Clustering of spatial data in the presence of obstacles and constraints has the very strong practical value, and becomes to an important research issue. Most of the existing spatial clustering algorithm in presence of obstacles and constraints can't cluster with irregular obstacles and the veracity of clustering result is affected. The algorithm complexity is affected by complexity of computing obstacle-distance. Grid-based hierarchical spatial clustering algorithm which is abbreviated as GSHCOC is proposed. The advantage of grid-based clustering algorithm is inherited. The obstacle-grid is defined and the algorithm processes arbitrary shape obstacle and finds arbitrary shape clusters efficiently. Meanwhile, the hierarchical strategy is used to reduce the complexity of clustering in presence of obstacles and constraints and the operation efficiency of algorithm is improved. The results of experiment show that GSHCOC algorithm can process spatial clustering in presence of obstacles and constraints and has higher clustering quality and better performance.