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Ren Y.,Beijing Research Center for Information Technology in Agriculture | Ren Y.,Henan University | Tang X.,Beijing Research Center for Information Technology in Agriculture | Liu Y.,Beijing Research Center for Information Technology in Agriculture | And 2 more authors.
Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery | Year: 2016

The quantity and spatial distribution of cereal field are important for food security and ecology function, especially in metropolitan area. A new method was presented to design the layout of cereal field in metropolitan area and these factors were accounted for in this method such as the land productivity, the ecological function as well as the geographical location. The first step was to identify the priority assigned region (PAR) and the none priority assigned region (NPAR) according to the properties and the locations of crop lands. If the crop lands were basic farmland and they also were within the region of allowable construction, these crop lands were identified as PAR and the others were identified as NPAR. The second step was to classify the NPAR into the suitable region (SR), the optional region (OR), the unsuitable region (UR) based on the comprehensive evaluation model(CEM). As a case study, this method was applied in Pinggu District in Beijing City to optimize the layout of cereal field. The results were as follow: the area of PAR was 1 427.26 hm2, accounting for 11.62% of the total cultivated area, and PAR distributed mainly around the urban area and neighboring towns. The area of NPAR was 10 850.96 hm2. The area of SR was 4 450.75 hm2, with the evaluation scores higher than 85.17. SR distributed mainly in the eastern region of Pinggu District. The area of OR was 3 881.18 hm2, with the evaluation scores between 80.00 and 85.17. OR distributed mainly in the western and southern regions of Pinggu District. The area of UR was 2 519.03 hm2, with the scores lower than 80.00. UR distributed mainly in the northern region of Pinggu District and the topography of UR is usually mountainous. The layout method of cereal field accounting for “Production-Ecology-Location” in this paper can provide a scientific basis for the grain layout in ecological conservation area of Beijing. © 2016, Chinese Society of Agricultural Machinery. All right reserved. Source


Zhao Y.,South China Agricultural University | Zhao Y.,Guangdong Province Key Laboratory of Land Use and Consolidation | Zhao Y.,Key Laboratory of the Ministry of Land and Resources for Construction Land Transformation | Zhang X.,Sun Yat Sen University | And 7 more authors.
Journal of Information and Computational Science | Year: 2014

Because Cellular Automata (CA) is a dynamic system with inherent parallelism, many studies are focused on mapping CA to the parallel system in order to obtain high performance computing capability, such as using clusters, supercomputers and networks of computers. But the application of these systems are too expensive and difficult to use on the occasions which need convenient computing. Recent developments in the General Purpose GPU can meet the desktop computing challenge, which have high performance at low cost. This paper presents a general-purpose approach to accelerate the CA in geographical domain in case of spatial simulation. A series of experiments are launched to test the performance of proposed method. Finally, the experimental results indicate the approach in this paper can obtain high performance and computational performance data using GPU based accelerating method are fifty to sixty times faster than the identical algorithms using CPU in test environment. It is worthy of (1) reducing the communication cost between GPU and CPU is crucial when visualization and processing are equally important in real time simulation and (2) improving the parallel capability in the CA functions is essential using GPU Programming. © 2014 Binary Information Press Source


Wang J.,South China Agricultural University | Wang J.,Guangdong Province Key Laboratory of Land Use and Consolidation | Wang J.,Key Laboratory of the Ministry of Land and Resources for Construction Land Transformation | Ge A.,South China Agricultural University | And 10 more authors.
Solid Earth | Year: 2015

Traditionally, potential evaluation methods for farmland consolidation have depended mainly on the experts' experiences, statistical computations or subjective adjustments. Some biases usually exist in the results. Thus, computer-aided technology has become essential. In this study, an intelligent evaluation system based on a fuzzy decision tree was established, and this system can deal with numerical data, discrete data and symbolic data. When the original land data are input, the level of potential of the agricultural land for development will be output by this new model. The provision of objective proof for decision-making by authorities in rural management is helpful. Agricultural land data characteristically comprise large volumes, complex varieties and more indexes. In land consolidation, it is very important to construct an effective index system. A group of indexes need to be selected for land consolidation. In this article, a fuzzy measure was adopted to accomplish the selection of specific features. A fuzzy integral based on a fuzzy measure is a type of fusion tool. The optimal solution with the fewest non-zero elements was obtained for the fuzzy measure by solving a fuzzy integral. This algorithm provides a quick and optimal way to identify the land-index system when preparing to conduct land consolidation. This new research was applied to Shunde's "Three Old" consolidation project which provides the data. Our estimation system was compared with a conventional evaluation system that is still accepted by the public. Our results prove to be consistent, and the new model is more automatic and intelligent. The results of this estimation system are significant for informing decision-making in land consolidation. © Author(s) 2015. Source


Zhao Y.,South China Agricultural University | Zhao Y.,Guangdong Province Key Laboratory of Land Use and Consolidation | Zhao Y.,Key Laboratory of the Ministry of Land and Resources for Construction Land Transformation | Hu X.,South China Agricultural University | And 7 more authors.
Journal of Information and Computational Science | Year: 2014

This paper presents a site selection model of Land Consolidation Project (LCP) using spatial Ant Colony Optimization (ACO) techniques. Generally, it is straightforward to use Equal Interval, Quartile, Natural Breaks and K-Means Cluster method for selecting the site of LCPs. However, the traditional analysis methods have difficulty in solving ideal solution problems because of complex spatial search, and ACO provides a useful tool for site selection. In this study, the integration of ACO with multi-way tree and GIS is proposed to solve site selection problems of LCPs. An evaluating system including eco-socio-economic and fitness function has also been established so that the model can find the suitable site which has contiguous space and high land suitability evaluation index. This model has been applied to the site selection of LCPs in Huazhou, Guangdong Province, China. The experiment showed that the proposed model had better performance in the site selection of strong advantage in land consolidation project. © 2014 Binary Information Press Source


Zhao Y.,South China Agricultural University | Zhao Y.,Guangdong Province Key Laboratory of Land Use and Consolidation | Zhao Y.,Key Laboratory of the Ministry of Land and Resources for Construction Land Transformation | Cheng J.,South China Agricultural University | And 6 more authors.
Xitong Fangzhen Xuebao / Journal of System Simulation | Year: 2015

A parallel agent-based model of Von Thünen Model was proposed driven by graphics processing units (GPUs). The Von Thünen Model often involved the simulation of large numbers of geographically located individual decision-makers and a massive number of individual-level interactions. This simulation required substantial computational power. GPU-enabled computing resources provided a massively parallel processing platform based on a fine-grained shared memory paradigm. This massively parallel processing platform held considerable promise for meeting the computing requirement of agent-based models of spatial problems. A dynamic relationship table rebuilding method was proposed to enable the use of GPUs for parallel agent-based modeling of the spatial Von Thünen Model. The key algorithm played an important role in best exploiting high-performance resources in GPUs for large-scale spatial simulation. Experiments conducted to examine computing performance show that GPUs provide a computationally efficient alternative to traditional parallel computing architectures and substantially accelerate agent-based models in large-scale spatial space. ©, 2015, Chinese Association for System Simulation. All right reserved. Source

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