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In Situ Soil Moisture Sensors in Undisturbed Soils
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An Extended Kriging Method to Interpolate Near-Surface Soil Moisture Data Measured by Wireless Sensor Networks
Jialin Zhang1,2, Xiuhong Li3,4, Rongjin Yang5
1Center for Global Change Studies, College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China. tozjlmail@163.com.
Sensors (Basel, Switzerland)
|June 16, 2017
Summary
An Extended Kriging method improves soil moisture interpolation by integrating remote sensing data. This new approach enhances spatial detail and accuracy compared to traditional methods, offering better soil moisture mapping.
Area of Science:
- Geosciences
- Remote Sensing
- Environmental Science
Background:
- Accurate soil moisture interpolation is crucial for various environmental applications.
- Traditional methods like Ordinary Kriging (OK), Co-kriging, and Kriging with External Drift (KED) struggle with soil moisture's heterogeneity and low correlation with auxiliary variables.
- Integrating remote sensing data offers potential for improved interpolation accuracy.
Purpose of the Study:
- To develop and evaluate an Extended Kriging method for interpolating near-surface soil moisture using remote sensing data.
- To compare the performance of Extended Kriging against traditional Kriging methods (OK, Co-kriging, KED).
- To assess the method's ability to capture spatial details and improve interpolation accuracy.
Main Methods:
- Developed an Extended Kriging algorithm that operates in a combined spatial and spectral space, incorporating remote sensing spectral variables.
- Applied the Extended Kriging method to wireless sensor network (WSN) soil moisture data from the HiWATER campaign.
- Compared Extended Kriging with OK (WSN data only), Co-kriging, and KED (both using remote sensing covariates).
Main Results:
- Extended Kriging visually demonstrated superior spatial detail in soil moisture interpolation compared to OK, Co-kriging, and KED.
- The Extended Kriging method achieved the lowest Root Mean Square Error (RMSE) among the evaluated methods.
- The results indicate that Extended Kriging effectively combines remote sensing information with ground measurements.
Conclusions:
- The Extended Kriging method offers significant advantages for soil moisture interpolation, particularly in heterogeneous environments.
- Integrating remote sensing data through Extended Kriging enhances the accuracy and spatial representation of soil moisture maps.
- This approach provides a more robust solution for soil moisture estimation compared to traditional Kriging techniques.
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