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干旱区地理 ›› 2020, Vol. 43 ›› Issue (2): 440-448.doi: 10.12118/j.issn.1000-6060.2020.02.18

• 地球信息科学 • 上一篇    下一篇

利用多源数据估算黑河流域总初级生产力

童志辉1，熊助国1，孙睿2,3，刘向铜1，王东东1   

  1. 1 东华理工大学测绘工程学院，江西 南昌 330013；

    2 北京师范大学遥感科学国家重点实验室，北京 100875； 3 北京市陆表遥感数据产品工程技术研究中心，北京 100875

  • 收稿日期:2019-03-25 修回日期:2019-08-14 出版日期:2020-03-25 发布日期:2020-05-08
  • 通讯作者: 熊助国
  • 作者简介:童志辉（1995-），男，硕士研究生，研究方向为生态遥感．E-mail：tongzhihui813@sina.com
  • 基金资助:
    国家重点研发计划（2017YFA0603002）；国家自然科学基金（41471349, 41531174）；江西省教育厅科学技术研究项目（GJJ170439）；江西省教育科学“十三五”规划课题（17YB070, 17YB079）；刘宝珺地学青年科学基金（DMSM2017010）资助

Estimating gross primary production in the Heihe River Basin from multiple data sources

TONG Zhi-hui1,XIONG Zhu-guo1,SUN Rui2,3,LIU Xiang-tong1,WANG Dong-dong1   

  1. 1 College of Surveying and Mapping,East China University of Technology,Nanchang 330013,Jiangxi,China;

    2 State Key Laboratory of Remote Sensing Science,Beijing Normal University,Beijing 100875,China; 3 Beijing Engineering Research Center of Global Land Remote Sensing Product,Beijing 100875,China

  • Received:2019-03-25 Revised:2019-08-14 Online:2020-03-25 Published:2020-05-08

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摘要：

总初级生产力（GPP）决定了进入陆地生态系统的初始物质与能量，但由MODIS GPP产品获取的GPP在地表覆盖复杂的黑河流域却不足以准确的反映生态系统物质与能量的分布。因此，利用MODIS影像数据、ASTER GDEM数据、30 m分辨率土地利用覆被数据和中国区域地面气象要素驱动数据，驱动VPM模型模拟黑河流域2015年5～10月的总初级生产力，并据此揭示黑河流域GPP在生长季的时空格局，时间分辨率为8 d，空间分辨率为500 m。研究结果表明：VPM模型估算结果的精度高于MODIS GPP产品，判定系数增长了45.5%，总均方根误差降低了57.0%；黑河流域生长季累积[WTBX]GPP[WTBZ]总体呈现出中游最高、上游其次、下游最低的显著空间分布梯度格局；全境与局部有植被覆盖区域的日GPP均呈先增加后减少倒U型变化规律，且前者在7月下旬达到最高值；植被覆盖率极低的地表区域生长季内的日GPP在基本稳定中上下波动，稳定值处于1 gC·m-2·d-1附近。

关键词: VPM模型, 多源数据, 总初级生产力, 时空格局,  , 黑河流域

Abstract: The initial matter and energy entering terrestrial ecosystem are determined by the gross primary productivity (GPP).Hovexer,the GPP measurements acquired by the MODIS [WTBX]GPP[WTBZ] products are not sufficient to accurately reflect the distribution of ecosystem matter and energy in the Heihe River Basin in Qinghai Province,Gansu Province and Inner Mongolia,China with complex surface coverage.Therefore,based on MODIS image data,ASTER GDEM data,land cover data with a spatial resolution of 30 m,and the China Meteorological Forcing Dataset,the VPM model was derived to simulate the gross primary productivity of the Heihe River Basin from May to October 2015 with a spatial resolution of 500 m and a temporal resolution of 8 days.Based on simulations using the VPM model,the spatial and temporal patterns of GPP in the Heihe River Basin during the growing season were determined．The results of the study indicate that the accuracy of the results estimated using the VPM model was higher than that of the MODIS GPP products.The judgment coefficient increased by 45.5%,while the total root mean square error reduced by 57.0%.The study results also demonstrate that the GPP accumulation during the growing season in the Heihe River Basin exhibited a significant spatial distribution gradient pattern,which can be described as the highest in the middle reaches,the next highest in the upper reaches,and the lowest in the lower reaches.In addition,the daily GPP of the whole and partial vegetation-covered areas in the Heihe River Basin first increased and then decreased in an inverted U-shape.The daily GPP values of all vegetationcovered areas reached the maximum in late July.The daily GPP values of those ground areas with very low vegetation coverage fluctuated up and down in their basic stability,while the stable value was approximately 1 gC·m-1·d-1.

Key words: VPM model, multi-source data, gross primary productivity, spatial and temporal patterns, Heihe River Basin