Quasi-HSL color space and its application: Sunlit and shaded component fractional cover estimation in vegetated ecosystem

• Quasi-HSL method is proposed for shadow fractional cover estimation in vegetated area. • The qHSL uses green, red, and NIR without blue band, decreasing atmospheric influence. • Two indices, HLI and SLI, are proposed based on hue, saturation, and lightness. • Fractional cover is estimated on a S2 MSI image and validated with UAV data. Sunlit and shaded components are commonly present in both airborne and satellite remote sensing images. In vegetated ecosystems, shaded component often result from sunlight being obstructed by topographic relief or canopy structures, and shaded component may impact plant growth, leaf photosynthesis, and ultimately carbon sequestration. To accurately estimate the fractional cover of the shaded and sunlit components, including both green and non-green vegetation within vegetated ecosystems, a novel method called the quasi-Hue-Saturation-Lightness (quasi-HSL) method is proposed in this study. Inspired by the RGB to HSL conversion, this method utilizes near-infrared, green, and red bands to compute hue (and normalized hue), saturation, and lightness. Subsequently, two indices, namely Hue-Lightness Index (HLI) and Saturation-Lightness Index (SLI), are introduced to construct a triangular space for estimating the fractional cover of the three components. Through unmanned aerial vehicle field experiments conducted in two forested areas, the accuracy of fractional cover estimation for three components reaches an R 2 value of 0.50–0.67. Furthermore, this fractional cover estimation approach can be extended to a four-component estimation, including sunlit green vegetation, sunlit non-green vegetation, shaded green vegetation, and shaded non-green vegetation. With this detailed fractional cover estimation in vegetated area, the fractional vegetation coverage can be retrieved. Cross-validated with the fractional vegetation coverage retrieved by NDVI, the accuracy reaches R 2 = 0.92. The advantages of the proposed method are (1) estimating fractional cover of shaded component without blue band, which is easily impacted by atmospheric conditions and sensor performance, and (2) differentiating the sunlit green and non-green vegetation components in the vegetated ecosystem.