Soil Moisture 101: Satellite-based Remote Sensing of Soil Moisture

Summary

In his presentation, John Bolton, a research scientist at NASA Goddard Space Flight Center, discusses the significance of satellite-based remote sensing for monitoring soil moisture. He highlights NASA's Soil Moisture Active Passive (SMAP) mission, launched in 2015, and the integration of passive and active sensing technologies to enhance soil moisture data accuracy. Bolton emphasizes the value of combining satellite observations with in-situ measurements to improve agricultural productivity, flood forecasting, and climate models. The talk concludes with exciting prospects for future missions, including a collaboration with the Indian Space Agency for enhanced soil moisture mapping.

Takeaways

• 🌍 NASA's Soil Moisture Active Passive (SMAP) mission, launched in 2015, focuses on satellite-based observations of soil moisture.
• 📡 There are two main remote sensing approaches: passive (measuring thermal emissions) and active (using radar technology).
• 🔄 Remote sensing offers a global perspective with frequent revisit times, enhancing understanding of the hydrologic cycle.
• 📈 The goal is to combine satellite and in situ observations to create a long-term, consistent data record for soil moisture analysis.
• 🔍 The SMAP mission aims for high-resolution soil moisture mapping with a target accuracy of 4% and sensing depth of 0-5 cm.
• 🤝 NASA collaborates with the Indian Space Agency on the NISAR mission, which will provide higher resolution data every 12 days.
• 🌱 Integrating satellite data with in situ measurements improves agricultural monitoring and crop productivity assessments.
• 🚨 Soil moisture data plays a crucial role in flood and drought forecasting, aiding in environmental management.
• 🔥 Remote sensing can be used to assess fire risk by correlating soil moisture anomalies with satellite-observed fire counts.
• 📊 The use of data assimilation systems enhances the accuracy and reliability of soil moisture models through combined observations.

Q & A

What is the main focus of John Bolton's discussion?

John Bolton discusses satellite-based remote sensing of soil moisture and its integration with in-situ observations.

What does SMAP stand for and what is its significance?

SMAP stands for Soil Moisture Active Passive mission, which is NASA's key satellite mission launched in 2015 to observe soil moisture globally.

How many Earth observing satellites does NASA have, and what do they monitor?

NASA has over 18 Earth observing satellites that monitor various components of the water, energy, and carbon cycles.

What are the two main approaches to soil moisture remote sensing mentioned?

The two main approaches are passive remote sensing, which measures thermal emissions, and active remote sensing, which uses radar to capture backscatter signals.

What are the advantages of satellite-based remote sensing?

Satellite-based remote sensing provides a global perspective with frequent revisit times, improving understanding of the hydrologic cycle and enabling applications in agriculture and environmental monitoring.

What is the target accuracy and sensing depth for the SMAP mission?

The SMAP mission aims for an accuracy of 4% soil moisture with a sensing depth of 0 to 5 centimeters.

What is the partnership between NASA and the Indian Space Agency about?

NASA is partnering with the Indian Space Agency for the NISAR soil moisture mission, planned for launch in 2023, which will offer higher resolution measurements.

How does NASA combine ground-based and satellite observations?

NASA combines ground-based measurements with satellite observations using data assimilation techniques to enhance the accuracy and coverage of soil moisture data.

What is the purpose of the Dynamic Agriculture and Productivity Index (DAPPY)?

DAPPY aims to provide enhanced agricultural monitoring by integrating satellite data with agronomic information.

What innovative approach has been used to improve spatial resolution of soil moisture products?

Researchers have used thermal inertia relationships between surface temperature changes and averaged soil moisture to create higher resolution products, leveraging long-term historical data.