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

@article{Pinty2004GEMIAN,
  title={GEMI: a non-linear index to monitor global vegetation from satellites},
  author={Bernard Pinty and Michel M. Verstraete},
  journal={Vegetatio},
  year={2004},
  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… 

Figures from this paper

The Development of Vegetation Indices: a Short Overview
Vegetation indices computed from remote sensing data became key components of agricultural monitoring and assessment. With the help of these indices, the difference of vegetational and other land
Linearized vegetation indices based on a formal statistical framework
  • C. Ünsalan, K. Boyer
  • Environmental Science, Computer Science
    IEEE Transactions on Geoscience and Remote Sensing
  • 2004
TLDR
This paper compares the indices obtained by linearizing the NDVI with extensive experimental results on real IKONOS multispectral images, and shows how to obtain a linearized and more reliable measure.
A new method to reduce the sun angle effects and noise contamination in extracting the vegetation indices from satellite images
  • M. Anvar, S. Almodarresi
  • Computer Science, Environmental Science
    2007 IEEE International Geoscience and Remote Sensing Symposium
  • 2007
TLDR
A new vegetation index (ADPVI) is introduced using composite data and the result of this index is compared with one of the most popular vegetation indices (NDVI) and Experimental results demonstrate that this new index reduce the deficiencies of NDVI and also is more reliable to be representative for vegetation density.
Spectral band difference effects on vegetation indices derived from multiple satellite sensor data
Vegetation indices based on satellite image data are widely used for change monitoring but, when derived from different satellite sensors, differ as a function of the uncorrectable differences
Significant Remote Sensing Vegetation Indices: A Review of Developments and Applications
TLDR
The spectral characteristics of vegetation are introduced and the development of VIs are summarized, discussing their specific applicability and representativeness according to the vegetation of interest, environment, and implementation precision.
Compositing AVHRR data for the Australian continent: seeking best practice
Daily observations of the earth by satellite sensors contain significant non-surface contributions such as cloud, atmospheric effects (aerosols, water vapour), and systematic effects resulting from
Spectral Simulations of Vegetation Indices in the Context of Landsat Data Continuity
TLDR
Among the vegetation indices considered, the Global Environmental Monitoring Index (GEMI) proved to be the least sensitive to spectral dissimilarities between sensors and hence GEMI is worth considering for quantitative monitoring of environmental change using images from multiple sensors to fill the Landsat data archive.
Sensitivity of vegetation indices to different burn and vegetation ratios using LANDSAT-5 satellite data
The application of vegetation indices is a very common approach in remote sensing of burned areas to either map the fire scar or estimate burn severity since they minimize the effect of exogenous
Linearized Vegetation Indices
TLDR
This book summarizes the multispectral information via vegetation and shadow–water indices and proposes a solution to the nonlinearity (saturation) problem based on this statistical explanation.
...
1
2
3
4
5
...

References

SHOWING 1-10 OF 24 REFERENCES
Characteristics of maximum-value composite images from temporal AVHRR data
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
Removal of Atmospheric Effects prom AVHRR Albedos
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. Lee, Y. Kaufman
  • Geology, Geography
    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
...
1
2
3
...