5 research outputs found
Using Artificial Neural Networks to Produce High-Resolution Soil Property Maps
High-resolution maps of soil property are considered as the most important inputs for decision support and policy-making in agriculture, forestry, flood control, and environmental protection. Commonly, soil properties are mainly obtained from field surveys. Field soil surveys are generally time-consuming and expensive, with a limitation of application throughout a large area. As such, high-resolution soil property maps are only available for small areas, very often, being obtained for research purposes. In the chapter, artificial neural network (ANN) models were introduced to produce high-resolution maps of soil property. It was found that ANNs can be used to predict high-resolution soil texture, soil drainage classes, and soil organic content across landscape with reasonable accuracy and low cost. Expanding applications of the ANNs were also presented
Zoning Prediction and Mapping of Three-Dimensional Forest Soil Organic Carbon: A Case Study of Subtropical Forests in Southern China
Accurate soil organic carbon (SOC) maps are helpful for guiding forestry production and management. Different ecological landscape areas within a large region may have different soil–landscape relationships, so models specifically for these areas may capture these relationships more accurately than the global model for the entire study area. The aim of this study was to investigate the role of zonal modelling in predicting forest SOC and to produce highly accurate forest SOC distribution maps. The prediction objects were SOC at five soil depths (0–20, 20–40, 40–60, 60–80, and 80–100 cm). First, the forest type map and soil texture class map were used to divide the relative homogeneous regions in Shaoguan City, Guangdong Province, China. Second, seven terrain variables derived from a 12.5-m digital elevation model (DEM) and five vegetation variables generated from 10-m Sentinel-2 remote sensing images were used as predictors to develop regional artificial neural network (ANN) models for each homogeneous region, as well as a global ANN model for the entire study area (1000 sample points). Finally, 10-fold cross-validation was used to assess the ANN prediction model performance, and independent validation was used to evaluate the produced forest SOC prediction maps (194 additional samples). The cross-validation results showed that the accuracies of the regional models were better than that of the global model. Independent validation results also showed that the precision (R2) of 0- to 100-cm forest SOC maps generated by forest type modelling had an improvement of 0.05–0.15, and that by soil texture class modelling had an improvement of 0.07–0.13 compared to the map generated by the global model. In conclusion, delineating relatively homogeneous regions via simple methods can improve prediction accuracy when undertaking soil predictions over large areas, especially with complex forest landscapes. In addition, SOC in the study area is generally more abundant in broadleaf forest and clay areas, with overall levels decreasing with soil depth. Accurate SOC distribution information can provide references for fertilization and planting. Plants with particularly high soil fertility requirements may perhaps be planted in broadleaf forests or clay areas, and plants with particularly developed roots may require furrow application of a small amount of SOC
The complete chloroplast genome sequence of Butea monosperma (Fabaceae)
Butea monosperma, an importantmedicinal plantin Fabaceae, is mainly distributed in southern Asia. In this study, we reported the complete chloroplast (cp) genome of B. monosperma assembled with Illumina sequencing data. The whole cp genome of this species is 151,925 bp in length, consisting of two inverted repeat regions (IR, 25,083 bp), one large single-copy region (LSC, 83,541 bp), and one small single-copy region (SSC, 18,218 bp).A total of 128 genes were annotated for the chloroplast genome, including 83 protein-coding genes, 37 tRNAs and 8 rRNAs. Phylogenetic analysis indicated that B. monosperma was closely related to the genus Lespedeza
Single-Nanoparticle Plasmonic Electro-optic Modulator Based on MoS<sub>2</sub> Monolayers
The manipulation
of light in an integrated circuit is crucial for
the development of high-speed electro-optic devices. Recently, molybdenum
disulfide (MoS<sub>2</sub>) monolayers generated broad interest for
the optoelectronics because of their huge exciton binding energy,
tunable optical emission, direct electronic band-gap structure, <i>etc.</i> Miniaturization and multifunctionality of electro-optic
devices further require the manipulation of light–matter interaction
at the single-nanoparticle level. The strong exciton–plasmon
interaction that is generated between the MoS<sub>2</sub> monolayers
and metallic nanostructures may be a possible solution for compact
electro-optic devices at the nanoscale. Here, we demonstrate a nanoplasmonic
modulator in the visible spectral region by combining the MoS<sub>2</sub> monolayers with a single Au nanodisk. The narrow MoS<sub>2</sub> excitons coupled with broad Au plasmons result in a deep
Fano resonance, which can be switched on and off by applying different
gate voltages on the MoS<sub>2</sub> monolayers. A reversible display
device that is based on this single-nanoparticle modulator is demonstrated
with a heptamer pattern that is actively controlled by the external
gates. Our work provides a potential application for electro-optic
modulation on the nanoscale and promotes the development of gate-tunable
nanoplasmonic devices in the future
Direct observation of ultrafast plasmonic hot electron transfer in the strong coupling regime
Achieving strong coupling between plasmonic oscillators can significantly modulate their intrinsic optical properties. Here, we report the direct observation of ultrafast plasmonic hot electron transfer from an Au grating array to an MoS2 monolayer in the strong coupling regime between localized surface plasmons (LSPs) and surface plasmon polaritons (SPPs). By means of femtosecond pump-probe spectroscopy, the measured hot electron transfer time is approximately 40 fs with a maximum external quantum yield of 1.65%. Our results suggest that strong coupling between LSPs and SPPs has synergetic effects on the generation of plasmonic hot carriers, where SPPs with a unique nonradiative feature can act as an ‘energy recycle bin’ to reuse the radiative energy of LSPs and contribute to hot carrier generation. Coherent energy exchange between plasmonic modes in the strong coupling regime can further enhance the vertical electric field and promote the transfer of hot electrons between the Au grating and the MoS2 monolayer. Our proposed plasmonic strong coupling configuration overcomes the challenge associated with utilizing hot carriers and is instructive in terms of improving the performance of plasmonic opto-electronic devices.MOE (Min. of Education, S’pore)Published versio