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<p>The convenience and reliability of crop growth research have been significantly enhanced by the synergy and application capabilities of multi-source satellite data. Consequently, a greater emphasis on evaluating the performance and application potential of these satellites is warranted. As suitable research subjects, two recently launched high-resolution Chinese satellites, equipped with WFV sensors sharing identical spatial resolution, were selected. This study focuses on winter wheat, comparing the consistency of GF-1 WFV_2 and GF-6 WFV data in band reflectivity. Furthermore, four vegetation indices were utilized to analyze the potential of these satellite data in studying crop growth parameters, including Leaf Area Index (LAI), coverage, chlorophyll content, and plant height. The primary conclusions are: (1) The coefficient of determination (<i>R</i><sup><i>2</i></sup>) for near-infrared, red, green, and blue band reflectivity between GF-1 WFV_2 and GF-6 WFV are 0.7008, 0.9520, 0.8764, and 0.8708, respectively, with better <i>R</i><sup><i>2</i></sup> values observed in the blue and green bands. (2) In terms of vegetation indices, NDVI and SRI exhibit greater consistency compared to CI<sub>green</sub> and ARVI. (3) For monitoring winter wheat vegetation growth parameters, GF-6 WFV-CI<sub>green</sub>, GF-1 WFV_2-SRI, and GF-1 WFV_2-SRI yield optimal results for LAI, coverage, and chlorophyll content, respectively, while GF-1 WFV_2-SRI performs best for height monitoring. (4) Through spectral data measurement and simulation, the potential impacts of spectral response functions and zenith angles on data discrepancies were analyzed.</p>

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Comparative Analysis of Application Between GF-1 WFV_2 and GF-6 WFV Image Data in Monitoring of Crop Physiological Parameters

  • 期刊论文

  • 发表日期：

    2025年2月11日

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  • Zhang Yuxun,
  • Lin Wenpeng,
  • Wang Lei,
  • Sun Yuan

摘要

The convenience and reliability of crop growth research have been significantly enhanced by the synergy and application capabilities of multi-source satellite data. Consequently, a greater emphasis on evaluating the performance and application potential of these satellites is warranted. As suitable research subjects, two recently launched high-resolution Chinese satellites, equipped with WFV sensors sharing identical spatial resolution, were selected. This study focuses on winter wheat, comparing the consistency of GF-1 WFV_2 and GF-6 WFV data in band reflectivity. Furthermore, four vegetation indices were utilized to analyze the potential of these satellite data in studying crop growth parameters, including Leaf Area Index (LAI), coverage, chlorophyll content, and plant height. The primary conclusions are: (1) The coefficient of determination (R2) for near-infrared, red, green, and blue band reflectivity between GF-1 WFV_2 and GF-6 WFV are 0.7008, 0.9520, 0.8764, and 0.8708, respectively, with better R2 values observed in the blue and green bands. (2) In terms of vegetation indices, NDVI and SRI exhibit greater consistency compared to CIgreen and ARVI. (3) For monitoring winter wheat vegetation growth parameters, GF-6 WFV-CIgreen, GF-1 WFV_2-SRI, and GF-1 WFV_2-SRI yield optimal results for LAI, coverage, and chlorophyll content, respectively, while GF-1 WFV_2-SRI performs best for height monitoring. (4) Through spectral data measurement and simulation, the potential impacts of spectral response functions and zenith angles on data discrepancies were analyzed.