Land surface temperature retrieval from AMSR-E passive microwave data

Area of Science:

• Earth Science
• Remote Sensing
• Climate Science

Background:

• Land surface temperature (LST) is crucial for understanding energy balance, evapotranspiration, and climate change.
• Accurate LST retrieval is essential for various environmental and climate studies.

Purpose of the Study:

• To develop and evaluate two novel methods for LST retrieval using passive microwave data.
• To compare the performance of these new methods against a traditional multi-channel approach.

Main Methods:

• Method 1: LST retrieval using single-channel, dual-polarized data and the microwave polarization difference index (MPDI).
• Method 3: LST retrieval using multi-channel data with prior knowledge of the normalized difference vegetation index (NDVI).
• Method 2: Traditional multi-channel LST retrieval for comparison.

Main Results:

• Method 3 demonstrated the smallest root mean square errors (RMSEs) for LST retrieval, ranging from 2.92 K to 3.44 K.
• Method 2 showed RMSEs between 3.07 K and 4.05 K.
• Method 1 yielded the highest RMSEs, ranging from 3.11 K to 4.13 K at 89 GHz.

Conclusions:

• The integration of NDVI in Method 3 significantly enhances LST retrieval accuracy by providing crucial emissivity information.
• Vegetation characteristics play a vital role in improving emissivity estimation for more precise LST.
• Method 3 represents a promising advancement for accurate LST determination from passive microwave data.