532
Multiscale Hydrologic Remote Sensing: Perspectives and Applications
the NMDI match well with MODIS fire products. It thus demonstrates that the
NMDI is not site specific and is expected to be applicable to different areas for
active fire detection. Such a capacity can help monitor large-scale fire hazards and
is therefore useful to carry out regional and global studies.
21.6 CONCLUSIONS
A new developed moisture index, the NMDI, is designed for remote sensing of both
soil and vegetation water content from space by using three channels centered near
0.86, 1.64, and 2.13 µm. The study suggests that the possible range of NMDI values
for soil is between 0 and 1, with higher values indicating increasing soil drought,
while the typical range is from 0.7 to 0.9 for very dry bare soil, 0.3–0.5 for intermediate moisture conditions, and <0.3 for extremely wet soil. For heavily vegetated
areas with LAI ≥ 2, the NMDI takes values ranging from 0.4 to 0.6 for moderate wet vegetations, >0.6 for extremely wet conditions, and <0.4 for dry vegetation.
Therefore, by combining information from multiple NIR and SWIR channels, the
NMDI has enhanced the sensitivity to drought severity and offers the potential for
estimating water content for both soil and vegetations.
Using a 7-year history of the satellite measurements and meteorology data over
Georgia, USA, the capability of the NMDI and other satellite-derived vegetation water
indices for drought monitoring, as well as the connection between fire occurrence
and drought conditions, are investigated. Results show that the drought conditions
indicated by most of the selected indices are consistent with what have been identified
by meteorology data. The NMDI, however, has demonstrated more dependable results
regarding seasonal moisture variations. The seasonal variations of moisture conditions interpreted by the NMDI agree well with LAI change: higher values during the
leaf development stage and lower values in the period of leaf senescence. In addition,
the NMDI exhibits quicker and stronger responses to moisture changes from wet to
dry conditions: the sensitivity of the NMDI to vegetation drought conditions has been
enhanced by an average rate of nearly 10% compared with the other two vegetation
water indices.
The fire frequency and NMDI reveal a strong quasilinear connection with an R 2
>0.9. Higher fire frequencies corresponded to lower NMDI values, and the fire frequency dropped abruptly with the increase of the NMDI. As an effective indicator of
moisture conditions, the NMDI demonstrates the potential for fire risk monitoring.
Since the NMDI derived from MODIS NIR and SWIR channels has a spatial resolution of 500 m, it could provide an effective alternative to traditional meteorology
drought indices such as the PDSI for regional/national drought and fire risk monitoring continuously over time with an improved spatial resolution.
The ability of the NMDI to detect forest fires was investigated by using fires
burning in southern Georgia, USA, and southern Greece in 2007. MODIS fire products were applied for evaluating the fire detection performance. Taking advantage of
information contained in multiple NIR and SWIR channels, the NMDI demonstrated
high overall performance and discrimination power in fire detection. For each test
case, the NMDI has strong signals corresponding to active fires and pinpoints the
active hot spots accurately. The substantially lower NMDI values make the burning
Multiscale Hydrologic Remote Sensing: Perspectives and Applications
the NMDI match well with MODIS fire products. It thus demonstrates that the
NMDI is not site specific and is expected to be applicable to different areas for
active fire detection. Such a capacity can help monitor large-scale fire hazards and
is therefore useful to carry out regional and global studies.
21.6 CONCLUSIONS
A new developed moisture index, the NMDI, is designed for remote sensing of both
soil and vegetation water content from space by using three channels centered near
0.86, 1.64, and 2.13 µm. The study suggests that the possible range of NMDI values
for soil is between 0 and 1, with higher values indicating increasing soil drought,
while the typical range is from 0.7 to 0.9 for very dry bare soil, 0.3–0.5 for intermediate moisture conditions, and <0.3 for extremely wet soil. For heavily vegetated
areas with LAI ≥ 2, the NMDI takes values ranging from 0.4 to 0.6 for moderate wet vegetations, >0.6 for extremely wet conditions, and <0.4 for dry vegetation.
Therefore, by combining information from multiple NIR and SWIR channels, the
NMDI has enhanced the sensitivity to drought severity and offers the potential for
estimating water content for both soil and vegetations.
Using a 7-year history of the satellite measurements and meteorology data over
Georgia, USA, the capability of the NMDI and other satellite-derived vegetation water
indices for drought monitoring, as well as the connection between fire occurrence
and drought conditions, are investigated. Results show that the drought conditions
indicated by most of the selected indices are consistent with what have been identified
by meteorology data. The NMDI, however, has demonstrated more dependable results
regarding seasonal moisture variations. The seasonal variations of moisture conditions interpreted by the NMDI agree well with LAI change: higher values during the
leaf development stage and lower values in the period of leaf senescence. In addition,
the NMDI exhibits quicker and stronger responses to moisture changes from wet to
dry conditions: the sensitivity of the NMDI to vegetation drought conditions has been
enhanced by an average rate of nearly 10% compared with the other two vegetation
water indices.
The fire frequency and NMDI reveal a strong quasilinear connection with an R 2
>0.9. Higher fire frequencies corresponded to lower NMDI values, and the fire frequency dropped abruptly with the increase of the NMDI. As an effective indicator of
moisture conditions, the NMDI demonstrates the potential for fire risk monitoring.
Since the NMDI derived from MODIS NIR and SWIR channels has a spatial resolution of 500 m, it could provide an effective alternative to traditional meteorology
drought indices such as the PDSI for regional/national drought and fire risk monitoring continuously over time with an improved spatial resolution.
The ability of the NMDI to detect forest fires was investigated by using fires
burning in southern Georgia, USA, and southern Greece in 2007. MODIS fire products were applied for evaluating the fire detection performance. Taking advantage of
information contained in multiple NIR and SWIR channels, the NMDI demonstrated
high overall performance and discrimination power in fire detection. For each test
case, the NMDI has strong signals corresponding to active fires and pinpoints the
active hot spots accurately. The substantially lower NMDI values make the burning