Possible　dependence　across　spatial　units　is　a　relevant　issue　in　many　areas　in　practice.　In　this　paper,　we　consider　the　partially　linear　single-index　spatial　autoregressive　model　to　analyze　the　dependence　of　the　spatial　units　and　suggest　an　estimation　method.　An　algorithm　procedure　is　proposed　to　estimate　the　link　function　for　the　single　index　and　the　parameters　in　the　single　index,　as　well　as　the　parameters　in　the　linear　component　and　the　spatial　parameter　of　the　model.　The　nonparametric　function　is　estimated　based　on　B-spline　approximation.　The　Nelder-Mead　iteration　algorithm　is　adopted　to　calculate　the　parametric　and　nonparametric　parts　simultaneously　in　the　optimization.　The　asymptotic　properties　of　parameter　and　function　estimates　are　established.　Monte　Carlo　simulation　studies　are　conducted　to　investigate　the　performance　of　the　proposed　estimation　methodology　and　calculation　procedure.　Furthermore,　we　use　the　proposed　method　to　analyze　air　quality　data　and　rural　household　income　data　in　China.