This paper proposes a potential solution to the traditional method of rice field preparation and management by utilizing unmanned aerial vehicles (UAVs) equipped with RGB and spectral cameras. Farmers typically rely on their experience to deal with bad weather and prepare rice fields in the beginning of the season, resulting in time-consuming and inefficient processes. The proposed method uses UAVs to evaluate the rice fields from the start to the middle stages of the season. The UAV flight follows a pre-determined trajectory autonomously, capturing successive images using the attached cameras. In the soil preparation stage, Harralick texture segmentation is used to analyze the roughness of paddy fields’ surfaces (low land, normal land and high land). In this approach, image is segmented first, then areas belonging the same clusters are extracted, manually verified and labelled. These labelled images are used as training data for the proposed model. The result shows that roughness of field surface can be observed clearly with high accuracy at over 90%, with random forest method is at over 97%. In addition to this, the effects of rain and flooding are also considered during the reproductive stages. The results show that the proposed method achieves high accuracy in evaluating rice fields, which can significantly increase efficiency and productivity compared to traditional methods. The study highlights the potential of UAV-based monitoring to provide a cost-effective and efficient way to manage rice fields and improve crop yields, leading to higher food security and sustainable agriculture.