Estimation and Prediction of Soil Moisture from Multi-temporal Radar Measurements Based on the Kalman Filter Technique

利用卡曼濾波器技術由多時序雷達量測來估計與預測土壤溼度

曾裕強(Y. C. Tzeng) ； 朱得銘(D. M. Chu)

《航測及遙測學刊》 11卷2期 (2006/06) Pp. 127-141

https://doi.org/10.6574/JPRS.2006.11(2).2

摘要

監測土壤溼度的變化，對許多應用而言是非常重要的。研究結果顯示，以雷達量測來對映土壤表面溼度具有極大的潛力。利用溼度變化在時間上的相關性，吾人可預期土壤溼度的估計與預測是可以達到一相當的準確度。此一時間上的相關性經過適當的模式化後，可藉由卡曼濾波器的理論將其納入。同時運用卡曼濾波器的兩個方程式，亦即處理方程式與量測方程式，可以由雷達量測來估計土壤溼度及預測土壤溼度在時間上的變化。土壤溼度與雷達散射係數間的對映關係是以量測方程式來表示，而土壤溼度在時序上漸乾或漸濕的狀態變化則以處理方程式來表示。本研究以裸露土之土壤溼度及其雷達散射係數的數值模擬來驗證此一方法之有效性。模擬結果顯示若土壤漸乾或漸濕的變化可更準確地模式化，應可改善多時序土壤溼度預測的準確度。

關鍵字

土壤溼度 ； 卡曼濾波器 ； 雷達散射係數

並列摘要

Monitoring soil moisture changes is of importance in many applications. Studies show that radar has great potential to provide useful near surface moisture mapping. By making use of the temporal correlation of the moisture changes, estimation and prediction might be achieved with satisfying accuracy. The temporal effects, when appropriately modeled, can be taken into account by means of the Kalman filter theory. The two equations in the Kalman filter, namely, process equation and measurement equation, are used simultaneously to estimate moisture content from radar measurements and to predict the moisture changes over time. The relationship of the moisture content and radar scattering coefficient is built into the measurement equation, while the dry-up (or wet-down) of soil moisture in multi-temporal states was modeled into the process equation. Validation of the presented approach is verified through numerical simulations of radar measurements over the bare soil surfaces. Simulation results indicate that the estimation and prediction of the mutli-temporal moisture content can be improved when the dry-up or wet-down process is properly modeled.

並列關鍵字

soil moisture ； Kalman filter ； radar scattering coefficient