东北大学学报:自然科学版 ›› 2016, Vol. 37 ›› Issue (10): 1450-1454.DOI: 10.12068/j.issn.1005-3026.2016.10.018

• 资源与土木工程 • 上一篇    下一篇

国产高分遥感数据估算草地NPP

包妮沙1, 吴立新1,2 , 叶宝莹3, 赵菲菲1   

  1. (1. 东北大学 资源与土木工程学院, 辽宁 沈阳110819; 2. 中国矿业大学 环境与测绘学院, 江苏 徐州221116; 3. 中国地质大学(北京) 地质调查院, 北京100083)
  • 收稿日期:2015-06-20 修回日期:2015-06-20 出版日期:2016-10-15 发布日期:2016-10-14
  • 通讯作者: 包妮沙
  • 作者简介:包妮沙(1985-),女,内蒙古呼伦贝尔人,东北大学副教授,博士; 吴立新(1966-),男,江西宜春人,东北大学教授,博士生导师.
  • 基金资助:
    国家自然科学基金青年基金资助项目(41401233); 中央高校基本科研业务费专项资金资助项目(N120801001).

Estimating Net Primary Productivity Using Chinese GF-1 Remote Sensing Data for Regional Grassland

BAO Ni-sha1, WU Li-xin2, YE Bao-ying3, ZHAO Fei-fei1   

  1. 1. School of Resources & Civil Engineering, Northeastern University, Shenyang 110819, China; 2. School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China; 3. Institute of Geological Survey, China University of Geosciences
  • Received:2015-06-20 Revised:2015-06-20 Online:2016-10-15 Published:2016-10-14
  • Contact: BAO Ni-sha
  • About author:-
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摘要: 利用国产卫星高分一号卫星数据评估其植被第一生产力(NPP)的潜力,对植被指数取值范围、光能利用率、水分指数等参数进行修订,建立适合高分卫星数据的光能利用率模型,反演小尺度草地生态系统的生产力,利用野外观测数据对反演结果进行验证.模型模拟的数值与实测值的拟合度达到0.94,均方差为20.59gC/(m2·a),并进一步将该结果与该区域同类型研究进行类比分析.结果表明,该模型对小尺度草地NPP估算可行,减少了工作量,为国产高分数据进行草地NPP、尤其煤矿区草地环境的监测提供了可行的技术方法,从而推动国产卫星在该地区的应用.

关键词: 国产高分卫星, 植被第一生产力, 干旱半干旱草地, 煤矿区, 光能利用率模型

Abstract: The ability of net primary production (NPP) was estimated by using the Chinese GF-1 remote sensing data. The specified land surface parameters such as vegetation indices, light efficiency and water indices were modified to establish Carnegie-Ames-Stanford approach (CASA) model for NPP modeling by using the Chinese GF-1 satellite data. The field observation data was used to valid the accuracy of simulated NPP from CASA model. There is a good correlation between the simulated NPP and field observed NPP with correlation coefficient of 0.94, and RMSE is 20.59gC/(m2·a). Furthermore, the NPP results were compared with similar study over semi-arid grassland zone. The results showed that the CASA model performs well at regional scale grassland monitoring. The Chinese satellite data has potential to be further applied on the semi-arid grassland, particular on coal mine environment monitoring over this region.

Key words: Chinese GF-1 satellite data, NPP (net primary productivity), semi-arid grassland, coal mine area; CASA model

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