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Mapping without the sun
Zhang, Jixian

moisture easily. But in remote sensing society, vegetation
canopy has been the important reasons affecting the sensitivity
of radar backscattering to soil moisture for long time, there is
no empirical model gives good accuracy, especially when
vegetation is dense.
1.3 SMEX02 Experiment
SMEX02 involved microwave remote sensing and in situ
sampling of soil moisture with the major objectives of:
development of models of microwave emission and backscatter
from soil and vegetation; development of soil moisture and
vegetation retrieval algorithms; and validation of airborne and
spacebome remotely sensed soil moisture and vegetation
measurements over a range of spatial scales. In order to satisfy
these objectives, an ideal test site with significant biomass
levels as well as varying soil moisture conditions was needed.
The study site chosen was Walnut Creek, a small watershed in
Iowa. This watershed has been studied extensively by the
USDA and hence was well instrumented for in situ sampling of
hydrologic parameters. The terrain is undulating and the land
cover type for the watershed region is primarily agricultural
with com and soybeans being the major crops. The experiments
were conducted from 25th June through 12th July 2002 during
which the soybean fields grew from essentially bare soils to
vegetation water content of 1-1.5 kg/m 2 , while the cornfields
grew from 2-3 to 4-5 kg/m 2 .
1.4 The PALS Instrument
The passive and active L/S band sensor (PALS) is a
nonscanning real aperture microwave radiometer and radar
operating at 1.41 and 2.69 GHz (radiometer) and 1.26 and 3.15
GHz (radar) with multiple polarizations. The radiometer
operates at V and H polarizations, while the radar operates at
VV, HH, and HV polarizations.
The PALS instrument was flown over the SMEX02 region on
June 25th, 27th, and July 1st, 2nd, 5th, 6th, 7th, and 8th, 2002
(corresponding to day of year, DOY, 176, 178, 182, 183, 186,
187, 188, and 189, respectively). Initial soil conditions were dry,
but scattered thunderstorms occurred on the evenings of July
4th, 5th, and 6th enabling a wetting and subsequent dry down to
be observed. The PALS radiometer and radar provided
simultaneous observations of horizontally and vertically
polarized L- and S-band brightness temperatures, radar
backscatter measured in VV, HH, and VH configurations, and
nadir- and boresight-looking thermal infrared surface
temperature. The instrument was flown on a C-130 aircraft
(velocity f70 m/s) at a nominal altitude of ~3500 ft with the
angle of incidence on the surface being ~ 45°. In this
configuration, the instantaneous 3 dB footprint on the surface
was 330-470 m. The instrument thus sampled a single-line
footprint track along the flight path. Aircraft location and
navigation data were also recorded.
1.5 Landsat TM and In-Situ Database
As part of SMEX02, two Landsat Thematic Mapper (TM)
scenes from Landsat 5 and four Landsat Enhanced Thematic
Mapper plus (ETM+) from Landsat 7 were acquired during the
primary study period. These data were used to produce high
resolution (30 m) NDVI and NDWI data sets. The Landsat TM
images list is shown in Table 1.
An extensive in situ dataset consisting of gravimetric soil
moisture, surface and subsurface temperatures, bulk density,
surface roughness, vegetation water content, crop type, and
radiometer and radar observations were collected over 31 field
sites out of which 21 were cornfields and 10 were soy.
Landsat No
June 6
June 23
July 1
July 8
July 16
July 17
Table. 1 Landsat TM Coverage for SMEX02
For long time, NDVI has been used to estimated VWC with
limited success. The limitation is related to its saturation when
vegetation coverage is dense. NDVI is based on the red and
near-infrared bands, which are located in the strong chlorophyll
absorption region and high reflectance plateau of vegetation
canopies respectively. Therefore, NDVI represents chlorophyll
rather than water content. For Landsat TM/ETM+, /? NIR and
/?re D correspond to bands 4 and 3.
NDVI=(R nir -/? red )/( J?nir + ^red)
Gao 131 developed the Normalized Difference Water
Index(NDWI) for determination of VWC based on physical
NDWI=(/? nir -/? SW i R )/( /'’nir+^swir)
Where R swir is the reflectance or radiance in a short wave
infrared wavelength channel (1.2-2.5 um). For Landsat
TM/ETM+, J? NIR and R S wir correspond to bands 4 and 5. Several
papers [4|t5] has proved that NDWI is superior to NDVI in the
estimating of VWC, because its saturation was observed one-
week lag than NDVI in experiment period. In this part, we
compared VWC derived from NDVI and NDWI, the results
were compared to in-situ measured at SMEX02. Overall, there
are totally 27 samples of VWC for soybean and 48 for com in
SMEX02, and six Landsat images were acquired, as shown in
table 1, Piecewise Cubic Hermite Interpolation was used to
derived daily NDVI and NDWI for the experiment period, the
correlation between NDVI/NDWI and VWC set up by
T.J.Jackson [41 is used: when VWC is predicted by NDWI, the
functions are as follows:
Com: VWC = 9.82 * NDWI + 0.05
Soybean: VWC= 1.44 * NDWI 2 + 1.36 * NDWI + 0.34
When NDVI are used , the functions are:
Com: VWC = 192.64 * NDWI 5 -417.46* NDWI 4 +347.96*
NDWI 3 -138.93* NDWI 2 +30.699* NDWI-
Soybean: VWC= 7.63* NDWI 4 -11.41* NDWI 3 +6.87* NDWI 2 -
1.24* NDWI+0.13
As the results shown in Fig.l, results of estimating VWC from
NDWI has higher correlation and lower RMSE errors in both
soybean and com fields (especially in com fields). A more