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May 29, 2026Remote Sensing0 citationsOpen Access

Multi-Context Validation of Global Fractional Vegetation Cover Products in Croplands Using Multi-Source Crop FVC References

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LXLili XuCentral China Normal UniversityYQYelu QinCentral China Normal UniversityTCTao ChengNanjing Agricultural University

Key Points

  • This research aims to validate global fractional vegetation cover products for croplands using a multi-source dataset.
  • Compiled a global CropFVC reference dataset from 2000-2024, integrating various international networks and new observations.
  • Organized references into three validation contexts to assess product behavior under different conditions.
  • Conducted spatio-temporal analysis at the KONZ site to confirm consistency in observed behavior patterns.
  • Products consistently overestimated CropFVC under dense canopy and displayed reduced differences at low FVC levels.
  • Peak-season deviations reflected shared product behavior rather than site-specific uncertainties.
  • Crop-specific validation indicated clearer responses, with predictive difficulty ranking as winter wheat > maize > rice > soybean.

Abstract

Fractional Vegetation Cover of Crops (CropFVC) is a critical canopy parameter for monitoring crop growth, yet the behavior of widely used global FVC products (GLASS, GEOV1, GEOV2, and GEOV3) over croplands remains insufficiently understood due to fragmented validation references and limited crop-specific assessments. This study compiled a multi-source global CropFVC reference dataset (2000–2024) by integrating five international validation networks, the literature-derived samples, and newly acquired UAV and Jilin-1 satellite-derived CropFVC samples from China in 2024. The references were organized into three complementary validation contexts (V1~V3) to examine product behavior under different temporal coverage, crop purity, and reference conditions, together with spatio-temporal observations at the KONZ site. Results show that (1) across validation contexts, the evaluated products showed consistent behavior patterns, including shared overestimation under dense canopy conditions and reduced differences at low FVC levels; (2) spatio-temporal analysis at the KONZ site confirmed that peak-season deviations reflect shared response behavior rather than site-specific reference uncertainties; (3) historical mixed references (V1~V2) showed similar bias structures, whereas crop-specific validation (V3) preliminary revealed clearer crop-dependent responses, with predictive difficulty following winter wheat > maize > rice > soybean and improved stability after integrating 2024 observations. The integration of recent high-resolution crop observations expands existing global CropFVC references and enables behavior-oriented interpretation of global FVC products beyond simple accuracy ranking, providing an updated validation perspective for future development and application of global CropFVC products in agricultural monitoring.

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Cite This Study

Xu et al. (2026) studied this question.

synapsesocial.com/papers/6a192eb9fab5b468c4417fbdhttps://doi.org/10.3390/rs18111727
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