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Early or in-season crop type mapping using remote sensing data is important for crop managements to maximize crop yield. Existing remote sensing-based approaches in the literature rely mainly on the timing and temporal frequency of satellite data acquisition during a growing season to obtain optimal identification feature (OIF) to complete crop mapping. At present, the optimal features for mapping crop types are commonly generated by using different feature selection methods, and thereby are not generic in nature. In this paper, a novel approach based on the OIF knowledge graph is proposed for identification of crop types within the crop growing season. The concept of OIF was proposed based on the one-class classification and optimization theory, which relates a specific crop type to its OIF. The OIF knowledge graph can be created to describe the seasonal trend of OIF in a season. Eventually, the OIF knowledge graphs can be incorporated into the moment-preserving segmentation method to automatically identify crop types within the growing season. To evaluate the performance of the new method, crop mapping was conducted using 2019 Sentinel-2 data in Heilongjiang province, China, and Illinois, USA, respectively. Results demonstrate that integrating the OIF knowledge graph and moment-preserving thresholding method is effective in identifying crop types without ground-truth data. The overall accuracy higher than 90 % (Kappa coefficient greater than 0.90), and the producer's accuracies for corn, soybean, and rice are generally greater than 93 % in Heilongjiang province. The proposed approach has the advantage of simplifying crop identification process while maintaining a satisfactory identification accuracy in shorter time than conventional methods. [ABSTRACT FROM AUTHOR]

• First experimental verification for synthesizing crystalline cellulose nanoribbon from inexpensive starch in one pot by two phosphorylases. • Degree of polymerization of insoluble synthetic CCNR was affected by the primer concentration based on the fixed concentration of maltodextrin. • CCNR can be used as a Pickering emulsions stabilizer and showed excellent emulsifiability. Nanocellulose has many promising applications such as a green ingredient for Pickering emulsion. Traditional strategies to produce nanocellulose, which are acid or enzymatic hydrolysis and mechanical methods on natural complicated cellulose, are hard to control and can result in significant pollutants during the processes. Herein, we demonstrated a facile and sustainable method for the biocatalytic production of insoluble synthetic crystalline cellulose nanoribbon (CCNR) from cheap maltodextrin by coupling α-glucan phosphorylase (αGP) and cellodextrin phosphorylase (CDP) using cellobiose as a primer. And by optimizing the combination of different αGP and CDP, it turned out that the optimal enzyme combination is αGP from Thermotoga maritime and CDP from Clostridium thermocellum , in which CDP was attached to a family 9 cellulose-binding module. The product yield and degree of polymerization (DP) of insoluble synthetic CCNR was affected by the primer concentration at a fixed concentration of maltodextrin. After optimization of reaction conditions, the highest product yield of insoluble synthetic CCNR was 44.92 % and the highest DP of the insoluble synthetic CCNR was 24 from 50 g 1−1 maltodextrin. This insoluble synthetic CCNR can be used as a Pickering emulsions stabilizer, showing excellent emulsifiability. This study provides a promising alternative for cost-efficient production of insoluble synthetic CCNR which was used as a green emulsion stabilizer. [ABSTRACT FROM AUTHOR]

This study presents a novel approach in which a dual network (DN) composite, comprising polyvinyl alcohol (PVA) and ribbon-like nanocellulose (RC), was synthesized in one step using the volume exclusion effect involved in enzyme-catalyzed cellulose synthesis. Additionally, the impact of PVA as a crowding reagent during enzymatic catalysis on the in situ formation of nanocellulose and its resulting aspect ratio was explored. In contrast, the other two composites were created by incorporating enzyme-catalyzed synthetic block cellulose (BC) and its acid-hydrolyzed regenerated disc-shaped cellulose (DC) into the PVA. Subsequently, the mechanism by which three distinct types of nanocellulose, varying in morphology and size, was explored to elucidate their contributions to enhancing the properties of PVA. The results demonstrated that PVA/RC outperformed PVA/BC and PVA/DC. The elevated aspect ratio and intricate network structure of RCs not only significantly bolster the mechanical robustness of PVA/RC, leading in an 86.40 % surge in tensile strength and a remarkable 277.03 % rise in tensile modulus in comparison to pure PVA, but also induce a slight enhancement in elongation at break. Moreover, the thermal stability and biodegradability of PVA/RC was enhanced. Collectively, this study introduces an innovative strategy for the efficient fabrication of biodegradable composites with enhanced properties. [Display omitted] [ABSTRACT FROM AUTHOR]

• The community livability evaluation is quantitative, practical and fine-grained. • The evaluation criteria span dimensions of environment, traffic and population. • Remote sensing, surface observation and geospatial big data are used. • Most communities are distributed within the central and marginal urban areas. • Communities in urban area tend to have robustly high livability. Effective evaluation of community livability is in urgent need to avoid increased livability at the expense of sustainability. However, studies concerning community livability evaluation were still conceptual, qualitative or conducted at city or regional scales. The availability of abundant, fine-grained, and multi-source data in the big data era laid the foundation for comprehensive livability evaluation at much finer scales. This paper proposed a quantitative and practical method for up-to-date livability evaluation at individual community scale in China. Nine evaluation criteria were identified spanning dimensions of environment, traffic, convenience, and population. These criteria were calculated respectively from remote sensing, surface observation and geospatial big data. The Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) was applied for community livability evaluation, and the uncertainty and sensitivity of evaluation results were assessed. The livability evaluation in the case study area of Haidian District, Beijing, China demonstrated the practicality and effectiveness of the framework. A total number of 1242 communities in Haidian District were evaluated. Communities in urban area were generally associated with higher evaluation scores and lower uncertainties than those in rural area. The careful selection of criteria weights with high sensitivity, i.e., green space coverage within community and driving time to schools, can potentially significantly reduce the uncertainty of the livability evaluation. The community scale livability evaluation is expected to bridge the gap between theoretical concepts and practical implementations of livability evaluation, and enables the development of more effective and locally specific regulations and policies to improve community livability. [ABSTRACT FROM AUTHOR]

β-Nicotinamide mononucleotide (NMN) is an important precursor in the synthesis of nicotinamide adenine dinucleotide (NAD+) and confers multiple health benefits, resulting in the rapid growth of NMN market capacity in the fields of food and health care. To overcome the drawbacks of NMN production by the existing chemical or microbial fermentation method, there is an urgent need to develop a prospective NMN production strategy with low cost, low pollution, and high yield. In this study, we demonstrated an artificial in vitro multi-enzyme cascade biocatalysis using starch and nicotinamide (Nam) as substrates for the synthesis of NMN in one-pot. This multi-enzyme cascade reaction was optimized in terms of pH value, buffer concentration, inorganic phosphate concentration, enzyme composition, and phosphoenolpyruvate concentration. Under optimized conditions, a high molar yield of 87.8% for NMN was achieved using 3.2 mM Nam as substrate, and a molar yield of 55.37% for NMN was also achieved under the initial Nam concentration of 9.21 mM. This in vitro enzymatic platform provides an environmental friendliness biomanufacturing technology for the production of NMN, showing a highly promising alternative approach for NMN production. • We created an innovative platform for the biomanufacturing of NMN from starch and Nam via in vitro multi-enzyme cascade biosystem. • This NMN production method is environmentally friendly. • The system can efficiently convert maltodextrin and Nam to NMN. [ABSTRACT FROM AUTHOR]

An antibacterial cellulose oligomer was synthesized by cellodextrin phosphorylase (CDP) from glucose 1-phosphate (G1P) using a glucoside with an antibacterial group as a primer, then a hydrophilic cellulose molecular coating with excellent anti-fouling and anti-bacterial properties on PVDF membrane surface was carried out by dissolving the synthetic cellulose into a homogeneous solution. [Display omitted] • The antibacterial cellulose was synthesized from G1P in one step catalyzed by CDP. • Hydrophilic coating fabricated in one step showed high water flux. • Cellulose coating showed excellent anti-fouling and anti-bacterial performances. Synthetic cellulose prepared by enzyme has the advantages of easy functionalization, easy preparation, and biocompatibility, making it an ideal material for constructing hydrophilic coating with functionalities. In this study, β-D glucose with phenolic group (arbutin) as a primer reacted with glucose 1-phosphate (G1P) under the catalysis of Clostridium thermocellum (CtCDP) to synthesize antibacterial cellooligomer. Then, the synthetic cellooligomer was dissolved into a homogeneous organic solution to prepare a functional hydrophilic coating composed of cellulose molecular chains on the surface of polyvinylidene fluoride (PVDF) membranes. The molecular structure of enzymatic antibacterial cellooligomer was characterized by fourier transform infrared spectroscopy (FTIR) and 1H nuclear magnetic resonance spectroscopy (1H NMR). ATR-FTIR confirmed the successful preparation of cellulose coatings. The performance test results showed that the strong interaction at the interface between cellooligomer and PVDF membrane promoted the uniform distribution of cellulose molecules on the membrane surface, which greatly improved the hydrophilicity of PVDF membrane and enhanced the stability of the coating bonded to the substrate. Moreover, the cellulose molecular coating had excellent antifouling performance, outstanding antibacterial activity, and anti-adhesion to Staphylococcus aureus (S. aureus). This work provides a versatile platform for the time-saving and cost-effective fabrication of antifouling and antibacterial membranes. [ABSTRACT FROM AUTHOR]

Hydrophilic PVDF membrane was fabricated in single step via cellulose molecular coating prepared by homogeneous solution of cellulose oligomer synthesized by enzyme catalysis (EC)/Trifluoroacetic acid (TFA). Both smooth and rough coatings can be prepared by regulating the aggregative structure of cellulose molecular coatings. The chemical structures of the cellulose and its coating were confirmed by 1H Nuclear Magnetic Resonance Spectroscopy (1H NMR) and Fourier Transform Infrared Spectroscopy (FTIR). The aggregation structure of the cellulose coating was characterized by wide-angle X-ray diffraction (WAXD). X-ray Photoelectron Spectroscopy (XPS) studies unveiled the strong binding of cellulose molecular to PVDF membranes at the interface. Scanning Electron Microscopy (SEM) morphologies show that the cellulose molecules were uniformly coated on the surface and cross section of the membranes. Water contact angle measurement suggested that cellulose molecular coating possessed high hydrophilicity and wetting rate, giving the PVDF membranes high water flux and excellent anti-fouling performances. The coated membranes also show excellent adsorption and desorption performances for crystal violet (CV). The superior performances of incompletely crystallized cellulose coating over amorphous cellulose coating were attributed to the increased specific surface area resulting from the surface roughness. The construction of cellulose molecular coating with controlled aggregation structure provides a novel efficient technology in the field of purification of wastewater, opening up a new approach to the microstructural manipulation of the hydrophilic coating. A novel strategy to prepare the cellulose molecular coating with versatile functions. [Display omitted] • Hydrophilic PVDF membrane was fabricated in one step via cellulose molecular coating. • The surface roughness of coating can be regulated based on the aggregation state. • Cellulose coating showed high water flux and excellent anti-fouling performances. [ABSTRACT FROM AUTHOR]

Abstract: This study presents a crop planting and type proportion (CPTP) method for crop acreage estimation of complex and diverse agricultural landscapes. CPTP has three major components: (1) Crop planting proportion (CPP), estimated with wide-swath satellite remote sensing data to completely cover the monitoring area by segmenting cropped and non-cropped areas through unsupervised classification. (2) Crop type proportion (CTP), estimated by transect sampling and a special GPS-Video-GIS instrument (GVG) and a visual interpretation of crop type proportion in collected pictures for different strata. (3) Multiplication of CPP and CTP with arable land area at the strata level, summed to the province and national level. Validation has been done with in situ data for different agricultural landscapes over China. Both CPP estimation with remote sensing data and CTP estimation through ground survey have a high accuracy with average relative error (RE) and root mean square error (RMSE) equal to 1.42% and 1.67% for CPP and to 2.63% and 2.25% for CTP. The RE for crop acreage estimation equals to 4.09%. The CPTP method thus has a high accuracy, yields timely information at low costs, and is robust and provides objective results. The study concludes that the CPTP method can be used for large area crop acreage estimation of complex agriculture landscapes. [Copyright &y& Elsevier]

Abstract: Crop acreage estimation is a key aspect to forecast crop production. Maize acreage estimation becomes more and more important because the fast production changes every year due to the dynamics of the prices. This paper focuses on maize acreage estimation in the North China Plain using ENVISAT MERIS and CBERS-02B CCD data of 2008. Firstly, adaptive maximum likelihood classification of CBERS-02B CCD images based on ground survey provided reliable maize area fraction image (AFI). CBERS derived AFIs (as reference AFI) were used to train a 3-layer back-propagation neural network, this was then used to the whole MERIS data to generate MERIS AFIs (AFIe). To estimate maize acreage, the maize AFI from MERIS was masked with cropland dataset and maize acreages were estimated by zonal statistic of maize AFI at district level. The statistical results were also modified using a non-arable coefficient to remove the effects of non-arable factors. The results showed a close relationship between estimated and statistical maize acreage (R 2 ≈0.88). At province level, the estimation error is approximately 8%. This method is valuable for wide-scale, regional crop acreage estimation at the early stage of growing season. The study gives suggestions about high resolution image acquisition, spatial distribution and cropland datasets. [Copyright &y& Elsevier]

• SCCO obtained by bioprocessing was used as a Pickering emulsion stabilizer. • The Pickering emulsions were stable in pH ranges of 2–12 and ionic strength from 0 to 2 M. • The Pickering emulsions showed good tolerance to temperature changes from 2 to 60 °C. • The Pickering emulsions remain stable for no less than 6 months. Nanocellulose are promising Pickering emulsion stabilizers for being sustainable and non-toxic. In this work, semicrystalline cellulose oligomers (SCCO), which were synthesized from maltodextrin using cellobiose as primer by in vitro enzymatic biosystem, were exploited as stabilizers for oil-in-water Pickering emulsions. At first, the morphology, structure, thermal and rheological properties of SCCO suspensions were characterized, showing that SCCO had a sheet morphology and typical cellulose-Ⅱ structure with 56 % crystallinity. Then the kinetic stabilities of emulsions containing various amounts of SCCO were evaluated against external stress such as pH, ionic strength, and temperature. Noting that SCCO-Pickering emulsions exhibited excellent stabilities against changes in centrifugation, pH, ionic strengths, and temperatures, and it was also kinetically stable for up to 6 months. Both SCCO suspensions and their emulsions exhibited gel-like structures and shear-thinning behaviors. These results demonstrated great potential of SCCO to be applied as nanocellulosic emulsifiers in food, cosmetic and pharmaceutical industries. [ABSTRACT FROM AUTHOR]

• This paper is the first to map explicitly phenological transition zones. • Both "phenological" and "transitional" characteristics of PTZs were highlighted. • The PTZ dynamics were sensitive, rapid and dramatic in response to climate change. • Three different types of gradient, inclusive and mosaic PTZs were identified. • The method can be easily extended to other areas with no or minor adjustments. Spatially explicit mapping of the Phenological Transition Zone (PTZ) is the prerequisite to PTZ dynamics monitoring and characterization, and is significant for more effective management of natural resources, biodiversity, and conservation areas in the context of climate change. However, to our knowledge there have been no studies to delineate spatially explicit PTZs and there are some potential issues associated with the mapping of other biogeographical transition zones. This paper developed a method to explicitly delineate PTZs continuously from 2003 to 2017 in the study area of the Forest-Grassland Mosaic Region (FGMR) in northeastern China, highlighting both their transitional and phenological characteristics. Annual Normalized Difference Vegetation Index (NDVI) time series were fed into the dynamic-time-warping (DTW) based fuzzy c-medoids (FCMdd) clustering to produce 12 fuzzy phenoregions. Potential PTZ pixels were identified for each pair of fuzzy phenoregions via the fuzzy intersection operator. The Delaunay tessellation field estimator was applied to convert the discrete potential PTZ pixels to continuous weighted density surface. The 7 consistently and 8 intermittently existing PTZs were exhaustively derived via thresholding. Three different types of gradient, inclusive and mosaic PTZs were identified. The PTZ dynamics were rapid and dramatic due to its phenological and transitional nature. This PTZ mapping method can be easily extended to other areas with no or minor adjustments, and it can also be adapted to map other biogeographical transition zones. [ABSTRACT FROM AUTHOR]

• NNVAI is proposed to indicate winter wheat damage caused by a single frost event. • Growth-stage-specific relations between NNVAI and frost features were explored. • Winter wheat is sensitive to different features of frost at different growth stages. • Developed monitoring framework to do two-phase assessment of winter wheat damage. Frost events pose a threat to normal development of winter wheat and increase risk of production loss, even given the context of global warming. On the Huang-Huai-Hai Plain (HHHP), which is the largest region of winter wheat cultivation in China, frost damage has become one of the major meteorological catastrophes. In recent years, both frequency of occurrence and severity of frost events in this region have exhibited an upward trend. For timely and accurate monitoring of single-event frost damage of winter wheat, this study developed a frost-monitoring framework that considers the processes of the evolution of a frost event and the response of winter wheat, as well as the lag between them. The framework adopts a NDVI valley area index (NVAI) to represent the gradual response process of winter wheat to frost. In this framework, the normalized NVAI (NNVAI) is used to indicate the degree of damage, and a two-phased damage assessment (i.e., T1 and T2) is adopted to resolve the contradiction between the urgency of obtaining information on frost severity, the spatial distribution of frost damage, and the delayed response process of winter wheat to frost. Using prediction models based on historical statistics, assessment at the T1 stage estimates the possible damage after the end of the frost, and assessment at the T2 stage evaluates the actual damage caused by frost when the winter wheat has recovered. Application of the proposed framework to a frost event that occurred on the HHHP during March 4–9, 2018 revealed that the average absolute percentage error between actual and predicted damage across the entire region was 33 %. Moreover, the prediction of damage was made 13 days ahead of the occurrence of actual damage. Thus, the framework could provide guidance to enable action to be taken to reduce the impact of frost. The proposed monitoring framework fully considers the processes of the evolution of a frost event and the response of winter wheat to frost, and it learns potential patterns from historical frost events to provide early prediction of potential frost damage. Consequently, the framework is considered suitable for wide practical application. [ABSTRACT FROM AUTHOR]

Abstract: Background: Myanmar has long been a focus of the international community as a major opium poppy cultivation region. Method: This study used remote sensing technology and ground verification to monitor opium poppy cultivation for three opium poppy growth seasons in North Myanmar. Results: The study found that opium poppy cultivation has remained high. In 2005–6, 2006–7 and 2007–8 growing seasons the total areas monitored were 52,482km2, 178,274km2 and 236,342km2 and the total cultivated area of opium poppy was 8959ha, 18,606ha and 22,300, respectively. This was significantly less than cultivation levels reported during the 1990s. The major cultivation regions were located in Shan State, producing 88% of total poppy cultivation in North Myanmar in 2007–8. The opium poppy was mainly cultivated in the interlocking regions controlled by the local armed forces in Shan State. The field survey noted that most households in this area were poor and poppy cultivation was a main source of income. There were also differences between our figures on poppy cultivation and those reported by United Nations Office on Drugs and Crime. Conclusion: Our study shows that although the opium poppy cultivation in North Myanmar has reduced over recent years, it remains a major producer of opium and to which the international community needs to pay attention, especially in those areas controlled by local armed forces. [Copyright &y& Elsevier]

Abstract: Opium is a narcotic obtained from opium poppy and raw materials of heroin for illegal drug trade. Information on opium production is important for governments and international communities to understand the scale of illegal drug trade and to implement drug fighting policies. Opium production can be estimated from opium yield and poppy cultivation acreage. Poppy cultivation acreage in turn can be estimated using remote sensing technique. This study explores the feasibility of assessing opium yield using remote sensing technique. The objective of this study is to find an effective biophysical indicator that can be related to both opium yield estimation and remote sensing measurements. Data are obtained from three years ground experiments conducted in an official farm in North-Western China. Opium yield and main plant and environmental parameters of opium poppy are measured. A linear regression analysis measures the relationship between opium yield and main plant parameters. A strong correlation between opium yield and leaf area index (LAI) in flowering and harvesting periods of opium poppy is observed (R 2 =0.826 and 0.862 respectively). LAI is a good indicator during flowering and harvesting periods and can be used to build a model for opium yield estimation. Furthermore, LAI can be retrieved using remote sensing at a region scale. The study shows that remote sensing could be used to estimate opium yield in opium poppy concentrated regions, and that a more comprehensive and precise opium production information could be obtained for further analysis of illegal drug circulating trend and policy. [Copyright &y& Elsevier]