The Wireless Sensor Networks of Coarse-resolution Pixel Parameters (CPP-WSN) was established to monitor the heterogeneity of coarse spatial resolution pixel, with consideration of different categories of land surface parameters in Huailai, Hebei province, China (40.349°N, 115.785°E). The observation network of radiation parameters (RadNet) in CPP-WSN was developed for multi-band radiation measurement and consisted of 6 nodes covering 2km*2km area to capture its heterogeneity. Each node employed four sensors to observe the five radiation parameters. The number and location of nodes in RadNet were determined through the representativeness-based sampling method. Thus, the RadNet is a distributed observation system with nodes work synchronously and measurements used together.
The intercomparison experiment for RadNet is necessary and was conducted in Huailai Remote Sensing Station from 5th Aug to 10th Aug in 2012. Time series observations from various sensors were collected and analyzed. The maximum relative differences among sensors of UVR, SWR, LWR, PAR, and LST are 4.83%, 5.3%, 3.71%, 11%, and 0.54%, respectively. Sensor/parameter differences indeed exist and are considerable large for PAR, SWR, UVR, and LWR, which cannot be ignored. The linear normalization and quadratic polynomial normalization perform similar for CUV5/UVR, PQS1/PAR, CNR4/SWR, and SI-111/LST. As for CNR4/LWR, quadratic polynomial normalization show higher accuracy than linear normalization, especially in node2, node4, and node5. Thus, the LWR measured by CNR4 is proved to be nonlinear, and should be normalized with quadratic polynomial coefficients for higher precision.
The evaluation of uncertainty in satellite-derived albedo products is critical to ensure their accuracy, stability and
consistency for studying climate change. In this study, we assess the Moderate-resolution Imaging
Spectroradiometer(MODIS) albedo 8 day standard product MOD43B3 using the ground-based albedometer
measurement based on the wireless sensor network (WSN) technology.
The experiment have been performed in Huailai, Hubei province. A 1.5 km*2 km area are selected as study region,
which locates between 115.78° E-115.80° E and 40.35° N-40.37° N. This area is characterized by its distinct landscapes:
bare ground between January and April, corn from May to Octorber. That is, this area is relatively homegeneous from
January to Octorber, but in Novermber and December, the surface is very heterogeneous because of straw burning, as
well as snow fall and snow melting.
It is a big challenge to validate the MODIS albedo products because of the vast difference in spatial resolution between
ground measurement and satellite measurement. Here, we use the HJ albedo products as the bridge that link the ground
measurement with satellite data. Firstly, we analyses the spatial representativeness of the WSN site under green-up,
dormant and snow covered situations to decide whether direct comparison between ground-based measurement and
MODIS albedo can be made. The semivariogram is used here to describe the ground hetergeneity around the WSN site.
In addition, the bias between the average albedo of the certain neighborhood centered at the WSN site and the center
pixel albedo is also calculated.Then we compare the MOD43B3 value with the ground-based value. Result shows that
MOD43B3 agree with in situ well during the growing season, however, there are relatively large difference between
ground albedos and MCD43B3 albedos during dormant and snow-coverd periods.
Land surface temperature (LST) is an important parameter that modulates land surface process. The
combination of infrared temperature and microwave temperature is a trend in the research of LST.
Thermal infrared temperature and microwave temperature have different physical significances and
values. However, they are always treated as the same temperature nowadays in the research on the
combination of infrared temperature and microwave temperature. In this study, the homogeneous
canopy is the leaf-dominated crown layer ignoring the effect of branches. Two layers with different
temperature, the canopy layer and the soil layer, are considered. MESCAM model based on matrix
doubling method has been modified by getting rid of the effects of the main and secondary stems.
The effect of multiple scattering at L and C band has been studied by comparing the results of taoomiga
model with that of the modified MESCAM model. Tao-omiga model was adopted to compute
the canopy brightness temperature at L band and a simple geometric-optical model basing on gap
probabilities was used to compute the canopy brightness temperature at thermal infrared band in the
same scene. The relationship and the difference between thermal infrared canopy surface physical
temperature and L band canopy effective physical temperature with different soil moisture have
been analyzed in three different situations of TC (the temperature of the foliage component) and TS
(the temperature of the soil component). It is a base of further exploring the cooperative inversion
combining thermal infrared remote sensing with passive microwave remote sensing.
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