Normalizing the local incidence angle in sentinel-1 imagery to improve leaf area index, vegetation height, and crop coefficient estimations

Gregoriy Kaplan, Lior Fine, Victor Lukyanov, V. S. Manivasagam, Josef Tanny, Offer Rozenstein

Research output: Contribution to journalArticlepeer-review

23 Scopus citations

Abstract

Public domain synthetic-aperture radar (SAR) imagery, particularly from Sentinel-1, has widened the scope of day and night vegetation monitoring, even when cloud cover limits optical Earth observation. Yet, it is challenging to combine SAR images acquired at different incidence angles and from ascending and descending orbits because of the backscatter dependence on the incidence angle. This study demonstrates two transformations that facilitate collective use of Sentinel-1 imagery, regardless of the acquisition geometry, for agricultural monitoring of several crops in Israel (wheat, processing tomatoes, and cotton). First, the radar backscattering coefficient (σ0) was multiplied by the local incidence angle (θ) of every pixel. This transformation improved the empirical prediction of the crop coefficient (Kc), leaf area index (LAI), and crop height in all three crops. The second method, which is based on the radar brightness coefficient (β0), proved useful for estimating Kc, LAI, and crop height in processing tomatoes and cotton. Following the suggested transformations, R2 increased by 0.0172 to 0.668, and RMSE improved by 5 to 52%. Additionally, the models based on the suggested transformations were found to be superior to the models based on the dual-polarization radar vegetation index (RVI). Consequently, vegetation monitoring using SAR imagery acquired at different viewing geometries became more effective.

Original languageEnglish
Article number680
JournalLand
Volume10
Issue number7
DOIs
StatePublished - 1 Jul 2021
Externally publishedYes

Keywords

  • Crop coefficient
  • Incidence angle
  • Leaf area index
  • RVI
  • SAR
  • Sentinel-1

ASJC Scopus subject areas

  • Global and Planetary Change
  • Ecology
  • Nature and Landscape Conservation

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