NOAA/AVHRR Satellite Data-Based Indices for Monitoring Agricultural Droughts - Monitoring and Predicting Agricultural Drought: A Global Study - page 80

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(Kogan, 1997, 2001, 2002). The indices became indispensable sources of
information in the absence of in situ data, whose measurements and deliv-
ery are affected by telecommunication problems, difficult access to environ-
mentally marginal areas, economic disturbances, and political or military
conflicts. In addition, indices have advantage over in situ data in terms of
better spatial and temporal coverage and faster data availability.
The AVHRR-based indices used for monitoring vegetation can be di-
vided into two groups: two-channel indices, and three-channel indices.
The normalized differences vegetation index (NDVI) is derived from two-
channel data, the visible (VIS, 0.58-0.68

µ m), and near infrared (NIR,

0.72-1.1 µ m) and is defined as NDVI VIS). The

NDVI has been widely used for characterizing distribution of vegetation
(Tarpley et al., 1984; Justice et al., 1985; Tucker and Sellers, 1986; Boken
and Shaykewich, 2002) and for monitoring vegetation conditions (Kogan,
1995). However, this approach is insufficient for monitoring crops specif-
ically during drought periods because crop health depends not only on the
water stress but also on thermal conditions. Therefore, three-channel in-
dices were introduced to monitor impacts of moisture and thermal
stresses on the vegetation conditions.

= (NIR − VIS)/(NIR +

[80],

Line
——
0.0
——
Norm
PgEn

N ew Method and Data

The new numerical method, introduced in the late 1980s, is based on the
combination of VIS, NIR, and thermal (10.3-11.3 µ m) channels (Kogan,
1997, 2001). This method is built on three basic environmental laws: law
of minimum (LOM), law of tolerance (LOT), and the principle of carrying
capacity (CC). The Leibig's LOM postulates that primary production is
proportional to the amount of the most limiting resource contributing to
growth and is at its lowest when one of the factors affecting it is at the
extreme minimum. The Shelford's LOT states that the effect of each envi-
ronmental factor on an organism or ecosystem is maximum or minimum
when the environmental factor ranges between the limits of tolerance. With
regard to these laws, the CC is defined as the maximal population size of a
given species that resources of a habitat can support (Ehrlich et al., 1977;
Orians, 1990).
The new method was applied to the NOAA global vegetation index
(GVI) data set issued routinely since 1985 (Kidwell,1997). The GVI is pro-
duced by sampling the AVHRR-based 4-km (global area coverage format;
GAC) daily radiances in the VIS, NIR, and IR (10.3-11.3 and 11.5-12.5
µ m), which were truncated to 8-bit precision and mapped to a 16-km 2 lat-
itude/longitude grid. To minimize the cloud effects, these maps were com-
posited over a seven-day period by saving radiances for the day that had
the largest difference between NIR and VIS channels.
Because AVHRR-based radiances have both interannual and intra-
annual noise (varying illumination and viewing, sensor degradation, satel-
lite navigation and orbital drift, atmospheric and surface conditions,

[80],