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

IF 7.5 1区 地球科学 Q1 Earth and Planetary Sciences International Journal of Applied Earth Observation and Geoinformation Pub Date : 2024-12-05 DOI:10.1016/j.jag.2024.104298
Jia Tian, Qingjiu Tian, Suju Li, Qianjing Li, Sen Zhang, Shuang He
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Abstract

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 R2 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 R2 = 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.
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拟hsl色彩空间及其应用:植被生态系统中光照和阴影分量覆盖度估算
在航空和卫星遥感图像中,阳光照射和阴影部分通常都存在。在植被生态系统中,遮荫成分通常是由于地形起伏或冠层结构阻挡阳光的结果,遮荫成分可能影响植物生长、叶片光合作用和最终的碳固存。为了准确估计植被生态系统中遮阳和日照组分(包括绿色和非绿色植被)的覆盖度,本文提出了一种新的方法——准色度-饱和度-亮度(quasi- saturation - lightness, hsl)方法。受RGB到HSL转换的启发,该方法利用近红外,绿色和红色波段来计算色调(和归一化色调),饱和度和亮度。随后,引入Hue-Lightness Index (HLI)和Saturation-Lightness Index (SLI)两个指标,构建一个三角空间来估计这三个分量的分数覆盖度。通过在2个林区进行的无人机野外试验,3个分量的覆盖度估算精度R2值为0.50-0.67。此外,这种分数覆盖度估计方法可以扩展为四分量估计,包括阳光照射下的绿色植被、阳光照射下的非绿色植被、阴影下的绿色植被和阴影下的非绿色植被。利用这种详细的植被覆盖度估算方法,可以反演植被覆盖度。与NDVI反演植被覆盖度交叉验证,精度达到R2 = 0.92。该方法的优点是:(1)估算无蓝带遮挡成分的覆盖度分数,蓝带容易受到大气条件和传感器性能的影响;(2)区分植被生态系统中阳光照射下的绿色和非绿色植被成分。
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来源期刊
CiteScore
10.20
自引率
8.00%
发文量
49
审稿时长
7.2 months
期刊介绍: The International Journal of Applied Earth Observation and Geoinformation publishes original papers that utilize earth observation data for natural resource and environmental inventory and management. These data primarily originate from remote sensing platforms, including satellites and aircraft, supplemented by surface and subsurface measurements. Addressing natural resources such as forests, agricultural land, soils, and water, as well as environmental concerns like biodiversity, land degradation, and hazards, the journal explores conceptual and data-driven approaches. It covers geoinformation themes like capturing, databasing, visualization, interpretation, data quality, and spatial uncertainty.
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