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Contrary to conventional Tamm plasmon (TP) absorbers of which narrow absorptance peaks will shift toward short wavelengths (blueshift) as the incident angle increases for both transverse magnetic (TM) and transverse electric (TE) polarizations, here we theoretically and experimentally achieve nonreciprocal absorption in a planar photonic heterostructure composed of an isotropic epsilon-near-zero (ENZ) slab and a truncated photonic crystal for TM polarization. This exotic phenomenon results from the interplay between ENZ and material loss. And the boundary condition across the ENZ interface and the confinement effect provided by the TP can enhance the absorption in the ENZ slab greatly. As a result, a strong and nonreciprocal absorptance peak is observed experimentally with a maximum absorptance value of 93% in an angle range of 60∼70°. Moreover, this TP absorber shows strong angle-independence and polarization-dependence. As the characteristics above are not at a cost of extra nanopatterning, this structure is promising to offer a practical design in narrowband thermal emitter, highly sensitive biosensing, and nonreciprocal nonlinear optical devices.

Land use and land cover (LULC) changes in oases have been a topic of great interest due to the impacts of oases on ecosystem services in arid regions. The oasis that is along the Keriya River in southern Tarim Basin, northwest China, is in an ecologically fragile region and is thus very sensitive to human interference. In this study, the spatial and temporal changes in LULC in the middle reaches of the river were quantified and assessed by using GIS technology based on remote sensing images from 1995, 2005 and 2015. The results indicated that cropland expansion and grassland degradation were the dominant LULC changes, especially in the last decade. Throughout the study period, cropland areas increased by 6.51%, while grassland areas decreased by 30.98%. A buffer analysis along the main river channel was conducted to analyze the spatial LULC characteristics. The results showed that water areas, croplands and forests were predominantly distributed along the river (in the 0–10 km buffer). The majority of mid-density grasslands and low-density grasslands were distributed in the 10–20 km buffer, and high-density grasslands were mainly distributed in the 20–30 km buffer. The conversion rates in different buffers indicated that cropland expansion primarily occurred along the river, and grassland degradation was noted in the 10–30 km buffer. Landscape pattern changes were also analyzed to account for the structural LULC characteristics. The results that were deduced from the landscape pattern change analysis showed that the patch structures of forestland and cropland increased, and increasing fragmentation tendencies were found in the other LULC types. Moreover, a model was introduced to quantify the directions of LULC changes, and the results showed that the direction of LULC change in the oasis was declining, which represents an undesirable change in LULC. Socio-economic changes were also analyzed to explain the LULC changes. The results of this study contribute to the future management of the LULC in the oasis and the protection of the Keriya River ecosystem.

Spectroscopy is regarded as a quick and nondestructive method to classify and quantitatively analyze many elements of the soil. Visible and Near-infrared reflectance spectroscopy offers a conductive tool for investigating soil heavy metal pollution. The main goal of this work is to obtain spectral optimized indices (RSI, NPDI and NDSI) related to soil heavy metal Arsenic (As), to estimate the As contents in soil based on geographically weighted regression model (GWR), and to investigate the plausibility of using these spectral optimized indices to map the distribution of heavy metal Arsenic in the soil of coal mining areas. The spectral optimized indices (RSI, NPDI and NDSI) derived from the original and transformed reflectance (the reciprocal (1/R), logarithm (lg R ), logarithm-reciprocal (1/lg R ) and root mean square method ( R ) were used to construct the GWR models. Then, the variables (RSIs, NPDIs and NDIs) were applied in estimating the Arsenic (As) concentration and in the mapping of the As distribution in this study region. The NPDIs calculated by the original and transformed reflectance ( R , 1/ R , lg R , 1/lg R , and R ) indicated higher correlation coefficient values than NDSI and RSI. The highest correlation coefficient and lowest p -values ( r ≥0.73 and p =0.001) were found in thenear-infrared (NIR, 780–1100 nm) and shortwave infrared (SWIR, 1100–1935 nm). From the 4 prediction models (GWR) performances, it can be seen that Model-a ( R ) showed superior performance to the other three models (Model-b (1/ R ), Model-c ( R ) and Model-d (lg R )), and it has the highest validation coefficients ( R 2 = 0.831, RMSE =4.912 μg/g, RPD=2.321) and lowest AIC (Akaike Information Criterion) value (AIC=179.96). NPDI 1417 nm, 1246 nm is more sensitive and potential hyperspectral index for As in the study area. Thus, the two band optimized index (NPDI 1417 nm, 1246 nm ) might be recommended as an indicator for estimating soil As content. The hyperspectral optimized indices may help to quickly and accurately evaluate Arsenic contents in soil, and furthermore, the results provide theoretical and data support to access the distribution of heavy metal pollution in surface soil, promoting fast and efficient investigation of mining environment pollution and sustainable development of ecology.

The angle-sensitive photonic bandgap (PBG) is one of the typical features of one-dimensional photonic crystals. Based on the phase-variation compensation effect between the dielectric and hyperbolic metamaterials (HMMs), angle-insensitive PBGs can be realized in photonic hypercrystals. However, since hypercrystals are usually constructed using metal components, these angle-insensitive PBGs are mostly limited to narrow bandwidths in visible range. Here, we replace metal with indium tin oxide (ITO) to construct HMMs in the near-infrared range. In these ITO-based HMMs, we experimentally demonstrate the negative refraction of light in transverse magnetic polarization. With this HMM component, we realize a photonic hypercrystal with an angle-insensitive PBG in the wavelength range of 1.15–2.02 µm. These ITO-based hypercrystals with large angle-insensitive PBGs can find applications in near-infrared reflectors or filters.

Random sampling is an important approach to field vegetation surveys. However, sampling surveys in desert areas are difficult because determining an appropriate quadrat size that represent the sparse and unevenly distributed vegetation is challenging. In this study, we present a methodology for quadrat size optimization based on low-altitude high-precision unmanned aerial vehicle (UAV) images. Using the Daliyaboyi Oasis as our study area, we simulated random sampling and analyzed the frequency distribution and variation in the fractional vegetation cover (FVC) index of the samples. Our results show that quadrats of 50 m × 50 m size are the most representative for sampling surveys in this location. The method exploits UAV technology to rapidly acquire vegetation information and overcomes the shortcomings of traditional methods that rely on labor-intensive fieldwork to collect species-area relationship (SAR) data. Our method presents two major advantages: (1) speed and efficiency stemming from the application of UAV, which also effectively overcomes the difficulties posed in vegetation surveys by the challenging desert climate and terrain; (2) the large sample size enabled by the use of a sampling simulation. Our methodology is thus highly suitable for selecting the optimal quadrat size and making accurate estimates, and can improve the efficiency and accuracy of field vegetation sampling surveys.

Arid and semi-arid ecosystems exhibit a spatially complex biogeophysical structure. According to arid western special climate-vegetation characters, the fractional cover of photosynthetic vegetation (PV), non-photosynthetic vegetation (NPV), bare soil and water are unmixed, using the remote sensing spectral mixture analysis. We try the method to unmix the canopy funation structure of arid land cover in order to avoid the differentiation of regional vegetation system and the disturbance of environmental background. We developed a modified production efficiency model NPP-PEM appropriate for the arid area at regional scale based on the concept of radiation use efficiency. This model refer to the GLO-PEM and CASA model was driven with remotely sensed observations, and calculates not just the conversion efficiency of absorbed photosynthetically active radiation but also the carbon fluxes that determine net primary productivity (NPP). We apply and validate the model in the Kaxger and Yarkant river basins in arid western China. The NPP of the study area in 1992 and 1998 was estimated based on the NPP-PEM model. The results show that the improved PEM model, considering the photosynthetical activation of heterogeneous functional vegetation, is in good agreement with field measurements and the existing literature. An accurate agreement (R 2 = 0.85, P

This paper reports a geomorphologic landscape investigation, vegetation survey and soil sampling at 14 sites across the Gurbantunggut Desert between 87°37′09″-88°24′04″E and 44°14′04″-45°41′52″N. The study encountered 8 species of low trees and shrubs, 5 of perennial herbs, 8 of annual plants and 48 of ephemeral and ephemeroid plants. These species of plants represent one-third of the species found in the Gurbantunggut Desert, and their communities make up a large proportion of desert vegetation with great landscape significance. In the investigation we found that the plant communities are accordingly succeeded with the spatial variation of macro-ecoenvironment. Using Principal Component Analysis (PCA) and Correlation Analysis (CA) we found that the micro-ecoenvironment heterogeneity of aeolian sandy soil’s physical and chemical properties such as soil nutrient, soil moisture, soil salt, pH etc. only impacted the diversity of herb synusia (PIEherb) of the desert, with a negative correlation. Meanwhile, the impact of microhabitat on the plant community pattern with an antagonistic interaction made vegetation’s eco-distribution in a temporary equilibrium.

Firstly, an air passenger capacity investigation at the capital international airport is made, and a composite forecasting model based on total air passenger capacity is established, in which multiple regression and ARIMA model are parallel connection and their forecast results are series connection with BP neural network. Secondly, according to the average growth rate of air passenger capacity, all airlines are divided into 5 subareas, and the series connection model of ARIMA and BP neural network is established. Finally, short-term air passenger capacity at the capital international airport is forecasted by the composite models, and analyzed results show that the model based on air partition is more precise than the model based on total air passenger capacity, which is a kind of viable and practicable air passenger forecasting model.