Abstract. The Carnegie–Ames–Stanford Approach (CASA) model is widely used to estimate vegetation net primary productivity (NPP) at regional scales. However, the CASA is still driven by multisource data, e.g. satellite remote sensing (RS) data, and ground observations that are time-consuming to obtain. RS data can conveniently provide real-time regional information and may replace ground observation data to drive the CASA model. We attempted to improve the CASA model in this study using the Moderate Resolution Imaging Spectroradiometer (MODIS) RS products, the GlobeLand30 RS product, and the digital elevation model data derived from radar RS. We applied it to simulate the NPP of alpine grasslands in the Qinghai Lake basin, which is located in the northeastern Qinghai–Tibetan Plateau, China. The accuracy of the RS-data-driven CASA, with a mean absolute percent error (MAPE) of 22.14 % and root mean square error (RMSE) of 26.36 g C m−2 per month, was higher than that of the multisource-data-driven CASA, with a MAPE of 44.80 % and RMSE of 57.43 g C m−2 per month. The NPP simulated by the RS-data-driven CASA in July 2020 shows an average value of 108.01 ± 26.31 g C m−2 per month, which is similar to published results and comparable with the measured NPP. The results of this work indicate that simulating alpine grassland NPP with satellite RS data rather than ground observations is feasible. We may provide a workable reference for rapid simulation of grassland NPP to satisfy the requirements of accounting carbon stocks and other applications.
Multidrug-resistant bacteria caused by the unlimited overuse of antibiotics pose a great challenge to global health. An antibacterial method based on reactive oxygen species (ROS) is one of the effective strategies without inducing bacterial resistance. Owing to the ability of generating ROS, piezocatalytic material-mediated sonodynamic therapy (SDT) has drawn much attention. However, its major challenge is the low ROS generation efficiency in the piezocatalytic process due to the poor charge carrier concentration of piezoelectric materials. Vacancy engineering can regulate the charge density and largely promote ROS generation under ultrasound (US) irradiation. Herein, a US-responsive self-doped barium titanate with controlled oxygen vacancy (Vo) concentrations was successfully synthesized through a facile thermal reduction treatment at different temperatures (i.e., 350, 400, and 450 °C), and the corresponding samples were named as BTO-350, BTO-400, and BTO-450, respectively. Then, the effect of Vo concentrations on ROS generation efficiency during the piezocatalytic process was systematically studied. And BTO-400 was found to possess the highest piezocatalytic activity and excellent sonodynamic antibacterial performance against Escherichia coli and Staphylococcus aureus. Furthermore, its antibacterial mechanism was confirmed that the ROS generated under US could damage bacterial cell membrane and cause considerable leakage of cytoplasmic components and irreversible death of bacteria. Notably, the in vivo results illustrated that the BTO-400 could serve as an effective antibacterial agent and accelerate skin healing via SDT therapy. In all, the Vo defect-modified nano-BaTiO3 has a noticeable potential to induce a rapid and efficient sterilization as well as skin tissue repair by SDT.
Abstract. The Carnegie-Ames-Stanford Approach (CASA) model is widely used to estimate vegetation net primary productivity (NPP) at regional scale. However, the CASA is still driven by multi-source data, e.g. satellite remote sensing (RS) data, and ground observations that are time-consuming to obtain. RS data, can conveniently provide real-time surface information at the regional scale, thus replacing ground observation data to drive CASA model. We attempted to improve the CASA model in this study using DEM data derived from radar RS and RS products data generated from Moderate Resolution Imaging Spectroradiometer satellite sensor. We applied it to simulate the NPP of alpine grasslands in Qinghai Lake Basin, which is located in the northeastern Qinghai-Tibetan Plateau, China. The accuracy of the RS data driven CASA, with mean absolute percent error (MAPE) of 23.32 % and root mean square error (RMSE) of 26.26 g C•m-2•month-1, was higher than that of the multi-source data driven CASA, with MAPE of 49.08 % and RMSE of 65.21 g C•m-2•month-1. The NPP simulated by RS data driven CASA in July 2020 shows an average value of 110.17 ± 26.25 g C•m-2•month-1, which is similar to published results and comparable with the measured NPP. The results of this work indicate that simulating alpine grassland NPP with satellite RS data rather than ground observations is feasible. We may provide a workable reference for rapidly simulating grassland, farmland, forest, and other vegetation NPP to satisfy the requirements of precision agriculture, precision livestock farming, accounting carbon stocks, and other applications.
WebGIS has become one of the primary research directions in GIS. It is an efficient approach for the socialization of GIS. So it is important to research the structure and realization of WebGIS which is interoperable, transplantable, expansible and fit for various platforms. After analyzing and comparing the WebGIS system structure development and its main realization technologies, a realization technology based on J2EE is proposed.
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