Analysis of Soil Properties and Climatic Data to Predict Crop Yields and Cluster Different Agricultural Regions of Bangladesh

摘要

Bangladesh, a nation renowned for its rich fertile land and a population around 160 million, earns most of its living from agriculture. The nutrient rich lands help us providing year-round crop yields that play a crucial role for the economy of Bangladesh. Thus, this is important to deliberately work on agricultural planning and prediction models to ensure economic prosperity. The advancement of crop yields is significantly dependent on soil factors like Ph, nutrients and organic substances along with climatic factors like rainfall, temperature and humidity. Data of such factors are recorded to serve the purpose of scientific and statistical analysis. With the help of applying different data mining techniques on them, we are able to determine effective parameters to predict crop yield from different locations. This paper mainly focuses on the analysis to predict Bangladesh's four most yielding crops; wheat, jute, T-Aman and mustard. To carry out the whole experiment, we have analyzed soil properties of medium high land and high land from different sub districts of Bangladesh and also their respective climatic data and crop production of the last 6 years. For our analysis, we have applied different data mining techniques such as K-means, PAM, CLARA and DBSCAN for clustering and four linear regression methods to predict crop yields.