DVI (Difference Vegetation Index)
Definition
The Difference Vegetation Index (DVI) is one of the simplest and earliest vegetation indices, calculated as the arithmetic difference between near-infrared (NIR) and red reflectance. It directly measures the contrast between high NIR reflectance and low red reflectance characteristic of healthy green vegetation, without normalization.
Application
DVI is used for basic vegetation detection, change monitoring, and as a component in more complex indices. It remains valuable for historical data analysis (e.g., with early Landsat sensors), for monitoring very high biomass systems where ratio indices saturate, and in educational contexts to demonstrate fundamental vegetation spectral properties.
FAQ
What is the formula for DVI and what is its typical range?
DVI = NIR - Red. Unlike normalized indices, DVI has no fixed range; values depend on sensor calibration and surface conditions. Typically, healthy vegetation yields positive values (often 0.1-0.4 in reflectance units), bare soil gives values near zero, and water bodies can yield negative values.
How does DVI compare to NDVI in terms of sensitivity and saturation?
DVI differs significantly:
1) DVI shows linear response to increasing leaf area index (LAI) over a wider range, while NDVI tends to saturate at moderate to high LAI;
2) DVI is more sensitive to absolute changes in reflectance but also more affected by extraneous factors like illumination changes;
3) DVI values are not bounded, making cross-scene comparisons difficult without normalization.
What are the main advantages of using DVI despite its simplicity?
Advantages include:
1) No saturation at high biomass, making it useful for dense forests or mature crops;
2) Simplicity and computational efficiency;
3) Historical continuity with early remote sensing data;
4) Direct physical interpretation as the "depth" of the chlorophyll absorption feature.
What are the primary drawbacks that limit DVI's widespread use?
Primary drawbacks include:
1) High sensitivity to atmospheric scattering and absorption (no atmospheric correction);
2) Strong influence from soil background brightness, especially in sparse vegetation;
3) Dependence on absolute calibration and illumination conditions;
4) Lack of standardized scaling, requiring scene-specific thresholds for vegetation classification.
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