This study applies remote sensing, GIS, landscape indices, and multivariate statistical analysis to monitor spatial and temporal land-use variations of Taipei districts from 1993 to 2007. The process includes the calculation of landscape indices from land-use maps and the performance of multivariate statistical analysis with three cases (i.e., cluster analysis with original landscape indices, principal component analysis, and factor analysis). The result from landscape indices indicates that variations exist among districts. As for multivariate statistical analysis, three cases achieve the same result. The results are concluded as follows: The integration of spatial technologies and landscape indices is a timely and useful approach to monitor Taipei land-use change. In addition, multivariate statistical analysis is a feasible approach for land-use change analysis. Particularly, principal component analysis and factor analysis are good for reducing the number of landscape indices, and cluster analysis is good for analyzing the spatial and temporal variations of Taipei districts. Therefore, the result obtained from this study can be a reference of Taipei urban planning in future.