CARM30: China annual rapeseed maps at 30 m spatial resolution from 2000 to 2022 using multi-source data.

Rapeseed is a critical cash crop globally, and understanding its distribution can assist in refined agricultural management, ensuring a sustainable vegetable oil supply, and informing government decisions. China is the leading consumer and third-largest producer of rapeseed. However, there is a lack of widely available, long-term, and large-scale remotely sensed maps on rapeseed cultivation in China. Here this study utilizes multi-source data such as satellite images, GLDAS environmental variables, land cover maps, and terrain data to create the China annual rapeseed maps at 30 m spatial resolution from 2000 to 2022 (CARM30). Our product was validated using independent samples and showed average F1 scores of 0.869 and 0.971 for winter and spring rapeseed. The CARM30 has high spatial consistency with existing 10 m and 20 m rapeseed maps. Additionally, the CARM30-derived rapeseed planted area was significantly correlated with agricultural statistics (R2 = 0.65-0.86; p < 0.001). The obtained rapeseed distribution information can serve as a reference for stakeholders such as farmers, scientific communities, and decision-makers.

A Phase Canceling Technique to Improve SAW Duplexer Isolation.

Spectrum resources are becoming increasingly crowded, and the isolation interval between different systems is getting smaller and smaller. This puts forward higher requirements for the duplexer. The duplexer is an important part of the radio frequency front end, and the isolation requirement is becoming higher. This paper presents a phase canceling circuit to improve the performance of the duplexer to meet the requirement of the communication system for isolation. A phase canceling circuit is an effective method to enhance the isolation through use of a surface acoustic wave (SAW) on-chip circuit. It contains a duplexer and a branch. The branch is designed for diminishing the leakage signal of the duplexer. Compared with the leakage signal, the branch consists of two attenuators and a phase shifter to generate a signal which has equal extent and reverse phase. As a result, this method is capable of increasing the isolation of band 5 by 12 dB in the downlink frequency. Meanwhile, it neither affects other factors, such as insertion loss or return loss, nor increases the size of the chip. The phase canceling circuit is expected to promote the quality of duplexer to satisfy the strict requirements in 4G and 5G systems.

Spatial allocation of anthropogenic carbon dioxide emission statistics data fusing multi-source data based on Bayesian network.

A gridded social-economic data is essential for geoscience analysis and multidisciplinary application. Spatial allocation of carbon dioxide statistics data is an important issue in the context of global climate change, which involves the carbon emissions accounting and decomposition of responsibility for carbon emission reductions. In this research a new spatial allocation method for non-point source anthropogenic carbon dioxide emissions (ACDE) fusing multi-source data using Bayesian Network (BN) was introduced. In addition to common-used DMSP (Defense Meteorological Satellite Program), PD (population density) and GDP (Gross Domestic Production) data, the land cover and vegetation data was imported into the model as prior knowledge to optimize the model fitting. The prior knowledge here was based on the understanding that ACDE was dominated by human activities and has strong correlations with land cover and vegetation conditions. A 1 km gridded ACDE map integrated emissions form point-source and non-point source was generated and validated. The model predicts ACDE with high accuracies and great improvement can be observed when fusing land cover and vegetation as prior knowledge. The model can achieve successful statistics data downscaling on national scale provided adequate sample data are available, offering a novel method for ACDE accounting in China.

[Sensitivity of spring phenology to elevation in Qinling Mountains, China]. / 秦岭山区植被春季物候的海拔敏感性.

Vegetation phenology, a regular and periodic phenomenon in nature, is an important indicator for natural environment, especially climate change. The study of spatiotemporal variations of vegetation phenology is of great significance for monitoring the changes of terrestrial vegetation. In this study, the Savitzky-Golay (S-G) filtering method was used to reconstruct time-series MODIS enhanced vegetation index (EVI) data in the Qinling Mountains from 2001 to 2018. The dynamic threshold method was used to extract the spring phenological parameter (start of growth season, SOS). The correlation between multi-year mean SOS and interannual variation with altitude and slope was analyzed. The results showed that SOS was delayed by 1.82 d with every 100 m increase in altitude in the Qinling Mountains. The interannual change trends of SOS mainly concentrated in 0-5 d·(10 a)-1. The pixels with delaying trend were mainly distributed in low-altitude regions, with the delaying degree being gradually decreased with the elevation. The interannual change trend of SOS in high-altitude regions was more complex than that in lower-altitude regions. The multi-year average SOS in the northern slope was approximately 2.9 d earlier than that of the southern slope, whereas the southern slope had a more significant advancing trend. The interannual change trends of SOS in both north and south slopes showed a delaying trend in low-altitude, with little difference between north and south slopes. The advancing trend in middle and high altitude was significantly different.

Spatial-Temporal Dynamics of Cropping Frequency in Hubei Province over 2001-2015.

Mapping crop patterns with remote sensing data is of great importance for agricultural production, food security and agricultural sustainability. In this paper, a hierarchical clustering method was proposed to map cropping frequency from time-series Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Indices (EVI) data and the spatial and temporal patterns of cropping frequency from 2001 to 2015 in Hubei Province of China were analyzed. The results are as follows: (1) The total double crop areas decreased slightly, while total single crop areas decreased significantly during 2001 and 2015; (2) The transfer between double crop and single crop was frequent in Hubei with about 11~15% croplands changed their cropping frequency every 5 years; (3) The crop system has obvious regional differentiation for their change trend at the county level.

Microcystin Bioaccumulation in Freshwater Fish at Different Trophic Levels from the Eutrophic Lake Chaohu, China.

The spatial and temporal variations of microcystins (MCs) in fishes with different trophic levels were studied monthly in Lake Chaohu in 2014. MCs content in muscle was highest in phytoplanktivorous Hypophthalmichthys molitrix (H. molitrix), followed by omnivorous Carassius auratus (C. auratus), and was lowest in herbivorous Parabramis pekinensis (P. pekinensis) and carnivorous Coilia ectenes (C. ectenes). MCs concentration in liver was highest in C. auratus, followed by H. molitrix, and was lowest in P. pekinensis and C. ectene. The main uptake routes of MCs for C. auratus and H. molitrix were via the diet. The mechanism to counteract MCs had not been well developed in C. ectenes. H. molitrix and C. auratus from the western region as they had higher mean concentrations of MCs than fishes from the eastern region. The estimated daily intakes of MCs in 45.4% of muscle samples were higher than the provisional tolerable daily intake set by WHO.

[A new spectral similarity measure based on multiple features integration].

Spectral characterization and feature selection is the key to spectral similarity measure which is the basis of both quantitative analysis and accurate object identification for hyperspectral remote sensing. However, spectral similarity measures using only one spectral feature are usually ambiguous in their distinction of similarity. Multiple spectral features integration is needed for objective spectral discrimination. We present a new spectral similarity measure, Spectral Pan-similarity Measure (SPM), based on geometric distance, correlation coefficient and relative entropy. Spectral Pan-similarity Measure objectively quantifies differences between spectra in three spectral features, the vector magnitude, spectral curve shape and spectral information content. The performance of different spectral similarity measures is compared using USGS Mineral Spectral Library and real (i.e., Operational Modular Imaging Spectrometer, OMIS) hyperspectral image. The experimental results demonstrate that the new spectral similarity measure is more effective than the spectral similarity measure taking into account only one or two features both in spectral discriminatory power and spectral identification uncertainty.