Analysis on the balance between supply and demand of cropland in Yantai City of China in 2020

Qiuxian Wang; Zhiqiang Gao; Jicai Ning; Ye Wang; Wei Gao

doi:10.1117/12.2062823

8 October 2014 Analysis on the balance between supply and demand of crop land in Yantai City of China in 2020

Qiuxian Wang, Zhiqiang Gao, Jicai Ning, Ye Wang, Wei Gao

Proceedings Volume 9221, Remote Sensing and Modeling of Ecosystems for Sustainability XI; 922114 (2014) https://doi.org/10.1117/12.2062823
Event: SPIE Optical Engineering + Applications, 2014, San Diego, California, United States

Abstract

With the fast development of economy and urbanization, the phenomenon of city construction occupying Cropland often happens. As the contradiction between human and land becomes more prominent, the contradiction between the supply and demand of the cropland are more radical in Yantai City of China. Analysis on the balance between supply and demand of cropland is the main basis to determine land use objectives, and also the basis of editing land use planning. In this paper, the authors firstly calculated the potential of cropland supply in Yantai for 2020 according to its current number of the cropland and the potential quantity of other kinds of land changing to the cropland, and then calculated the demand for cropland in 2020 with the methods of the population prediction and its national economic development planning. Then the balance between the supply and demand of cropland was analyzed. The results were that the cropland in Yantai city in 2020 were lower than those of its demand. At last, to relieve the contradiction, the authors tried to put forward some recommendations like optimizing the structure to coordinate the balance between the supply and demand of the cropland etc. to realize its regional sustainable development.

Citation Download Citation

Qiuxian Wang, Zhiqiang Gao, Jicai Ning, Ye Wang, and Wei Gao "Analysis on the balance between supply and demand of crop land in Yantai City of China in 2020", Proc. SPIE 9221, Remote Sensing and Modeling of Ecosystems for Sustainability XI, 922114 (8 October 2014); https://doi.org/10.1117/12.2062823

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