• Preeti Tiwari
• Dr. Piyush Kumar Shukla

Information on spatial propagation of land cover and land utilization is important factor for taking care of connected issues in numerous domains. Geospatial information including satellite information assume a vital part since it can give normal, predictable and target data. Distinguishing geospatial designs and measure changes that happen in space with time require exceptional systems to be used. Different regular, monetary and organic variables impact the yield production yet random changes in these variables prompt an awesome losses to farmers. These dangers can be evaluated when proper numerical or measurable strategies are connected on information identified with soil, climate and past yield. This paper displays a review on the different models utilized for crop yield forecasting. So this paper focus on this problem of increasing the size of the data. Here various approaches adopt by researchers are detailed with their field of accuracy for prediction. Some of issue related to the papers is also discussed. Techniques of knowledge extraction and storage were discussed in this work. Here feature required to analyze the crop yield are present with their calculation and requirement

Geo-Spatial, Crop Yield, Artificial Neural Network, NDVI,VCI.

"A Review on Geo-Spatial Data based Crop Yield Analysis Using Artificial Neural Network Approach", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 7, page no.425-429, July-2018, Available :http://www.jetir.org/papers/JETIR1807781.pdf

"A Review on Geo-Spatial Data based Crop Yield Analysis Using Artificial Neural Network Approach", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 7, page no. pp425-429, July-2018, Available at : http://www.jetir.org/papers/JETIR1807781.pdf