Acta Geographica Sinica ›› 1998, Vol. 53 ›› Issue (6): 545-552.doi: 10.11821/xb199806008

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Li Guosheng, Shao Yubin   

  1. Institute of Geography, CAS, Beijing 100101
  • Received:1997-01-01 Revised:1998-06-01 Online:1998-11-15 Published:1998-11-15
  • Supported by:
    Supported by National Natural Science Foundation of China, and“the National Ninth Five-Year Plan”project of No.HY126-06-04-04

Abstract: The possibility of using remote sensing of ocean water color to determine oceanic primary productivity has been recognized for many years. After reviewing the relevant literature, this paper presents the mechanism and a methodology to obtain oceanic primary productivity by using remote sensing and GIS technologies. The physical processes of absorption and scattering cause the upwelling radiance just beneath the sea surface to be related to the constituents of the water. Except for waters in close proximity to coastlines and coastal river months, biological constituents play a dominant role in these processes. The most important constituent appears to be phytoplankton, microscopic plant organisms that photosynthesize and constitute the bottom link in the ocean food chain. These plankton contain chlorophyll a, which absorbs strongly in the blue and red regions of the visible spectrum. Hence, increasing concentrations of phytoplankton (chlorophyll a) have the effect of changing the color of water from its pure state of deep blue to green hues. Another major factor that influences the precision of water color sensing is the unknown spectral characteristics of the water. Because of inherently different characters, there is great difference between the spectral measurement and analysis of different types of land and water. The method we use to remove the aerosol effects is based on a correction algorithm devised by Gordon, which isL(λ)=L s(λ)+L d(λ)={L w(λ)+L g(λ)}×T A(λ)+L P A(λ)+L P R(λ) In the investigation of marine primary productivity, it is most important that one formulates suitable algorithm for estimating primary productivity using the chlorophyll concentrations derived from remotely sensed ocean color data. Because of the problems in plant physiological response, there are difficulties in generating a suitable algorithm. Three methods for measuring primary productivity have been suggested by Ryther and Yentsch (1957), Parsons, et al (1984) and Eppley, et al (1985) based on the use of assimilation ratio, the intensity of photosynthesis to chlorophyll concentration, the chlorophyll a concentration, and the irradiance penetrating to ocean depths, etc. Such works show that equations can be written as P= C×Q×R/K , P t,d =P t, max {aI o, max sin 3(π/D)te -kd }/{1+aI o, max sin 3(π/D)te -kd } and ln P t =3.06+0.5ln C -0.24 T A +0.25 D L , respectively. In this paper, with the remote sensing algorithm model of the content of sea surface chlorophyll, three types of algorithm about oceanic primary productivity are introduced. By using GIS rule based on simulation technologies, a theoretical GIS estimation model written as P t=? 苮{phy(x,y,z),a,b,c} and its resolution method for the spatial oceanic primary productivity are proposed.

Key words: oceanic primary productivity, chlorophyll concentration, remote sensing algorithm, GIS estimation model

CLC Number: 

  • P715.7