Horticulture Crop Inventory: A Survey on Identification and Classification of Crops using Satellite Image Processing

Abstract

Identification of horticulture crop type is as important and classification of crops, it shall be used for crop yield measurement and planning of plantation. It is also important to obtain an accurate classification of crops to help ARO’s report outcomes to the authorized representatives in the respective department. It mainly focuses on crop identification in certain areas and hence it is important not only to classify the crop but also to detect the type and grade based on the satellite imagery and ground data. The dataset used is composed of the local region and appropriate channel images from the satellite. The analysis identifies the techniques of Machine Learning methods that will classify the type of horticulture crop, Deep Learning methods are used to diagnose grades for the crop in a particular region/area that helps the farmers and agriculturists. Neural Network algorithms have been successfully used to identify the crop and grade the crop with very little variation. In this paper, it is proposed to provide a detailed survey on information technologies and methodologies used in horticulture crop inventory to improve the accuracy of crop identification and classification.