Application of Hyperspectral Remote Sensing Technology for Plant Disease Forecasting: An Applied Review

Abstract

Each plant has distinct behaviour, features, and infections known as pathogens. Plant growth and its life have to be estimated to prevent economic loss in agriculture. Many techniques such as optical techniques, knowledge graph, image processing techniques, remote sensing techniques, DNA based, and serological methods are used to detect the plant diseases from the captured input in the form of images, video frames, and set of characteristics features. Health conditions of a plant are to be recognized accurately in time to avoid disease spread severity. Remote sensing techniques with different types of sensors exemplify extraordinary means which are most helpful to monitor and identify the plant diseases, preventing expensive use of pesticides. Disease forecasting aims to organize control measures before the substance of a plant is likely to infect the crop. A survey on plant disease detection and the applications of remote sensing technology in forecasting the pathogens is presented in this article. Thus it is very significant to predict the diseases by an effective disease warning system that should be reliable to the crop cultivators.