Full year crop monitoring and separability assessment with fully-polarimetric L-band UAVSAR: A case study in the Sacramento Valley, California

Huapeng Li*, Ce Zhang, Shuqing Zhang, Peter M. Atkinson

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

36 Citations (Scopus)

Abstract

Spatial and temporal information on plant and soil conditions is needed urgently for monitoring of crop productivity. Remote sensing has been considered as an effective means for crop growth monitoring due to its timely updating and complete coverage. In this paper, we explored the potential of L-band fully-polarimetric Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) data for crop monitoring and classification. The study site was located in the Sacramento Valley, in California where the cropping system is relatively diverse. Full season polarimetric signatures, as well as scattering mechanisms, for several crops, including almond, walnut, alfalfa, winter wheat, corn, sunflower, and tomato, were analyzed with linear polarizations (HH, HV, and VV) and polarimetric decomposition (Cloude–Pottier and Freeman–Durden) parameters, respectively. The separability amongst crop types was assessed across a full calendar year based on both linear polarizations and decomposition parameters. The unique structure-related polarimetric signature of each crop was provided by multitemporal UAVSAR data with a fine temporal resolution. Permanent tree crops (almond and walnut) and alfalfa demonstrated stable radar backscattering values across the growing season, whereas winter wheat and summer crops (corn, sunflower, and tomato) presented drastically different patterns, with rapid increase from the emergence stage to the peak biomass stage, followed by a significant decrease during the senescence stage. In general, the polarimetric signature was heterogeneous during June and October, while homogeneous during March-to-May and July-to-August. The scattering mechanisms depend heavily upon crop type and phenological stage. The primary scattering mechanism for tree crops was volume scattering (>40%), while surface scattering (>40%) dominated for alfalfa and winter wheat, although double-bounce scattering (>30%) was notable for alfalfa during March-to-September. Surface scattering was also dominant (>40%) for summer crops across the growing season except for sunflower and tomato during June and corn during July-to-October when volume scattering (>40%) was the primary scattering mechanism. Crops were better discriminated with decomposition parameters than with linear polarizations, and the greatest separability occurred during the peak biomass stage (July-August). All crop types were completely separable from the others when simultaneously using UAVSAR data spanning the whole growing season. The results demonstrate the feasibility of L-band SAR for crop monitoring and classification, without the need for optical data, and should serve as a guideline for future research.

Original languageEnglish
Pages (from-to)45-56
Number of pages12
JournalInternational Journal of Applied Earth Observation and Geoinformation
Volume74
DOIs
Publication statusPublished - 1 Feb 2019

Bibliographical note

Funding Information:
This research was co-funded by the Jilin Province Science and Technology Development Program ( 20170520087JH , 20170204025SF ), the National Key Research and Development Program of China ( 2017YFB0503602 ), and the National Natural Science Foundation of China ( 41301465 , 41671397 ). We would like to thank the support from China Scholarship Council (CSC) (File No. 201704910192 ) during a visit of Huapeng Li to Lancaster Univerisity. We also thank Alaska Satellite Facility for the supply of UAVSAR data employed in this research.

Publisher Copyright:
© 2018 Elsevier B.V.

Keywords

  • Classification
  • Crop growth monitoring
  • Full-polarimetric SAR
  • Multi-temporal image
  • Polarimetric decomposition
  • Scattering mechanisms

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