Abstract: A remote inspection vehicle for inspecting a plant for early drought stress and a neural network model for calculating a score corresponding to a level of early drought stress in the plant. The inspection vehicle may be equipped with an inspection camera having a radiometric infrared sensor and a red, green, and blue light sensor to capture plant images. Image data from the inspection vehicle, as well as soil moisture and calculated CWSI scores, can be used to train the neural network model, deriving weights and biases therefrom using a plurality of neural network layers. Using a plant canopy temperature value, a red raster value, a green raster value, a blue raster value, and a soil moisture value, the trained neural network model can generate a score which can be used to assess the level of early drought stress in a plant.