Spatial Pattern and Temporal Variation Law-Based Multi-Sensor Collaboration Method for Improving Regional Soil Moisture Monitoring Capabilities

Regional soil moisture distributions and changes are critical for agricultural production and environmental modeling. Currently, hundreds of satellite sensors exist with different soil moisture observation capabilities. However, multi-sensor collaborative observation mechanisms for improving regional soil moisture monitoring capabilities are lacking. In this study, a Spatial pattern and Temporal variation law-based Multi-sensor Collaboration (STMC) method is proposed to solve this problem. The first component of the STMC method deduces the regional soil moisture distribution and variation patterns based on time stability theory and long-term statistical analyses. The second component of the STMC method detects potential anomalous soil moisture events and immediately triggers the high spatial resolution sensor with the soonest pass-over time. In the detection phase, an anomalous soil moisture judgment (ASMJ) algorithm and high temporal resolution sensors (the Advanced Microwave Scanning Radiometer 2 (AMSR2)) were utilized. Experiments conducted in Hubei province, China, demonstrated that the proposed STMC method was capable of accurately identifying of anomalous soil moisture conditions caused by waterlogging and drought events. Additionally, we observed that the STMC method combined the advantages of different long-term observation, high temporal, and high spatial resolution sensors synergistically for monitoring purposes. OPEN ACCESS Remote Sens. 2014, 6 12310