.