Study of the spectral mixture model of soil and vegetation in PoYang Lake area, China

International Journal of Remote Sensing

Volumn 19, Issue 11, 1998, Pages 2077-2084

  Zhang, L ^a   Li, D ^a   Tong, Q ^b   Zheng, L ^b  

^a WUHAN UNIVERSITY   (China)

^b INSTITUTE OF REMOTE SENSING APPLICATIONS   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ECOLOGY; ECOSYSTEMS; LAKES; MATHEMATICAL MODELS; PLANTS (BOTANY); ROCKS; SOILS; SPECTROMETERS;

AIRBORNE IMAGING SPECTROMETERS; SPECTRAL MIXTURE MODELS;

REMOTE SENSING;

SPECTRAL MIXTURE MODEL; SPECTROMETER;

CHINA;

EID: 0032551509     PISSN: 01431161     EISSN: 13665901     Source Type: Journal    
DOI: 10.1080/014311698214875     Document Type: Article

References (20)

1. Bateson, A., and Curtiss, B. 1996, A method for manual endmember selection and spectral unmixing. Remote Sensing of Environment, 55, 229-243.
2. Ben-Dor, E., and Banin, A., 1994, Visible and near-infrared (0-4-1-1 mm) analysis of arid and semiarid soils. Remote Sensing of Environment, 48, 261-174.
3. Bo-Cao, G., and Goetz, A. F. H., 1995, Retrieval of equivalent water thickness and information related to biochemical components of vegetation canopies from AVIRIS data. Remote Sensing of Environment, 52, 155-162.
4. Borel, C. C., 1991, The radiosity method in optical remote seining of structured 3-D surfaces.Remote Sensing of Environment, 36, 13-44.
5. Borel, C. C., and Gerstl, S. A. W., 1994, Nonlinear spectra mixing models for vegetative and soil surface. Remote Sensing of Environment, 47, 403-416.
6. Forrest, G. H., and Huemmrich, K. E., 1990, Use of narrow-band spectra to estimate the fraction of absorbed photosynthetically active radiation. Remote Sensing of Environment, 31, 47-54.
7. Gates, D. M., 1965, Spectral properties of plants. Applied Optics, 4, 11-20.
8. Huete, A. R., 1985, Separation of soil-plant spectral mixtures by factor analysis. Remote Sensing of Environment, 19, 237-251.
9. Huete, A. R., and Jackson, R. D., 1983, Spectral response of a plant canopy with different soil backgrounds. Remote Sensing of Environment, 17, 37-53.
10. Huete, A. R and Escadafal, F., 1991, Assessment of biophysical soil properties through spectral decomposition techniques. Remote Sensing of Environment, 35, 149-159.
11. John, B. A., and Smith, M. O., 1986, Spectral mixture modeling: A new analysis of rock and soil types at the viking lander 1 site. Journal of Geophysical Research, 9, 8098-8112.
12. Knipling, E. B., 1970, Physical and physiological basis for the reflectance pf visible and nearinfrared radiation from vegetation. Remote Sensing of Environment, 1, 155-179.
13. Lenio, S. G., Vitorello, I., and Waldio, R., 1995, Paradella spectroradiometric discrimination of latrines with principal components analysis and additive modeling. Remote Sensing of Environment, 53, 70-75.
14. Murray, R. T., and Wadge, G., 1995, The effects of vegetation on the ability to map soils using imaging spectrometer data. International Journal of Remote Sensing, 12, 2153-2164.
15. R Oberts, D. A., Smith, M. O., and A Dams, J. B., 1993, Green vegetation, Nonphotosynthetic vegetation, and soil in AVIRIS data. Remote Sensing of Environment, 44, 255-269.
16. Siegal, B. S., and G Oetz, F. H., 1977, Effect of vegetation on rock and soil type discrimination. Photogrammetric and Remote Sensing, 43, 191-196.
17. Smith, M. O., and U Stin, S. L., 1990, Vegetation in deserts: I. A regional measure of abundance from multispectral images. Remote Sensing of Environment, 31, 1-26.
18. Terria, W. R., and Murray, B. C., 1996, Nonlinear spectral mixing in desert vegetation. Remote Sensing of Environment, 55, 59-64.
19. William, H. F., and Singer, R. B., 1995, Retrieval of apparent surface reflectance from AVIRIS data: A comparison of empirical line, Radiative transfer, and spectral mixture methods. Remote Sensing of Environment, 47, 311-321.
20. Yosio, E. S., and Smith, J. A., 1991, The least-square mixing models to generate fraction images derived from remote sensing multispectral data. I.E.E.E. T ransactions on Geoscience and Remote Sensing, 29, 16-20.