Calculation and Analysis of the Industrial Green Development Index in Hunan Province

In order to realize the purpose of human sustainable development,green development has become a dominant trend in contemporary society. ＂ Green Hunan＂ is the primary slogan of Hunan＇s four cards. Thus,in recent years,what is the practice result of Hunan＇s green development？ Based on the concept of industrial green development index,we selected the related panel data from 14 different cities of Hunan Province in 2012. The energy consumption and carbon emissions were also selected as input indexes,and GDP of secondary industry was used as the output index to build the industrial green development index. The CRS model of DEA was used to calculate and sequence the industrial green development indexes of 14 cities in Hunan Province.

Recent Advances in Design Strategies and Multifunctionality of Flexible Electromagnetic Interference Shielding Materials

With rapid development of 5G communication technologies,electromagnetic interference(EMI)shielding for electronic devices has become an urgent demand in recent years,where the development of corresponding EMI shielding materials against detrimental electromagnetic radiation plays an essential role.Meanwhile,the EMI shielding materials with high flexibility and functional integrity are highly demanded for emerging shielding applications.Hitherto,a variety of flexible EMI shielding materials with lightweight and multifunctionalities have been developed.In this review,we not only introduce the recent development of flexible EMI shielding materials,but also elaborate the EMI shielding mechanisms and the index for"green EMI shielding"performance.In addition,the construction strategies for sophisticated multifunctionalities of flexible shielding materials are summarized.Finally,we propose several possible research directions for flexible EMI shielding materials in near future,which could be inspirational to the fast-growing next-generation flexible electronic devices with reliable and multipurpose protections as offered by EMI shielding materials.

Automatic Generation of Water Masks from RapidEye Images

Water is a very important natural resource and it supports all life forms on earth. It is used by humans in various ways including drinking, agriculture and for scientific research. The aim of this research was to develop a routine to automatically extract water masks from RapidEye images, which could be used for further investigation such as water quality monitoring and change detection. A Python-based algorithm was therefore developed for this particular purpose. The developed routine combines three spectral indices namely Simple Ratios (SRs), Normalized Green Index (NGI) and Normalized Difference Water Index (NDWI). The two SRs are calculated between the NIR and green band, and between the NIR and red band. The NGI is calculated by rationing the green band to the sum of all bands in each image. The NDWI is calculated by differencing the green to the NIR and dividing by the sum of the green and NIR bands. The routine generates five intermediate water masks, which are spatially intersected to create a single intermediate water mask. In order to remove very small waterbodies and any remaining gaps in the intermediate water mask, morphological opening and closing were performed to generate the final water mask. This proposed algorithm was used to extract water masks from some RapidEye images. It yielded an Overall Accuracy of 95% and a mean Kappa Statistic of 0.889 using the confusion matrix approach.

Green UHPLC Method for Simultaneous Determination of Febuxostat and Diclofenac in Pharmaceutical Dosage Form and Human Plasma

Eco-friendly Ultra-high-performance liquid chromatography (UHPLC) with green aqueous-organic mobile phase was applied for the simultaneous determination of febuxostat (FEB) and diclofenac (DIC) with the composition of water:ethanol (85:15 v/v) utilizing phenomenex Kinetex C18 column (4.6 × 100 mm 2.6 μm), flow rate 1 ml/min and UV detection at 280 nm with linear ranges of 0.4 - 4.0 μg/mL and 0.5 - 5.0 μg/mL for FEB and DIC, respectively. The proposed method was also successfully applied to analyze the two drugs in pharmaceutical dosage form and human plasma. The results obtained were validated and statistically analyzed and found to be in accordance with those given by reported methods. Moreover, the greenness of the developed method is assessed using suitable analytical Eco-Scale and GAPI tools and comparison with the previously published methods have been carried out to indicate the priority of the proposed method. UHPLC is considered eco-friendly method regarding uses of safe solvents, simple, accurate and short time of analysis.

An effective Building Neighborhood Green Index model for measuring urban green space

Urban green space forms an integral part of urban ecosystems.Quantifying urban green space is of substantial importance for urban planning and development.Considering the drawbacks of previous urban green space index models,which established either through a grid method or green distribution,and the difficulty of the validation process of earlier urban green space index models,this study exploits the advantages of multisource high-resolution remote sensing data to establish a Building Neighborhood Green Index(BNGI)model.The model which analyzes the spatial configuration of built-up areas and the vegetation is based on the building-oriented method and considers four parameters–Green Index(GI),proximity to green,building sparsity,and building height.Comparing BNGI with GI in different types of characteristic building regions,it was found that BNGI evaluates urban green space more sensitively.It was also found that high-rise low-sparsity area has a lower mean value of BNGI(0.56)as compared with that of low-rise low-sparsity neighborhood(0.62),whereas mean GI(0.24)is equal for both neighborhoods.Taking characteristics of urban building and green types into consideration,BNGI model can be effectively used in many fields such as land suitability analysis and urban planning.

Quantification of urban greenery using hemisphere-view panoramas with a green cover index

Urban greenery has positive impacts on the well-being of residents and provides vital ecosystem services.A quantitative evaluation of full-view green coverage at the human scale can guide green space planning and management.We developed a still camera to collect hemisphere-view panoramas(HVPs)to obtain in situ heterogeneous scenes and established a panoramic green cover index(PGCI)model to measure human-scale green coverage.A case study was conducted in Xicheng District,Beijing,to analyze the quantitative relationships of PGCI with the normalized difference vegetation index(NDVI)and land surface temperature(LST)in different land use scenarios.The results show that the HVP is a useful quantization tool:(1)the method adaptively distinguishes the green cover characteristics of the four functional areas,and the PGCI values are ranked as follows:recreational area(29.6)>residential area(19.0)>traffic area(15.9)>commercial area(12.5);(2)PGCI strongly explains NDVI and LST,and for each unit(1%)increase in PGCI,NDVI tends to increase by 0.007,and(3)LST tends to decrease by 0.21 degrees Celsius.This research provides government managers and urban planners with tools to evaluate green coverage in complex urban environments and assistance in optimizing human-scale greenery and microclimate.

Dataset of the mountain green cover index(SDG15.4.2)over the economic corridors of the Belt and Road Initiative for 2010-2019

Mountains are undergoing widespread changes caused by human activities and climate change.Given the importance of mountains,the protection and sustainable development of mountain ecosys-tems have been listed as the goals of the United Nations 2030 Sustainable Development Agenda.As one of the indicators,the Mountain Green Cover Index(MGCI)datasets can provide consis-tent and comparable status of green vegetation in mountainous areas,which can support the mapping of heterogeneous mountain ecosystem health and monitoring changes over time.The produc-tion of explicitly high-spatial-resolution MGCI datasets is therefore urgently needed to support the protection measures at subnational and multitemporal scales.In this paper,the MGCI datasets with 500-meter spatial resolutions,covering the economic corridors of the Belt and Road Initiative(BRI),were developed for 2010 to 2019 based on all available Landsat-8 data and the Google Earth Engine cloud computing platform.The validation of green vegeta-tion cover with the ground-truth samples indicated that the data-sets can achieve an overall accuracy of 94.06%,with well-detailed spatial and temporal variations.The archived datasets include the MGCI of each BRI economic corridor,matched to a geospatial layer denoting the economic corridor boundaries.The essential informa-tion of the datasets and their limitations,along with the production flow,were described in this paper.