Algorithms that understand the different bounded segments that are present in an image by itself without referring to the ground truth.
Published in Chapter:
Recommendation of Crop and Yield Prediction by Assessing Soil Health From Ortho-Photos
J Dhalia Sweetlin (Anna University, Chennai, India), Visali A. L. (Anna University, Chennai, India), Sruthi Sreeram (Anna University, Chennai, India), and Jyothi Prasanth D. R. (Anna University, Chennai, India)
Copyright: © 2022
|Pages: 19
DOI: 10.4018/978-1-7998-8763-8.ch003
Abstract
Agriculture is considered to be the driving force of the Indian economy. Production of crops is considered to be one of the complex phenomena as they are influenced by the agro-climatic parameters. From novice to experienced farmers, at times, fail to figure out the suitable crop for their lands, leading to financial loss. This is because of the dynamic change in soil nutrient levels and climatic conditions. Hence, it is important to predict crops according to the presence of the nutrients in a land. Recommending the crops to a farm after considering the nutrients levels of the soil and predicting the yield will largely help the landowner in taking necessary steps for marketing and storage in the future. These results will further assist the industries to plan the logistics of their business who are working in partnership with these landowners. In this work, pH and other soil nutrients are estimated from the input ortho images to recommend crops that can grow well under the given circumstances.