Abstarct: Estimation of water demands for urban green space plants is necessary for the management and planning of groundwater resources, optimal water withdrawal of wells and qanats, as well as for the design of irrigation systems. There are various methods for estimation of the water demands of green space plants on a small scale, such as the lysimeter method, which has high accuracy, but the use of these methods on large scales implied high costs. Therefore, methods baxsed on remote sensing techniques and the use of satellite imagery have been considered by researchers. Consequently, in this study, the water demand of urban green spaces plants in Shahrood city has been estimated using satellite image processing and the Sabal algorithm. In this research, using Landsat 8 satellite images, a method baxsed on the Sabal algorithm, and measured parameters in Shahrood synoptic meteorological station the water demand of urban green spaces has been estimated. Furthermore, using the FAO-Penman-Mantith method and according to the KC coefficient of plants and their growth stages, the water demand of urban green spaces has been evaluated. The results showed that remote sensing techniques are capable to forecast the values of the coefficient of determination in the methods of FAO-Penman-Monteith, Hargreaves, Taylor, and Blaney-Kridel, 0.84, 0.72, 0.93, and 0.91respectively.