Monitoring Agricultural Drought in China - Monitoring and Predicting Agricultural Drought: A Global Study - page 361

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Table 28.2 The categories of drought

Grade W / W f Crop water satisfaction index

Heavy drought < 0.4 > 0.913

Dry 0.41-0.50 0.765-0.913

Light dry 0.51-0.60 0.617-0.764

Normal 0.61-0.80 0.322-0.616

Moist > 0.81 < 0.321

Source: Yao (1990).

N ormalized Difference Water Index

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The spectral signature of vegetation canopy at 1.55-1.75 µ m waveband
is sensitive to water content in the canopy. Remotely sensed data at the
shortwave infrared can be used to monitor water content of vegetation
canopy. A normalized difference water index (NDWI) was developed to
monitor drought during the cropping season (Tian et al., 2002):

Line
——
1.4
——
Shor
PgEn

P SW − P R

NDWI = [28.12]

P SW + P R

where P SW is the reflectance at shortwave infrared (e.g., 1.55-1.75 µ m),
and P R is the reflectance at red band (0.61-0.68 µ m). The NDWI is corre-
lated with soil moisture (Tian et al., 2002) at root zone and therefore can
be used to monitor drought conditions in crops.

[361

A nomalous NDVI Model

The anomalous NDVI (Chen, et al., 1994) can also be used to monitor
drought conditions:

NDVI NDVI

NDVI

−

ANDVI = [28.13]

where NDVI is th e nor malized difference vegetation index based on
AVHHR data, and NDVI is an NDVI averaged for multiple (more than
10) years.

C ombination Model

The combination model (CM) is defined as

NDVI
T S

CM = [28.14]

where T S is surface temperature that can be derived from channel 4 and
channel 5 data of the AVHHR thermal data (Xin et al., 2003).