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Vegetation as Indicator of Environmental Pollution

Transactions of the Institute of British Geographers, 1984
The environment can be polluted by industrial emissions and effluents and by dumped waste materials from mines. Most pollutants constitute health hazards and some like mercury and lead can cause disease and death. Toxic conditions can also occur in the natural environment notably where mineral elements, particularly heavy metals emanating from ...
Monica M. Cole, Roger F. Smith
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Relationships between percent vegetation cover and vegetation indices

International Journal of Remote Sensing, 1998
In this paper, percent vegetation cover is estimated from vegetation indices using simulated Advanced Very High Resolution Radiometer (AVHRR) data derived from in situ spectral reflectance data. Spectral reflectance measurements were conducted on grasslands in Mongolia and Japan.
TS. Purevdorj   +3 more
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Are vegetation indices useful in the Arctic?

Polar Record, 1998
AbstractThis paper describes a preliminary investigation of the extent to which the normalised difference vegetation index (NDVI), derived from satellite optical imagery, can indicate the extent of damage to upland tundra (fruticose lichen and dwarf shrub) vegetation.
Rees WG, Golubeva EI, Williams M
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Vegetation indices in crop assessments

Remote Sensing of Environment, 1991
Abstract Vegetation indices (VI), such as greenness (GVI), perpendicular (PVI), transformed soil adjusted (TSAVI), and normalized difference (NDVI), measure the photosynthetic size of plant canopies and portend yields. A set of equations, called spectral components analysis (SCA), that interrelates VI or cumulative seasonal VI (∑VI), leaf area index (
C.L. Wiegand   +3 more
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Probability and performance of vegetation indices

spie newsroom, 2007
A vegetation index (VI) is expressed as the ratio of reflectance of an object at the near infrared (x) to its reflectance at the visible red (y) band. It can also be given as a function of this ratio or the ratio of the linear combinations of x and y. VIs are used in mapping vegetation cover with satellite imagery, with high and low values reflecting ...
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Effects of shadows on vegetation indices

IGARSS '96. 1996 International Geoscience and Remote Sensing Symposium, 2002
An important methodology in the remote sensing of biophysical variables is the use of Spectral Vegetation Indices (SVI). An SVI is an algebraic combination of reflectance values from different wavelength bands to produce a single value. Two SVI are evaluated for their usefulness in determining the Fraction of Absorbed Photosynthetically Active ...
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The reliability of vegetation indices for monitoring saltmarsh vegetation cover

International Journal of Remote Sensing, 1997
The dynamic nature of saltmarshes poses a challenge for coastal zone monitoring; natural variability in the sediment reflectance and atmospheric visibility within saltmarsh environment affects the reliability of regression relations between vegetation cover and vegetation indices.
J. A. Eastwood   +3 more
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Vegetation as an Indicator of Geologic Formations

AAPG Bulletin, 1931
Although there are exceptions, plants are commonly found to be as indicative of the formation on which they grow as are the fossils in the rocks. The most important reason for using vegetation is that contacts between formations may be mapped at a distance of several miles, because a decided change in the vegetation is noticeable.
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Vegetation indices for Landsat images

Proceeding of Southwest Symposium on Image Analysis and Interpretation, 2002
Satellite-based remote sensing of vegetation densities is a growing technology with great future potential owing to the proliferation of increasingly sophisticated space-based sensors and the computational tools required to analyze the wealth of data. We explore algorithms that create vegetation mappings from the satellite image data.
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Radar vegetation indices for monitoring surface vegetation: Developments, challenges, and trends

Science of The Total Environment
Monitoring surface vegetation is essential for environmental protection, disaster prevention, and carbon sequestration in forests. However, optical remote-sensing methods and their derivative technologies typically fail to fully meet this requirement due to constraints such as lighting and weather.
Xueqian, Hu   +7 more
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