Remotely sensed data are data taken from above the Earth’s surface. They offer a global coverage, with variable spatial, radiometric, spectral and temporal resolutions, and are the major source of geo-spatial information. The importance of cities and their structural complexity and continuous change make the use of such data even more necessary. In this chapter, we will limit ourselves to remotely sensed sensors that can facilitate the extraction of basic geo-spatial information, such as Digital Terrain Models (DTMs), Digital Surface Models (DSMs) and orthoimages, In addition, we will examine the identification of urban objects, such as buildings, roads, vegetation, etc., as well as the mapping of entire cities and the rudiments of three-dimensional city modelling. We will restrict the discussions mainly to imaging sensors with spatial resolutions of up to around lm , as well as active systems such as LIDAR (Laser-Induced Detection And Ranging); while other sensors, such as SAR (Synthetic Aperture Radar), thermal and hyperspectral will be mentioned only briefly. We also acknowledge that lower spatial resolution satellite imagery have been often used and are still valuable for various urban applications.