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- W4306640273 abstract "The reliable estimation of aboveground biomass (AGB) plays a critical role in the carbon budget and eventually contributes to the global carbon cycle. Availability of forest inventory data and accurate estimation of aboveground biomass are two essential factors for this purpose. The harvesting process yields the most reliable biomass estimation, but it is expensive, labor intensive, and time consuming, and repeated assessments are not practically viable. Alternatively, optical remote sensing provides images that help estimate biomass over an area, though it suffers from cloud cover. However, the SAR data has an advantage over others as it can penetrate clouds. In this work, the aboveground biomass of Shorea robusta and Tectona grandis forest stands in the Katerniaghat Wildlife Sanctuary (KWS) was estimated by corresponding ground-based biomass data with TerraSAR-X satellite data, located in Uttar Pradesh, India. The sal and teak forests occur in expansive patches in KWLS and occupy nearly 60% of the total forest area, making it an ideal test site for this study. A semi-empirical model, water cloud model (WCM), was utilised for this study. WCM correlates mean backscatter coefficient values with the biophysical parameters such as volume, density, biomass, etc. The field-estimated aboveground biomass ranged from 150 to 729 Mg/ha and 14 to 208 Mg/ha for Shorea robusta and Tectona grandis species, respectively. The RMSE obtained for HH and HV sal plots were 17.88 Mg/ha and 4.43 Mg/ha, whereas for teak plots, they were 31.33 Mg/ha and 10.09 Mg/ha, respectively. The variation is mainly due to the difference in stand age and tree density of the forest type. According to the field conditions, the backscatter values range from −17.8 to −5.8 dB. The cross-polarised data exhibited the most robust trend, according to the backscattering analysis. The most notable trend was discovered in pure teak stands. The biomass saturation threshold for the X-band data may be more effective than previously anticipated." @default.
- W4306640273 created "2022-10-18" @default.
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- W4306640273 date "2022-10-17" @default.
- W4306640273 modified "2023-09-27" @default.
- W4306640273 title "Estimating Above-ground Biomass of Sal and Teak Forests Using TerraSAR-X and a Semi-Empirical Model in a Dense Tropical Forest" @default.
- W4306640273 doi "https://doi.org/10.1201/9781003268383-11" @default.
- W4306640273 hasPublicationYear "2022" @default.
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