A number of national, regional and global land cover classification systems have been developed to meet specific user requirements for land cover mapping exercises, independent of scale, nomenclature and quality. However, this variety of land-cover classification systems limits the compatibility and comparability of land cover data. Furthermore, the current lack of interoperability between different land cover datasets, often stemming from incompatible land cover classification systems, makes analysis of multi-source, heterogeneous land cover data for various applications a very difficult task. This paper provides a critical review of the harmonization of land cover classification systems, which facilitates the generation, use and analysis of land cover maps consistently. Harmonization of existing land cover classification systems is essential to improve their cross-comparison and validation for understanding landscape patterns and changes. The paper reviews major land cover classification standards according to different scales, summarizes studies on harmonizing land cover mapping, and discusses some research problems that need to be solved and some future research directions.

Zircon has been widely applied in various traditional and emerging fields due to its distinct physiochemical advantages while monodisperse spherical zircon (MSZ) powders hitherto have not been explored for the tremendous challenges in the control of zircon crystallization and growth. Herein, systematic investigations are presented to reveal the paramount role of halide mineralizers upon the crystallization and growth of MSZ powders synthesized under highly acidic hydrothermal environments (pH <0). A formation mechanism is revealed revolving around the complexation of central Zr4+ with the Lewis basic ligand, fluorine, which forms the F‐containing species of [(OH)1–y·Ry] (R = F, Cl) to replace Zr and generates Zr‐deficient zircons as (ZrO4)1‐xSi[(OH)1‐y·Ry]4x. This finding differs much from conventional views on common fluoro‐hydroxylated hydrothermal zircons, which were generally regarded as Si‐deficient silicates from the substitution of fluoro‐hydroxyls for the [SiO4] tetrahedra. A parameter, Kr=4xy, is first proposed as an index to evaluate the stability of hydrothermal zircons. The MSZ powders demonstrate superb thermal stability at high temperature, superior photo‐reflectance, and thermal insulation over normal zircons, promising attractive prospects to extend zircon applications.

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Due to rapid changes in urban and rural economic development, the Chinese landscape has been gradually transforming toward urbanization. Most Chinese rural villages face declining problems such as population loss, land use transformation, fragmentation and abandonment, resulting in big changes in the rural spatial morphology. To understand these urbanization challenges, this study established a multi-factor methodology and applied it to a case study of three selected typical villages in southern Jiangsu Province. From this analysis, the quantification of the rural spatial morphology and environmental status, from 2005 to 2016, was determined. The eight driving factors established considered the rural geological location, landform, and social economic status. To analyze the driving factors, a quantitative analysis using ArcGIS, Environment for Visualizing Images (ENVI), and Analytic Network Process (ANP) decision-making methods were used. The results revealed mechanisms between the changes to spatial morphology of rural villages in southern Jiangsu Province and their key driving factors. This study provides data support and a theoretical framework to guide future development and policy of rural villages of different types, which supports the sustainable development of Chinese rural villages.

China Internet plus agriculture was first put forward in 2015 by the Chinese government’s work report, laying the foundation for the development of Internet plus agriculture and promoting the rapid growth of e-commerce marketing of agricultural products. The combination of agricultural product marketing and e-commerce effectively reduces the intermediate links of agricultural product sales. Many e-commerce professional villages have sprung up in some rural areas across the country, and the number of rural e-commerce stores has continued to grow. At this stage, rural e-commerce has become a new way of agricultural trade, and rural e-commerce has formed a unique rural e-store. At present, the e-commerce market share of agricultural products in rural stores is very large, and its advantages are favored by the government, scientific research institutions, and agricultural products processing enterprises. However, with the gradual development of rural e-commerce, it has also encountered many difficulties. Based on this point, this study applies deep learning and data mining to optimize e-commerce marketing. First, with the growth of the online scale of agricultural product transaction data, the creation of traditional shallow model cannot meet the needs of online data processing. Therefore, this study decides to use the deep learning theory for optimization. It has excellent performance in the technical fields of big data processing and image and voice processing and has strong construction ability, which can effectively represent the characteristics of the model. Combined with the characteristics of e-commerce agricultural products processing and consumer practice, this study designs and develops a new customer value evaluation model based on data mining and e-commerce agricultural products value characteristics in the field of e-commerce. By combining deep learning and data mining technology, this study applies it to the field of e-commerce, so as to promote the transformation of marketing optimization.

With the rapid development of global economy, the industrial cluster has become the new trend of world economic development. So far, the industrial cluster mode with space as the main division has been formed. The cooperation of industrial clusters is dynamic. The industries in the cluster cooperate with each other for mutual benefit and win-win, occupying a place in the fierce market competition. In addition, the industrial cluster is also conducive to strengthen the international economic division of labor and points out the direction of regional industrial transfer. China is now in a critical period of economic development; the industrial cluster plays an important role in China's industrial transformation and economic development. At present, the most common regional development mode in China is industrial cluster. The emergence of industrial cluster accelerates the development of industrial regional economy and the balance of industrial layout. Industrial clusters occupy a key position in China's economic industry chain, and the development and change in industrial clusters will directly affect the development of the entire industrial chain. This study first simulates the evolution path of industrial cluster and then establishes the relevant data model. Finally, through repast simulation, it puts forward conclusions and suggestions according to the verification results. The construction of dynamic model can realize the simulation of industrial cluster theory. According to the simulation results, we can find that the ecosystem in different stages will produce different characteristics; the formation and evolution of industrial clusters are actually the epitome of market development. In this process, the government guidance and market regulation are needed to accelerate the formation of industrial cluster ecosystem and increase the scale of industrial cluster.

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