Engineering Commons^™

Assessment Of Surface Soil Moisture Using High-Resolution Multi-Spectral Imagery And Artificial Neural Networks, Leila Hassan-Esfahani, Alfonso F. Torres-Rua, Austin M. Jensen, Mac Mckee

Civil and Environmental Engineering Faculty Publications

Many crop production management decisions can be informed using data from high-resolution aerial images that provide information about crop health as influenced by soil fertility and moisture. Surface soil moisture is a key component of soil water balance, which addresses water and energy exchanges at the surface/atmosphere interface; however, high-resolution remotely sensed data is rarely used to acquire soil moisture values. In this study, an artificial neural network (ANN) model was developed to quantify the effectiveness of using spectral images to estimate surface soil moisture. The model produces acceptable estimations of surface soil moisture (root mean square error (RMSE) = …