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Arable Land

The Experts below are selected from a list of 34908 Experts worldwide ranked by ideXlab platform

G Q Chen – 1st expert on this subject based on the ideXlab platform

  • an overview of Arable Land use for the world economy from source to sink via the global supply chain
    Land Use Policy, 2018
    Co-Authors: Xudong D Wu, G Q Chen

    Abstract:

    Abstract As an extension of a previous work ( Chen and Han, 2015a ), this study explored the Arable Land use of the world economy from source of exploitation to sink of final consumption via the global supply chain, by means of embodiment accounting that includes the indirect feedbacks associated with both intermediate and primary inputs. In magnitude, the global transfer of Arable Land use is estimated to be around 40% of the total direct exploitation. The connections as well as imbalances of major economies in intermediate and final trades of Arable Land use are discussed. Canada, Australia, Argentina, Pakistan and African regions turn out to have a massive deficit of Arable Land use in both intermediate and final trades. In contrast, the United States, Japan, MainLand China, the United Kingdom, Germany and France obtain a surplus of Arable Land use in both intermediate and final trades by Land displacement in those net exporters. Indices in terms of Arable Land use self-sufficiency rate by source and that by sink are devised. For India as the biggest source region, around 20% of the Arable Land resources exploited locally are for final consumption abroad. For the United States as the largest sink region, around 40% of its Arable Land use originates from foreign regions led by Canada. For Japan as the biggest net importer in both intermediate and final trades, over 90% of its Arable Land use comes from foreign economies led by African and Asian regions. For sustained development, regions are suggested to be more adapted to the global supply chain based on their behaviors in both intermediate and final trades of Arable Land use.

  • global Arable Land transfers embodied in mainLand china s foreign trade
    Land Use Policy, 2018
    Co-Authors: G Q Chen

    Abstract:

    Abstract The process of globalization increases spatial separation of basic resources in terms of demand and supply across multiple countries/regions, thereby leading to the shift of environmental pressure mainly triggered by population expansion and economic growth via global supply chains. To comprehensively analyze MainLand China’s Arable Land use issues, the present work illustrates its Arable Land transfers embodied in foreign trade based on a multi-regional input-output analysis. In total, the trade volume of MainLand China’s Arable Land transfers is revealed in magnitude up to 70% of its direct Arable Land area. With a distinction between production- and consumption-based transfers, MainLand China exports 27.18 Mha (million hectares) of embodied Arable Land to other economies, while it imports 48.35 Mha of embodied Arable Land, making it a large force for agricultural industry development and Arable Land utilization in regions such as ASEAN, EU27, and Africa. The relations, pressures, and structures of embodied Arable Land related to MainLand China are clearly depicted from the global perspective. With detailed embodied Arable Land transfer profiles, it is practical to comprehensively analyze MainLand China’s Arable Land utilization via supply chains from the global perspective for essential policy implications in reasonably reshaping MainLand China’s economic structures and trade patterns.

  • global supply chain of Arable Land use production based and consumption based trade imbalance
    Land Use Policy, 2015
    Co-Authors: G Q Chen

    Abstract:

    Closely related to food supply, Arable Land use has been extensively studied, especially regarding booming global trade activities. However, the analysis on trade patterns of Arable Land use, particularly in terms of intermediate use and final demand, is still lacking. To shed light on the complex Arable Land use relationships among economies, the global supply chain of Arable Land use is intensively explored in the present work by a systems multi-regional input-output analysis for the year of 2010, with focus on the trade patterns from the perspective of production and consumption. Global Arable Land use embodied in international trade is estimated near one third the global Arable Land use, and that embodied in intermediate use is almost twice that embodied in final demand. Arable Land use trade patterns are noted in terms of production-based imports/exports and consumption-based imports/exports. Most notably, MainLand China is shown as the leading production-dominated importer. With regard to other large economies, Canada is found as a production-oriented exporter, in contrast to Australia as a consumption-oriented exporter. Japan is identified as a production-oriented importer, while the United States is a consumption-oriented importer. As heavy trade imbalance is revealed prevailing not only between countries and regions but also between intermediate products and final goods, the study to explore global supply chains of Arable Land use can provide essential policy making implications for security and sustainability in Arable Land use and food supply on both global and regional scales.

Si-jing Ye – 2nd expert on this subject based on the ideXlab platform

  • Spatial pattern of Arable Land-use intensity in China
    Land Use Policy, 2020
    Co-Authors: Si-jing Ye, Changqing Song, Shi Shen, Changxiu Cheng, Feng Cheng

    Abstract:

    Abstract In recent years, the sustainable utilization of China’s Arable Land has been confronted with several challenges. The China government has been very strict in Arable Land protection, and a package of policies and measures have been promulgated. All these endeavors are of great significance for proposing an innovative policy system for sustainable Land use in China. However, above stated policies are all designed from the perspective of space control with the purpose of reducing Arable Land loss or increasing Arable Land area, few policies have been designed from the perspective of utilization control, namely guide the actual Arable Land farming in sustainable ways and constraint unreasonable Land use behavior such as overuse, rough use, Land abandonment. In this paper, we analyze spatial distribution of average Land-use intensity (ALUI) at the county-level in MainLand China, which can be used as a significant index for evaluating the rationality of Arable Land use and providing effective decision-making supporting information for design of regional Arable Land protection policy. Based on the experimental results, there is still considerable room for yield improvement as the ALUI of ∼73.1 % counties are lower than 0.7 while the 53.60 % counties are lower than 0.6. Furthermore, the ALUI dataset shows significant global spatial autocorrelation characteristic. Boundaries of regions that aggregated by counties with high ALUI are more consistent with that of provincial administrative districts, comparing with that of sub-standard farming system regions. On the other hand, counties with low ALUI are mostly cluster in mountains, hills, or plateaus, where grain yield is mainly limited by regional hydrothermal conditions. In addition, counties with different ALUI status have been divided into six classes, using k-means clustering algorithm. This will facilitate the understanding of appropriate Arable Land protection and utilization paths for different regions and the rethinking of current support policies on farmLand protection.

  • Landq v1 a gis cluster based management information system for Arable Land quality big data
    International Conference on Agro-Geoinformatics, 2017
    Co-Authors: Jianyu Yang, Lin Li, Zuliang Zhao, Si-jing Ye

    Abstract:

    In the era of spatial big data, geographic information system (GIS) faces many opportunities and challenges. The first challenge for future GIS is how to store and manage the spatial big data efficiently. For example, in 2013, the volume of Chinese Arable Land quality (ALQ) dataset is up to 2.51TB with ESRI Shapefile format, and traditional GIS development pattern with standalone version is not meeting the needs including storage, query, analysis and visualization. To solve above problems, in this paper, we present a system framework, LandQv1, based on the GIS cluster to support Arable Land quality big data management and analysis in geospatial domain. Firstly, it describes the design of the system architecture with three layers in details, and implemented by different technologies accordingly. Secondly, three models, data storage model, service release model, and data calling model, are developed to solve the key problems of each layer in the system framework. And then, LandQv1 is developed with the WPF, GIS cluster, Oracle database and C# language. Finally, through application and system test, the results show that LandQv1 with GIS map tools, data query and other functions can be meted the needs in high performance, which will lay the foundation for Arable Land big data analyzing in the future.

  • LandQv1: A GIS cluster-based management information system for Arable Land quality big data
    2017 6th International Conference on Agro-Geoinformatics, 2017
    Co-Authors: Xiaochuang Yao, Si-jing Ye, Lin Li, Jianyu Yang, Wenju Yun, Zuliang Zhao, Dehai Zhu

    Abstract:

    In the era of spatial big data, geographic information system (GIS) faces many opportunities and challenges. The first challenge for future GIS is how to store and manage the spatial big data efficiently. For example, in 2013, the volume of Chinese Arable Land quality (ALQ) dataset is up to 2.51TB with ESRI Shapefile format, and traditional GIS development pattern with standalone version is not meeting the needs including storage, query, analysis and visualization. To solve above problems, in this paper, we present a system framework, LandQv1, based on the GIS cluster to support Arable Land quality big data management and analysis in geospatial domain. Firstly, it describes the design of the system architecture with three layers in details, and implemented by different technologies accordingly. Secondly, three models, data storage model, service release model, and data calling model, are developed to solve the key problems of each layer in the system framework. And then, LandQv1is developed with the WPF, GIS cluster, Oracle database and C# language. Finally, through application and system test, the results show that LandQv1with GIS map tools, data query and other functions can be meted the needs in high performance, which will lay the foundation for Arable Land big data analyzing in the future.

Lin Li – 3rd expert on this subject based on the ideXlab platform

  • Landq v1 a gis cluster based management information system for Arable Land quality big data
    International Conference on Agro-Geoinformatics, 2017
    Co-Authors: Jianyu Yang, Lin Li, Zuliang Zhao, Si-jing Ye

    Abstract:

    In the era of spatial big data, geographic information system (GIS) faces many opportunities and challenges. The first challenge for future GIS is how to store and manage the spatial big data efficiently. For example, in 2013, the volume of Chinese Arable Land quality (ALQ) dataset is up to 2.51TB with ESRI Shapefile format, and traditional GIS development pattern with standalone version is not meeting the needs including storage, query, analysis and visualization. To solve above problems, in this paper, we present a system framework, LandQv1, based on the GIS cluster to support Arable Land quality big data management and analysis in geospatial domain. Firstly, it describes the design of the system architecture with three layers in details, and implemented by different technologies accordingly. Secondly, three models, data storage model, service release model, and data calling model, are developed to solve the key problems of each layer in the system framework. And then, LandQv1 is developed with the WPF, GIS cluster, Oracle database and C# language. Finally, through application and system test, the results show that LandQv1 with GIS map tools, data query and other functions can be meted the needs in high performance, which will lay the foundation for Arable Land big data analyzing in the future.

  • LandQv1: A GIS cluster-based management information system for Arable Land quality big data
    2017 6th International Conference on Agro-Geoinformatics, 2017
    Co-Authors: Xiaochuang Yao, Si-jing Ye, Lin Li, Jianyu Yang, Wenju Yun, Zuliang Zhao, Dehai Zhu

    Abstract:

    In the era of spatial big data, geographic information system (GIS) faces many opportunities and challenges. The first challenge for future GIS is how to store and manage the spatial big data efficiently. For example, in 2013, the volume of Chinese Arable Land quality (ALQ) dataset is up to 2.51TB with ESRI Shapefile format, and traditional GIS development pattern with standalone version is not meeting the needs including storage, query, analysis and visualization. To solve above problems, in this paper, we present a system framework, LandQv1, based on the GIS cluster to support Arable Land quality big data management and analysis in geospatial domain. Firstly, it describes the design of the system architecture with three layers in details, and implemented by different technologies accordingly. Secondly, three models, data storage model, service release model, and data calling model, are developed to solve the key problems of each layer in the system framework. And then, LandQv1is developed with the WPF, GIS cluster, Oracle database and C# language. Finally, through application and system test, the results show that LandQv1with GIS map tools, data query and other functions can be meted the needs in high performance, which will lay the foundation for Arable Land big data analyzing in the future.

  • Development of a Highly Flexible Mobile GIS-Based System for Collecting Arable Land Quality Data
    IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2014
    Co-Authors: Si-jing Ye, Nan Zhang, Shuai Fang, Lin Li

    Abstract:

    In recent years, well-designed terminal-based methods for collecting index data have gradually replaced traditional pen-and-paper methods and have been extensively used in numerous studies. These new approaches offer users increased accuracy, efficiency, consumption, and data compatibility compared to traditional methods. In general, we find that spatial data content and quality index systems vary widely across different Arable Land regions. Thus, a system for the investigation of Arable Land quality indices that has the flexibility to utilize various types of spatial data and quality indices without requiring program modification is needed. This paper presents the framework, the module partition, and the structure of the data exchange interface for a highly flexible mobile GIS-based system, which we call the “Arable Land quality index data collection system” (ALQIDCS). This system incorporates a series of self-adaptive methods, a data table-driven model and two types of formulas for flexible data collection and processing. We tested our prototype system by investigating Arable Land quality in the Da Xing District, Beijing and in the Te Da La Qi District, Inner Mongolia, China. The results indicate that the ALQIDCS can effectively adapt to variations in spatial data and quality index systems and meet different objectives. The limitations of the ALQIDCS and suggestions for future work are also presented.