Gravimetric Vegetation Water Content Estimation for Corn Using L-Band Bi-Angular, Dual-Polarized Brightness Temperatures and Leaf Area Index

Qi Wang,Zhongjun Zhang,Shaojie Zhao,Linna Chai

doi:10.3390/rs70810543

Abstract

In this study, an algorithm to retrieve the gravimetric vegetation water content (GVWC, %) of corn was developed. First, the method for obtaining the optical depth from L-band (1.4 GHz) bi-angular, dual-polarized brightness temperatures (TB) for short vegetation was investigated. Then, the quantitative relationship between the corn optical depth, corn GVWC and corn leaf area index (LAI) was constructed. Finally, using the Polarimetric L-band Microwave Radiometer (PLMR) airborne data in the 2012 Heihe Watershed Allied Telemetry Experimental Research (HiWATER) project, the Global Land Surface Satellite (GLASS) LAI product, the height and areal density of the corn stalks, the corn GVWC was estimated (corn GLASS-GVWC). Both the in situ measured corn GVWC and the corn GVWC retrieved based on the in situ measured corn LAI (corn LAINET-GVWC) were used to validate the accuracy of the corn GLASS-GVWC. The results show that the GVWC retrieval method proposed in this study is feasible for monitoring the corn GVWC. However, the accuracy of the retrieval results is highly sensitive to the accuracy of the LAI input parameters.

Highlights

Vegetation water content (VWC) is one of the most important parameters for evaluating the growth of vegetation
The results show that the gravimetric vegetation water content (GVWC) retrieval method proposed in this study is feasible for monitoring the corn GVWC
The corn Global Land Surface Satellite (GLASS)-GVWC of each pixel was validated by coincident measurements of the corresponding ground sampling points on the day of the Polarimetric L-band Microwave Radiometer (PLMR) flights

Summary

Introduction

Vegetation water content (VWC) is one of the most important parameters for evaluating the growth of vegetation. VWC has been widely used to monitor agricultural conditions, estimate biomass, etc. VWC is a key parameter for retrieving soil moisture from active and passive microwave remote sensing data [3]. Developing a feasible VWC retrieval method is important for agricultural production, soil moisture monitoring, and biomass estimation. Many methods to retrieve VWC from visible- and infrared-band data are based on selecting bands that are the most sensitive to water content to construct vegetation moisture indices that can directly reflect the VWC. Optical remote sensing data often contains only information for the vegetation canopy. Passive microwave remote sensing is an effective technique for monitoring land surface parameters because of its comprehensive, macro-scale, efficient, and real-time observations

Methods

Results

Discussion

Conclusion