Crop Growth Modeling and Yield Forecasting

Abstract

In the past decades, crop growth modeling and yield forecasting have attracted increasing attention in both scientific researches and agricultural practices. Many scientific studies have been carried out to improve the capabilities of crop growth modeling and yield forecasting by using various data sources and methods like statistical models, crop growth simulation models, and remote sensing. In this chapter, four categories of crop growth models were reviewed. Firstly, the traditional crop modeling and forecasting methods were introduced: statistical modeling and crop growth models. Then remote sensing models mainly based on spectral indices and quantitative products were introduced. The quality of remote sensing data is critical for crop modeling and yield forecasting. Finally, the widely used data assimilation of crops was described. More research is necessary for the full use of the value of remote sensing and crop growth model in crop growth monitoring and yield forecasting at a regional scale.