Modified Multiple Spectrum-Based Vegetation Index (MMSVI): A Reflectance Index With High Spatiotemporal Generalization Ability

Vegetation indices (VIs) are valuable in numerous remote sensing fields. Nevertheless, it is difficult to accurately discern vegetation using VIs, causing by the effects of the shaded vegetation, saturation vegetation, synthetic turf stadiums, and colored steel tile. Measuring the spectral curves of shadows, synthetic turf stadiums, and colored steel tiles, we found that the interfering features can be suppressed by a formula composition, named the original multiple spectrum-based vegetation index (OMSVI). In addition, we integrated the antisaturation function into OMSVI to solve the band saturation issue, resulting in the improved multiple spectrum-based vegetation index (IMSVI). To address the structure saturation issue, the blue and red edge 1 band could be used to alter the denominator structure of IMSVI, thus obtaining the final modified multiple spectrum-based vegetation index (MMSVI). To demonstrate the generalization of the MMSVI, nine common VIs were compared in three large cities with diverse environments. The results of MMSVI showed that the vegetation extraction accuracy was stabilized at more than 90%, and the saturated leaf area index (SLAI) position continued to exceed 5.0, both of which were superior to the current VIs. In combination with a conventional optical sensor, it provided an innovative solution for monitoring vegetation in high-dynamic spaces, particularly in subtropical cities, where saturation issues are more prevalent.