Research Progresses of Crop Growth Monitoring Based on Synthetic Aperture Radar Data

Abstract

SignificanceCrop production is related to national food security, economic development and social stability, so timely information on the growth of major crops is of great significance for strengthening the crop production management and ensuring food security. The traditional crop growth monitoring mainly judges the growth of crops by manually observing the shape, color and other appearance characteristics of crops through the external industry, which has better reliability and authenticity, but it will consume a lot of manpower, is inefficient and difficult to carry out monitoring of a large area. With the development of space technology, satellite remote sensing technology provides an opportunity for large area crop growth monitoring. However, the acquisition of optical remote sensing data is often limited by the weather during the peak crop growth season when rain and heat coincide. Synthetic aperture radar (SAR) compensates well for the shortcomings of optical remote sensing, and has a wide demand and great potential for application in crop growth monitoring. However, the current research on crop growth monitoring using SAR data is still relatively small and lacks systematic sorting and summarization. In this paper, the research progress of SAR inversion of crop growth parameters were summarized through comprehensive analysis of existing literature, clarify the main technical methods and application of SAR monitoring of crop growth, and explore the existing problems and look forward to its future research direction.Progress]The current research status of SAR crop growth monitoring were reviewed, the application of SAR technology had gone through several development stages: from the early single-polarization, single-band stage, gradually evolving to the mid-term multi-polarization, multi-band stage, and then to the stage of joint application of tight polarization and optical remote sensing. Then, the research progress and milestone achievements of crop growth monitoring based on SAR data were summarized in three aspects, namely, crop growth SAR remote sensing monitoring indexes, crop growth SAR remote sensing monitoring data and crop growth SAR remote sensing monitoring methods. First, the key parameters of crop growth were summarized, and the crop growth monitoring indexes were divided into morphological indicators, physiological and biochemical indicators, yield indicators and stress indicators. Secondly, the core principle of SAR monitoring of crop growth parameters was introduced, which was based on the interaction between SAR signals and vegetation, and then the specific scattering model and inversion algorithm were used to estimate the crop growth parameters. Then, a detailed summary and analysis of the radar indicators mainly applied to crop growth monitoring were also presented. Finally, SAR remote sensing methods for crop growth monitoring, including mechanistic modeling, empirical modeling, semi-empirical modeling, direct monitoring, and assimilation monitoring of crop growth models, were described, and their applicability and applications in growth monitoring were analyzed.Conclusions and ProspectsFour challenges exist in SAR crop growth monitoring are proposed: 1) Compared with the methods of crop growth monitoring using optical remote sensing data, the methods of crop growth monitoring using SAR data are obviously relatively small. The reason may be that SAR remote sensing itself has some inherent shortcomings; 2) Insufficient mining of microwave scattering characteristics, at present, a large number of studies have applied the backward scattering intensity and polarization characteristics to crop growth monitoring, but few have applied the phase information to crop growth monitoring, especially the application study of polarization decomposition parameters to growth monitoring. The research on the application of polarization decomposition parameter to crop growth monitoring is still to be deepened; 3) Compared with the optical vegetation index, the radar vegetation index applied to crop growth monitoring is relatively less; 4 ) Crop growth monitoring based on SAR scattered intensity is mainly based on an empirical model, which is difficult to be extended to different regions and types of crops, and the existence of this limitation prevents the SAR scattering intensity-based technology from effectively realizing its potential in crop growth monitoring. Finally, future research should focus on mining microwave scattering features, utilizing SAR polarization decomposition parameters, developing and optimizing radar vegetation indices, and deepening scattering models for crop growth monitoring.

Keywords

• growth monitoring
• synthetic aperture radar (sar)
• radar vegetation index
• mechanistic modeling method