Abstract

Crop phenology is critical for agricultural management, crop yield estimation, and agroecosystem assessment. Traditionally, crop growth stages are observed from the ground, which is time-consuming and lacks spatial variability. Remote sensing Vegetation Index (VI) time series has been used to map land surface phenology (LSP) and relate to crop growth stages mostly after the growing season. In recent years, high temporal and spatial resolution remote sensing data have allowed near-real-time mapping of crop phenology within the growing season. This paper summarizes two classes of near-real-time mapping methods, i.e., curve-based and trend-based approaches. The curve-based approaches combine the time series VIs and crop growth stages from historical years with the current observations to estimate crop growth stages. The curve-based approaches are capable of a short-term prediction. The trend-based approaches detect upward or downward trends from time series and confirm the trends using the increasing or decreasing momentum and VI thresholds. The trend-based approaches only use current observations. Both curve-based and trend-based approaches are promising in mapping crop growth stages timely. Nevertheless, mapping crop phenology near real-time is challenging since remote sensing observations are not always sensitive to crop growth stages. The accuracy of crop phenology detection depends on the frequency and availability of cloud-free observations within the growing season. Recent satellite datasets such as the harmonized Landsat and Sentinel-2 (HLS) are promising for mapping crop phenology within the season over large areas. Operational applications in the near future are feasible.

Highlights

  • Crop phenology defines physiological development stages of crop growth from planting to harvest

  • Remote sensing data have been used for mapping land surface phenology (LSP) and relating to crop growth stages

  • Near-real-time mapping of crop phenology is still very challenging since remote sensing observations may not be sensitive to the change of crop growth stages

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Summary

Introduction

Crop phenology defines physiological development stages of crop growth from planting to harvest. Satellite remote sensing provides frequent observations of land surface properties, which can characterize crop and vegetation phenology. Remote sensing phenological dates are different from crop growth stages. The greenup event may be related to emergence, and dormancy onset may be related to harvest Their connections depend on crop types and the remote sensing phenology method used [12]. Remote sensing phenology or LSP detections only became applicable after daily satellite observations were available since 1981 from the Advanced Very HighResolution Radiometer (AVHRR) [16]. Retroactive LSP products are mainly used for research purposes They are not suitable for operational applications that need crop phenology information within the season, usually a few days or weeks after the change of crop growth stages. Opportunities, challenges, and future development for the near-real-time crop phenology mapping are discussed

Crop Phenology Mapping Methods
Applications Using Remote Sensing Phenology
Discussions
Summary
Disclosure
Findings
Conflicts of Interest

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