Early Season Winter Wheat Identification Using Sentinel -1 Synthetic Aperture Radar (Sar) and Optical Data

Early season crop identification is important for food security and economic stability. The USDA NASS uses optical data to provide acreage estimates, each June, to the NASS Agricultural Statistics Board. However, early season crop identification is difficult using optical data alone, because imagery is frequently cloudy during the spring. The purpose of this study is to determine whether using SAR and SAR texture can improve early season winter wheat identification compared to optical data alone. Study areas in the Missouri "Bootheel" (2017 growing season) and Northwest Texas (2018 growing season), United States (U.S.) are selected. The SAR data used in this study are Sentinel-1. Optical data include: Landsat 8, Disaster Monitoring Constellation, and Sentinel-2. Study results show that optical data with SAR achieved the highest winter wheat accuracies, 7.7% higher than optical data alone, in Missouri. Optical with SAR and SAR texture resulted in improved accuracies over optical alone, but only marginally, in Texas. These results indicate that optical and SAR, used together, can potentially improve early season crop identification.

• Publication year

  2019

• Venue

  IEEE International Geoscience and Remote Sensing Symposium

• Publication date

  2019-07-01

• Fields of study

  Agricultural and Food Sciences, Computer Science, Environmental Science

• Identifiers
  DOI 10.1109/IGARSS.2019.8898511
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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