Advances in Earth Science ›› 2003, Vol. 18 ›› Issue (1): 94-099. doi: 10.11867/j.issn.1001-8166.2003.01.0094

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Zhao Dehua, Li Jianlong, Song Zijian   

  1. Department of Biological Sciences & Technology, Nanjing University, Nanjing 210093, China
  • Received:2002-05-21 Revised:2002-08-30 Online:2003-02-10 Published:2003-02-01

Zhao Dehua, Li Jianlong, Song Zijian. HYPERSPECTRAL REMOTE SENSING FOR ESTIMATING BIOCHEMICAL VARIABLES OF CANOPY[J]. Advances in Earth Science, 2003, 18(1): 94-099.

Hyperspectral remote sensing (narrow bands) provides the possible estimates of biochemical characteristics of plant such as moisture, leaf pigment (for example, chlorophyll, carotenoids and anthocyanins), lignin, cellulose, protein, amino acids, sugar, starch, macro-element (nitrogen, phosphorus and potassium as the example), micro-element (such as Fe, Mn, Co, Zn, Cu). It is special significant to obtain biochemical information of canopy at territorial or even at global levels which could be widely used to study the ecosystem, accelerate the application of precision agriculture technology, and so on. At leaf or small area levels, not only it is significant for the researching on the forming of plant reflectance spectrum for remote sensing, but also, it may provide a rapid, nondestructive method for the detection of these characteristics in lab or in field. But from ground leaf or dry leaf level to fresh leaf level and to canopy level, more and more factors influence the spectrum. There are interferences among the factors, which may add the difficulty to estimate a certain biochemical variable or influence the accuracy. Some new progress in obtaining information from ground-level and airborne or satellitic level hyperspectral reflectance data were summarized and emphasis was especially focused on introducing the methods for improving accuracy of estimating biochemical variables and the mechanism of hyperspectral remote. The problems might be occurred because of the methods self that were being widely used to estimate biochemical variables of canopy also were pointed out. Future work should be focused both on improving the ratio of signal to noise, reforming the method of spectrum analysis and accelerating application of the existing research findings, but also on itemizing the biophysical variables and making clear their spectral characteristics (contribution to the reflectance spectrum). On the other hand, it is necessary to do more research on establishing new canopy spectrum reflectance models or improving existing models by mechanism in the future. The paper may supply the convenience, general picture and discuss to understand the new progress in the technologies and theories of hyperspectral remote sensing for estimating biochemical variables of plant.

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