Abstract

Crop phenology is an important parameter for crop growth monitoring, yield prediction, and growth simulation. The dynamic threshold method is widely used to retrieve vegetation phenology from remotely sensed vegetation index time series. However, crop growth is not only driven by natural conditions, but also modified through field management activities. Complicated planting patterns, such as multiple cropping, makes the vegetation index dynamics less symmetrical. These impacts are not considered in current approaches for crop phenology retrieval based on the dynamic threshold method. Thus, this paper aimed to (1) investigate the optimal thresholds for retrieving the start of the season (SOS) and the end of the season (EOS) of different crops, and (2) compare the performances of the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) in retrieving crop phenology with a modified version of the dynamic threshold method. The reference data included SOS and EOS ground observations of three major crop types in 2015 and 2016, which includes rice, wheat, and maize. Results show that (1) the modification of the original method ensures a 100% retrieval rate, which was not guaranteed using the original method. The modified dynamic threshold method is more suitable to retrieve crop SOS/EOS because it considers the asymmetry of crop vegetation index time series. (2) It is inappropriate to retrieve SOS and EOS with the same threshold for all crops, and the commonly used 20% or 50% thresholds are not the optimal thresholds for all crops. (3) For single and late rice, the accuracies of the SOS estimations based on EVI are generally higher compared to those based on NDVI. However, for spring maize and summer maize, results based on NDVI give higher accuracies. In terms of EOS, for early rice and summer maize, estimates based on EVI result in higher accuracies, but, for late rice and winter wheat, results based on NDVI are closer to the ground records.

Highlights

  • Crop phenology refers to seasonal and recurring crop developments, such as emergence, greening, jointing, heading, grouting, maturity, and more [1]

  • We used the 20% amplitude threshold to retrieve crop start of the season (SOS) and end of the season (EOS) based on MODerate-resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) time series

  • In order to investigate crop phenology accuracy based on the dynamic threshold method, we first improved the method to ensure a 100% retrieval rate

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Summary

Introduction

Crop phenology refers to seasonal and recurring crop developments, such as emergence, greening, jointing, heading, grouting, maturity, and more [1]. Crop phenological information is of great importance for agricultural production management and decision-making [2,3]. It is an important parameter for crop growth monitoring, yield prediction, and crop growth modeling using process-driven models [4]. Information about phenology provides important parameters to extract the crop planting area and the crops’ response to climate change [5,6]. Any changes in crop phenology are closely related to climate change and human activities, which makes it an important indicator of changes in terrestrial systems. Accurate retrieval of crop phenology information contributes to scientific research in global climate change, global carbon balance, ecological processes evolution, and more [8]

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