A database of daily evapotranspiration (ET) maps derived from thermal remote sensing data using energy balance algorithms has numerous applications including irrigation scheduling, groundwater management, climate change impact assessment, hydrological modeling, development of drought indices, recharge prediction, irrigation performance, and land use planning. The objective of this study is to develop a framework for generating time series ET maps for Kansas using Landsat imagery. To achieve this objective, Landsat 5 and 7 imageries acquired over the past 25 years were downloaded from a USGS website. A QA/QC was conducted to select cloud free images for applying an energy balance algorithm. Meteorological parameters (air temperature, humidity, wind speed, downward solar radiation) at various locations throughout the state were collected and processed into spatially interpolated inputs. Surface energy balance system (SEBS) was used to derive evaporative fraction maps for calculating time series daily ET maps. In order to test the framework, a limited number of imageries were processed to derive ET maps. Accuracy assessment of ET maps indicated that the developed framework has the potential to be used for developing ET database for any given region. However, accurate data on air temperature may be needed for improving the accuracy of ET maps. Further, more work is needed to assess the quality of the extrapolated daily ET maps.