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A Review on Various Features and Techniques of Crop Yield Prediction Using Geo-Spatial Data

Geospatial information, including satellite information, is a vital part of crop yield prediction since it can give normal, predictable, target data. Distinguishing geospatial designs and measure changes that happen require exceptional systems to be used. Different monetary and organic variables impact the yield production and variables prompt losses to farmers. These dangers can be evaluated when proper numerical or measurable strategies are connected with soil, climate and past yield data. This article reviews different models utilized for crop yield forecasting. The focus of this problem is the increasing size of the data. Here, various approaches adopted by researchers are detailed with their field of accuracy for prediction. Some of issues related to the papers are also discussed. The techniques of knowledge extraction and storage were also discussed in this work.