Volume XLII-3
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 1069-1072, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-1069-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 1069-1072, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-1069-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  30 Apr 2018

30 Apr 2018

EVALUATION OF RESOURCES CARRYING CAPACITY IN CHINA BASED ON REMOTE SENSING AND GIS

K. Liu1, Y. H. Gan1, T. Zhang1, Z. Y. Luo1, J. J. Wang1, and F. N. Lin2 K. Liu et al.
  • 1Satellite, Surveying and Mapping Application Center, NASG, Beijing 100048, China
  • 2Ningbo Shiyou Information Technology Co., Ltd., Ningbo, China

Keywords: carrying capacity, CCRR, model modification, remote sensing

Abstract. This paper accurately extracted the information of arable land, grassland (wetland), forest land, water area and construction land, based on 1 : 250000 basic geographic information data. It made model modification of comprehensive CCRR to achieve carrying capacity calculation taking resource quality into consideration. Ultimately it achieved a comprehensive assessment of CCRR status in China. The top ten cities where the status of carrying capacity of resources was overloaded were Wenzhou, Shanghai, Chengdu, Baoding, Shantou, Jieyang, Dongguan, Fuyang, Zhoukou and Handan. The cities were basically distributed in the central and southern areas with convenient transportation and more economically developed areas. Among the cities in surplus status, resources carrying capacity in Hulun Buir was the most abundant, followed by Heihe, Bayingolin Mongol Autonomous Prefecture, Qiqihar, Chifeng and Jiamusi, all of which were located in northeastern China with a small population and plentiful cultivated land.