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Figure 5. Relationships between tree density and vegetation
indices (VIs)
3.2 Relationship between vegetation indices and tree
density for the 5x5 maximum filtering algorithm for juniper
A simple linear regression between the conventional vegetation
indices, new TRVI vegetation index and tree density based on
the 5x5 maximum filtering algorithm was calculated. In the
field survey, we observed that plots with few juniper trees had
more ground vegetation, as shown in the significant positive
relationship. Vegetation that is dead or stressed reflects more
red lights and less NIR light. Likewise, non-vegetated surfaces
have much more even reflectance across the light spectrum. In
arid and semi-arid regions, the NDVI is low, particularly in
forests where vegetation cover is sparse compared to the soil
background. The NDVI is sensitive to the optical properties of
the soil background (Baret and Guyot, 1991) (Figure 6).
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Figure 6. Relationships between tree density and vegetation
indices (VIs)
3.3 Relationship between new vegetation index and tree
density for the 5x5 maximum filtering algorithm for both
area
In the arid and semi-arid regions, soil type is very important;
thus, we attempted to reduce the confounding effect of the soil-
vegetation interaction by using optimum window sizes to obtain
spectral values for TRVI. Generally, in arid and semi-arid
regions, the green vegetation index tends to decrease with low-
reflecting soil backgrounds, and the influence of soil
background has been found to seriously hamper the assessment
and characterization of vegetation canopy cover (Huete et al.
1985; Huete and Jackson 1987).The relationship between TRVI
and tree density was positive. TRVI values were generally
higher than the conventional vegetation indices(Figures 7 and
8).
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Figure 7. The relationship between pistachio tree density and
TRVI vegetation index
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