Paucity of information on Urban Canopy Parameters (UCPs) is considered as one of the major reason behind limited urban climate research and modelling in developing region of Asia, Africa, and Latin America. UCPs define those characteristics of urban built form which have direct or indirect influence on urban climate. Most of the studies in developed world have utilized 3-Dimension (3D) Geographic Information System (GIS) database either developed from ground survey or Remotely Sensed (RS) data such as Aerial Photographs, Airborne Light Detection and Ranging (LiDAR) and high-resolution Interferometric Synthetic Aperture Radar (InSAR) data for retrieval of UCPs. However, non-existence of 3D GIS database and limited availability of above RS datasets in developing region necessitates to employ widely available low-cost alternative datasets for retrieval of UCPs. Hence, this study focuses on retrieval of UCPs by employing Very High Resolution Satellite (VHRS) optical stereo data, which has repeat availability, low cost and extensive coverage, in a highly dense and complex urban environment with a challenging composite climate like Delhi, India. A novel methodology for extraction of gridded UCPs from VHRS optical stereo data has been developed in this study to overcome the limitation of extraction of individual building footprint in dense and compact urban built-up. The validation of key UCPs such as building height (Mean error, Root Mean Square Error (RMSE) and Mean Absolute Error <1 m in all height groups), Building Surface Area (Accuracy 84.27%) and Sky View Factor (RMSE = 0.046 and correlation = 0.94) with ground measurements has displayed reasonable accuracies. Hence, the study demonstrates successfully the use of VHRS optical satellite stereo data for generation of gridded UCPs in a highly heterogeneous and dense urban built-up environment. The developed approach is globally replicable in any city of any country.