Abstract
Leaf area index (LAI) is widely used for algorithms and modelling in the field of ecology and land surface processes. At a global scale, normalized difference vegetation index (NDVI) products generated by different remote sensing satellites, have provided more than 40 years of time series data for LAI estimation. NDVI saturation issues are reported in agriculture and forest ecosystems at high LAI values, creating a challenge when using NDVI to estimate LAI. However, NDVI saturation is not reported on LAI estimation in grasslands. Previous research implies that non-photosynthetic vegetation (NPV) reduces the accuracy of LAI estimation from NDVI and other vegetation indices. A question arises: is the absence of NDVI saturation in grasslands a result of low LAI value, or is it caused by NPV? This study aims to explore whether there is an NDVI saturation issue in mixed grassland, and how NPV may influence LAI estimation by NDVI. In addition, in-situ measured plant area index (PAI) by sensors that detect light interception through the vegetation canopy (e.g., Li-cor LAI-2000), the most widely used field LAI collection method, might create bias in LAI estimation or validation using NDVI. Thus, this study also aims to quantify the contribution of green vegetation (GV) and NPV on in-situ measured PAI. The results indicate that NDVI saturation (using the portion of NDVI only contributed by GV) exists in grassland at high LAI (LAI threshold is much lower than that reported for other ecosystems in the literature), and that the presence of NPV can override the saturation effects of NDVI used to estimate green LAI. The results also show that GV and NPV in mixed grassland explain, respectively, the 60.33% and 39.67% variation of in-situ measured PAI by LAI-2000.
Highlights
Leaf area index (LAI, see an acronym index in Table A1 from Appendix A) is defined as one-half of the total photosynthetic leaf area per ground surface unit in the horizontal direction [1,2]
Previous research indicates that large amounts of non-photosynthetic vegetation (NPV), reduce the accuracy for LAI estimation based on the vegetation indices extracted from optical satellite imagery, because a dead component accounts for a high portion of variations in Normalized difference vegetation index (NDVI) [31,32]
The question arises: is the absence of the NDVI saturation issue really due to a relatively low LAI value in grassland compared to other ecosystems, or is it caused by NPV? The answer remains unknown
Summary
Leaf area index (LAI, see an acronym index in Table A1 from Appendix A) is defined as one-half of the total photosynthetic leaf area (i.e., one-sided live green leaves in the canopy) per ground surface unit in the horizontal direction [1,2]. LAI is mostly estimated by these NDVI products for algorithms and modelling in ecology [1], agriculture [12,13,14], biogeochemistry [15], climate change [16,17], and land surface process research [18]. The NDVI saturation issue was mostly reported in agricultural studies [25] and the NDVI saturation threshold of LAI varies with different corps [26]. Previous research indicates that large amounts of non-photosynthetic vegetation (NPV), reduce the accuracy for LAI estimation based on the vegetation indices extracted from optical satellite imagery, because a dead component accounts for a high portion of variations in NDVI [31,32]. This study aims to explore whether there is an NDVI saturation issue in mixed grassland, and to evaluate the impact of NPV on LAI estimation, using NDVI
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