1 November 2010 Actual evapotranspiration estimation for different land use and land cover in urban regions using Landsat 5 data
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Abstract
Evapotranspiration (ET) is deemed critical for water resources management. Even in the same climatic and meteorological conditions, actual ET (ETa) may exhibit remarkable spatial variability across different vegetation covers, agricultural land use practices, and differing types of urban land development. The main objectives of this study are (1) to evaluate the possible closure of the heat balance equation using Oklahoma's unique environmental monitoring network; and (2) to estimate ETa and determine the variation with regards to varying types of land use and land cover in urban settings. In this study, a Surface-Energy-Balance ET algorithm was implemented to estimate ETa at a higher spatial resolution using Landsat 5 satellite images while the Oklahoma Mesonet observations can be used as our ground truth data. Accuracy of the estimated ETa was assessed using latent heat flux measurements provided by AmeriFlux towers. The associated bias ratios of daily mean ETa with respect to both burn and control sites are -0.92%, and -8.86% with a correlation of 0.83 and 0.81, respectively. Additionally, estimated ETa from a water balance budget analysis and the remotely sensed ETa are cross-validated with a low bias ratio of 5.2%, and a correlation coefficient of 0.7 at the catchment scale. The lowest ETa was observed for developed urban areas and highest for open water bodies. The ETa difference is also demonstrated from two contrasting counties. The results show Garfield County (agricultural) has higher ETa values than Oklahoma County (urban) for all land cover types except open water bodies.
Wenjuan Liu, Wenjuan Liu, Yang Hong, Yang Hong, Sadiq Ibrahim Khan, Sadiq Ibrahim Khan, Mingbin Huang, Mingbin Huang, Baxter Vieux, Baxter Vieux, Semiha Caliskan, Semiha Caliskan, Trevor Grout, Trevor Grout, } "Actual evapotranspiration estimation for different land use and land cover in urban regions using Landsat 5 data," Journal of Applied Remote Sensing 4(1), 041873 (1 November 2010). https://doi.org/10.1117/1.3525566 . Submission:
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