A Radar Vegetation Index for Crop Monitoring Using Compact Polarimetric SAR Data

• Published in: IEEE transactions on geoscience and remote sensing 2020-09, Vol.58 (9), p.6321-6335
• Main Authors: Mandal, Dipankar, Ratha, Debanshu, Bhattacharya, Avik, Kumar, Vineet, McNairn, Heather, Rao, Yalamanchili S., Frery, Alejandro C.
• Format: Article
• Language: English
• Subjects: Agriculture; Canopies; Canopy; Circular polarization; Compact-pol; Computer simulation; Constellations; crop; Crop growth; Crops; Data; Depolarization; Distance; geodesic distance (GD); Indexes; Moisture content; Monitoring; Plant growth; Polarization; Radar; Radar data; Radar polarimetry; Radarsat; RADARSAT Constellation Mission (RCM); Regression analysis; SAR (radar); Scattering; Similarity; Similarity measures; Soil; Soil moisture; Soybeans; Synthetic aperture radar; Vegetation; Vegetation index; Vegetation mapping; Water content; Wheat
• ISSN: 0196-2892; 1558-0644
• DOI: 10.1109/TGRS.2020.2976661

Crop growth monitoring using compact-pol synthetic aperture radar (CP-SAR) data is gaining attention with the rapid advancements toward operational applications. In this article, we propose a vegetation index for compact polarimetric (CP) SAR data [compact-pol radar vegetation index (CpRVI)]. The CpRVI is derived using the concept of a geodesic distance between the Kennaugh matrices projected on a unit sphere. This distance is utilized to compute a similarity measure between the observed Kennaugh matrix and the Kennaugh matrix of an ideal depolarizer (a realization of vegetation canopy). The similarity measure is then modulated with a scaled quantity derived from the scattering power ratio of the same and opposite sense polarization with respect to the transmitted circular polarization. In this article, we utilize time-series-simulated RADARSAT Constellation Mission (RCM) compact-pol SAR data (RH-RV) obtained from the full-pol RADARSAT-2 observations during the soil moisture active passive (SMAP) validation experiment 2016 (SMAPVEX16-MB) campaign in Manitoba, Canada, to assess the proposed vegetation index. Among the various crops grown in this region, in particular, we analyze the growth stages of wheat and soybean due to their different canopy structures. A temporal analysis of the proposed CpRVI with crop biophysical parameters [the plant area index (PAI) and vegetation water content (VWC)] at different phenological stages confirms the trend of CpRVI with the plant growth. Nevertheless, variations of CpRVI values are apparent with different plant densities for both the crop types. Also, the linear regression analysis confirms that the CpRVI values significantly correlate with PAI ( r = 0.72 and 0.85) and VWC ( r = 0.62 and 0.75) for both wheat and soybean. We observed good retrieval of PAI and VWC for both wheat and soybean.