A Deep Gaussian Process for Forecasting Crop Yield and Time Series Analysis of Precipitation Based in Munshiganj, Bangladesh

In this study, we use the combination of remote sensing and deep learning techniques to predict agricultural yield of potato one of the most consumed items all over the world. Time-Series analysis of rainfall using an LSTM (Long Short Term Memory) network is also exhibited in this study to help better understand the changes in climate and crop yield. The study was carried out in Munshiganj district of Bangladesh, which is the main contributor of potatoes in the country. With our results, we exhibit how the changes in seasonal rainfall affects the country's economy as well as livelihood since majority of the people's livelihood depends on agriculture.