A paper co-authored by Professor Kentato Takagi of Hokkaido University’s Field Science Center for Northern Biosphere has been published in Remote Sensing.
- Yuki Mizuno, Taiga Sasagawa, Yoshiyuki Takahashi, Reiko Ide, Toshiyuki Kobayashi, Hiroyuki Muraoka, Kentaro Takagi, Keisuke Ono and Kenlo Nishida Nasahara. Assessment of the Applicability of Hue from In Situ Spectral Measurements to Remote Sensing of Plant Phenology. Remote Sens. 2025, 17(16), 2767
DOI: https://doi.org/10.3390/rs17162767
Abstract
Climate change is accelerating, and the monitoring of plant phenology is becoming increasingly important. In response to this need, many vegetation indices (VIs) and analytical methods have been developed. However, many VIs are vulnerable to uncertainties caused by snowmelt, making them potentially unsuitable for monitoring spring phenology in forested regions where leaf flush (start of season, SOS) begins simultaneously with snowmelt. Although several VIs for snowy regions have been proposed, most of them were designed for tundra vegetation, such as grasslands. Currently, no VI or analytical method specifically suited for snowy forested regions has been firmly established. Similarly, there is still no well-established method for continuously monitoring autumn coloration. In this study, we propose the use of hue, one of the components of the HSV model, for remote sensing of plant phenology. Hue quantifies differences in object color and is expected to facilitate clearer distinction of snow influence. It may also enable accurate detection of canopy color transitions, such as autumn coloration. We evaluate the applicability of hue to remote sensing using in situ spectroradiometer observations collected from five sites of the Phenological Eyes Network (PEN), which represent a range of ecosystems—including forests, grasslands, and paddy fields—as well as the relative spectral response (RSR) of the Second-generation Global Imager (SGLI) onboard the GCOM-C satellite operated by JAXA (Japan Aerospace Exploration Agency). The results suggest that hue is more robust to snow-related uncertainties than traditional VIs (NDVI, EVI, CCI, NDGI) and may also be effective for quantifying autumn coloration. Hue is calculated solely from blue, green, and red reflectance, without relying on near-infrared (NIR) or shortwave infrared (SWIR) channels. Since blue, green and red channels are available on almost all optical satellite sensors, hue may offer broader applicability than many traditional VIs.
Keywords:
plant phenology; remote sensing; vegetation index (VI); hue; HSV model; spectroradiometer; spectral reflectance; Phenological Eyes Network (PEN)
Source: Remote Sensing 2025, 17, 2767. https://doi.org/10.3390/rs17162767
© 2025 by the authors. Licensed under CC BY 4.0.