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Analyze the Impact of Weather Parameters for Crop Yield Prediction Using Deep Learning

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Big Data Analytics (BDA 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13773))

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Abstract

Accurate crop yield prediction is one of the most important aspects for the agricultural policy decision for the policy makers and the farmers. However, prediction of crop yield depends on many parameters such as weather, soil, seed quality and farm practices. Importance of different parameters on crop is varying from crop to crop and region to region. With the availability of satellite images along with statistical data, deep leaning based model can capture growth of crop over temporal data. In this paper, we introduce informal methods to analyze and measure the impact of weather on the crop yield prediction using remote sensing images. Here, we applied Convolutional Neural Network (CNN) - Long Short-Term Memory (LSTM) based model over a large spatial and temporal data collected during crop growth season. We compared our model with two other models and found that it confers performance improvement over other models. From the experimental result, we dissect that inclusion of weather increase yield prediction and crop growth is highly correlated on the weather parameters.

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Authors and Affiliations

  1. Ahmedabad University, Gujarat, India

    Pragneshkumar Patel & Sanjay Chaudhary

  2. L. D. College of Engineering, Gujarat, India

    Hasit Parmar

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  1. Pragneshkumar Patel
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  2. Sanjay Chaudhary
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  3. Hasit Parmar
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Corresponding author

Correspondence to Pragneshkumar Patel .

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Editors and Affiliations

  1. Indian Institute of Technology-Roorkee, Roorkee, India

    Partha Pratim Roy

  2. IBM Research, Gurugram, India

    Arvind Agarwal

  3. Southwest Jiaotong University, Chengdu, China

    Tianrui Li

  4. International Institute of Information Technology - Hyderabad, Hyderabad, India

    P. Krishna Reddy

  5. The University of Aizu, Fukushima, Japan

    R. Uday Kiran

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Patel, P., Chaudhary, S., Parmar, H. (2022). Analyze the Impact of Weather Parameters for Crop Yield Prediction Using Deep Learning. In: Roy, P.P., Agarwal, A., Li, T., Krishna Reddy, P., Uday Kiran, R. (eds) Big Data Analytics. BDA 2022. Lecture Notes in Computer Science, vol 13773. Springer, Cham. https://doi.org/10.1007/978-3-031-24094-2_17

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  • DOI: https://doi.org/10.1007/978-3-031-24094-2_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-24093-5

  • Online ISBN: 978-3-031-24094-2

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