Abstract
Aboveground biomass (AGB) is one of the key indicators of aboveground net primary productivity (ANPP). The aim of this study is to demonstrate the potential of hyperspectral remote sensing techniques to predict AGB in grasslands. In order to reach this goal, biomass properties with different ecological features and altitudes of 550 m, 1200 m, and 1400 m above sea level were investigated. Twenty-one biomass samples and hyperspectral measurements were collected from each region and a total of 63 samples were analyzed. Linear and nonlinear regression models were generated to analyze the relationships between biomass and hyperspectral vegetation indices (VIs). The results showed strong relationships between VIs and biomass variations. However, dense biomass samples indicated weaker relationships with VIs due to saturation phenomena. Findings based on the measured data showed that AGB (except dense biomass) can be estimated with high accuracy using hyperspectral vegetation indices.
Highlights
Grasslands are geographically unique and ecologically and agroeconomically significant, covering roughly 25% of the terrestrial landscape of the earth and sustaining a considerable amount of carbon
Suitable simple ratio indices (SRs) and normalized difference vegetation indices (NDVIs) for biomass estimation based on grassland characteristics The findings of this study show that the performance of SRs and NDVIs in biomass prediction is directly related to grassland structure (Figures 5 and 6)
Information on the productivity of grassland ecosystems can be monitored via biomass assessment
Summary
Grasslands are geographically unique and ecologically and agroeconomically significant, covering roughly 25% of the terrestrial landscape of the earth and sustaining a considerable amount of carbon. These valuable areas contribute greatly to biomass production and play an important role in biochemical cycles (Guo et al, 2005). Grassland areas are experiencing quick and significant modifications in composition, character, structure, and size driven by human-related activities, such as agricultural activities and cattle and sheep grazing. These drastic and continuous alterations widely affect the ecological and socioecological functioning of vegetative systems. The grasslands of Turkey are at risk of extensive modification due to human-related activities along with climatic variations. quantification and characterization of the types and conditions of grasslands are required for the sustainable use of such resources and for better understanding the impact of changes in these areas via technology-based approaches (May et al, 2010; Dusseux et al, 2015)
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