With reference to Normalized Difference Vegetation Index, consider the...
• Statement 1 is correct: Normalized Difference Vegetation Index (NDVI) quantifies vegetation by measuring the difference between near-infrared (which vegetation strongly reflects) and red light (which vegetation absorbs). NDVI always ranges from -1 to +1. For example, when the NDVI values are negative, it‘s highly likely that it‘s water. On the other hand, if the NDVI value close to +1, there‘s a high possibility that it‘s dense green leaves. But when NDVI is close to zero, there is not green leaves and it could even be an urbanized area. Overall, NDVI is a standardized way to measure healthy vegetation. When the NDVI values are high, the vegetation can be expected to be healthier vegetation. When you have low NDVI, you have less or no vegetation.
• In particular, there are several sectors that use NDVI. For example, in agriculture, farmers use NDVI for precision farming and to measure biomass. Whereas, in forestry, foresters use NDVI to quantify forest supply and leaf area index. Furthermore, NASA states that NDVI is a good indicator of drought. When water limits vegetation growth, it has a lower relative NDVI and density of vegetation.
• Statement 2 is correct: For both academic and practical purposes, there is the practice of remotely monitoring vegetation in an area and representing it in terms of maps and parameters. One such parameter used is the normalized difference vegetation index (NDVI) which is measured remotely from satellite data. This has been used to estimate the amount of food abundance available to herbivorous animals, for example, elephants. The NDVI is used, for instance, in attempts to track the presence of elephants using the vegetation they consume.
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With reference to Normalized Difference Vegetation Index, consider the...
Normalized Difference Vegetation Index (NDVI)
The Normalized Difference Vegetation Index (NDVI) is a widely used remote sensing technique to assess and monitor the density of vegetation in a particular region. It is derived from the analysis of satellite imagery, specifically by measuring the difference between visible and near-infrared sunlight reflected by the plants.
Statement 1: It measures the density of vegetation in a particular region by measuring the difference between visible and near-infrared sunlight reflected by the plants.
This statement is correct. NDVI is calculated using the following formula:
NDVI = (NIR - Red) / (NIR + Red)
Where NIR represents the near-infrared reflectance and Red represents the red reflectance. The near-infrared light is mainly absorbed by healthy vegetation, while the red light is absorbed by chlorophyll. By comparing the reflectance values of these two spectral bands, NDVI can quantify the amount and health of vegetation in a given area. Higher NDVI values indicate dense and healthy vegetation, while lower values indicate sparse or stressed vegetation.
Statement 2: It is a technique used in tracking the presence of wild elephants.
This statement is incorrect. NDVI is primarily used for assessing vegetation density and health, and it is not specifically designed for tracking the presence of wild elephants. However, NDVI can indirectly help in wildlife monitoring, including the identification of potential habitats for certain species. By analyzing satellite imagery and mapping areas with high NDVI values, conservationists and researchers can identify areas with abundant vegetation that may serve as habitats for elephants or other wildlife.
Conclusion:
In conclusion, statement 1 is correct as NDVI measures the density of vegetation by analyzing the difference between visible and near-infrared sunlight reflected by the plants. However, statement 2 is incorrect as NDVI is not a specific technique used for tracking the presence of wild elephants. Nevertheless, NDVI can indirectly assist in wildlife monitoring and habitat identification.
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