GEMI: a non-linear index to monitor global vegetation from satellites

@article{Pinty1992GEMIAN,
  title={GEMI: a non-linear index to monitor global vegetation from satellites},
  author={Bernard Pinty and Michel M. Verstraete},
  journal={Vegetatio},
  year={1992},
  volume={101},
  pages={15-20}
}
Knowledge about the state, spatial distribution and temporal evolution of the vegetation cover is of great scientific and economic value. Satellite platforms provide a most convenient tool to observe the biosphere globally and repetitively, but the quantitative interpretation of the observations may be difficult. Reflectance measurements in the visible and near-infrared regions have been analyzed with simple but powerful indices designed to enhance the contrast between the vegetation and other… 

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References

SHOWING 1-10 OF 24 REFERENCES

Characteristics of maximum-value composite images from temporal AVHRR data

  • B. Holben
  • Environmental Science, Mathematics
  • 1986
Abstract Red and near-infrared satellite data from the Advanced Very High Resolution Radiometer sensor have been processed over several days and combined to produce spatially continuous cloud-free

Analysis of the dynamics of African vegetation using the normalized difference vegetation index

Abstract Images at a resolution of 8 km are currently being generated for the whole of Africa, displaying the normalized difference vegetation index (NDVI). These images have undergone a process of

North American vegetation patterns observed with the NOAA-7 advanced very high resolution radiometer

Spectral vegetation index measurements derived from remotely sensed observations show great promise as a means to improve knowledge of land vegetation patterns. The daily, global observations

AVHRR for Monitoring Global Tropical Deforestation

Abstract Advanced Very High Resolution Radiometer (AVHRR) data have been used to assess the dynamics of forest transformations in three parts of the tropical belt. A large portion of the Amazon Basin

Red and photographic infrared linear combinations for monitoring vegetation

  • C. Tucker
  • Environmental Science, Mathematics
  • 1979

Removal of Atmospheric Effects prom AVHRR Albedos

  • P. Koepke
  • Environmental Science, Mathematics
  • 1989
Abstract Based on numerical simulations, coefficients are determined to be used in a linear relationship between clear-sky planetary albedo and surface albedo. Thew coefficients are given as

Estimation of Total Above-Ground Phytomass Production Using Remotely Sensed Data *

Remote sensing potentially offers a quick mad nondestructive method for monitoring plant canopy condition and development. In this study, multispectral reflectance and thermal emittance data were

Non-Lambertian Effects on Remote Sensing of Surface Reflectance and Vegetation Index

  • T. LeeY. Kaufman
  • Mathematics, Environmental Science
    IEEE Transactions on Geoscience and Remote Sensing
  • 1986
This paper discusses the effects of non-Lambertian reflection from a homogeneous surface on remote sensing of the surface reflectance and vegetation index from a satellite. Remote measurement of the