Abstract
The eco-hydrological wireless sensor network (EHWSN) in the middle reaches of the Heihe River Basin in China is designed to capture the spatial and temporal variability and to estimate the ground truth for validating the remote sensing productions. However, there is no available prior information about a target variable. To meet both requirements, a hybrid model-based sampling method without any spatial autocorrelation assumptions is developed to optimize the distribution of EHWSN nodes based on geostatistics. This hybrid model incorporates two sub-criteria: one for the variogram modeling to represent the variability, another for improving the spatial prediction to evaluate remote sensing productions. The reasonability of the optimized EHWSN is validated from representativeness, the variogram modeling and the spatial accuracy through using 15 types of simulation fields generated with the unconditional geostatistical stochastic simulation. The sampling design shows good representativeness; variograms estimated by samples have less than 3% mean error relative to true variograms. Then, fields at multiple scales are predicted. As the scale increases, estimated fields have higher similarities to simulation fields at block sizes exceeding 240 m. The validations prove that this hybrid sampling method is effective for both objectives when we do not know the characteristics of an optimized variables.
Highlights
Sensor networks, one of important components of Global Earth Observation System of Systems [1], promote the advancement of Earth system science and environmental science [2]
EP represents a method that is effective for estimating variogram parameters, and SP is a method that is good for spatial prediction
A hybrid sampling method is proposed to optimize samples for both spatial estimation and spatial interpolation when there is lack of prior information on the target variable. This hybrid method is used to optimally design the eco-hydrological wireless sensor network (EHWSN) in the HeiheRiver Basin (HRB), and its effectiveness has been verified in terms of representativeness, parameter estimation and prediction accuracy, using various simulation fields
Summary
One of important components of Global Earth Observation System of Systems [1], promote the advancement of Earth system science and environmental science [2]. With the development of international water science, the NSFC (National Nature Science Foundation of China) launched the Heihe Plan entitled “Integrated research on eco-hydrological process of the Heihe. Program is the observation platform of the Heihe Plan, and the eco-hydrological wireless sensor network (EHWSN) is one of the fundamental experiments of HiWATER [7]. The EHWSN provides indispensable observations that allow HiWATER to address problems that include heterogeneity, scaling and uncertainty. To solve these problems, EHWSN is required to capture the spatial variability and temporal dynamics of soil moisture and temperature and to provide accurate ground-truth estimates at remote sensing pixel scales [8].
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