Estimation of Land Surface Temperature from Chinese ZY1-02E IRS Data
Abstract
:1. Introduction
2. Study Area and Data
2.1. Study Area
2.2. ZY1-02E Data
2.3. MODIS Data
2.4. The ASTER Spectral Library
2.5. ERA5 Atmospheric Profiles
2.6. In Situ Data
3. Methodology
3.1. WVS-Based LST Method
3.2. Land Surface Emissivity Inversion
3.3. Atmospheric Parameter Inversion
3.4. WVS-Based LST Retrieval
- Land surface emissivity retrieval. Firstly, land surface reflectance is retrieved from the ZY1-02E VNIC data using the ERA 5 atmospheric profile from MODTRAN. Then, the NDVI and FVC can be obtained from land surface reflectance data. Subsequently, the land surface emissivity is accurately retrieved based on FVC and NDVI.
- TOA brightness temperature retrieval: The DN values received by the ZY1-02E IRS data are converted into radiance data with the calibration parameters. Subsequently, the TOA radiance is converted into TOA BT using the look-up table between radiance and brightness temperature.
- Adjusted atmospheric parameters: The atmospheric parameters in the ERA5 spatial scale can be calculated using ERA5 profile data from MODTRAN. Then, the atmospheric parameters in the ZY1-02E spatial scale can be estimated using temporal and spatial interpolation. Finally, the WVS method is used to adjust the ZY1-02E atmospheric parameters.
- Based on the adjusted atmospheric parameters and LSE data, the ZY1-02E LST can be inversed using the thermal radiative transfer Equation (2).
4. Results
4.1. LST Results
4.2. Validation
4.2.1. Validation Based on In Situ Data
4.2.2. Cross-Validation Compared to MODIS LST and SST Products
5. Discussion
6. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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No. | Station | Land Cover | Study Area | Longitude (°) | Latitude (°) | Elevation (m) | LSE |
---|---|---|---|---|---|---|---|
1 | Ulansuhai | Water body | Baotou | 108.7706E | 40.8476N | 977 | 0.9869 |
2 | Bare soil | Bare soil | Baotou | 108.8176E | 40.7978N | 977 | 0.9257 |
3 | Kubuqi desert | Desert | Baotou | 108.6203E | 40.4551N | 977 | 0.8836 |
4 | Baotou sand | Sand | Baotou | 109.6187E | 40.8659N | 1296 | 0.9159 |
5 | Baotou Crop | Vegetation | Baotou | 109.5537E | 40.8708N | 1295 | 0.9718 |
6 | Zhangye wetland | Reed wetland | HRB | 100.4464E | 38.9751N | 1460 | 0.9869 |
7 | Desert | Reaumuria desert | HRB | 100.9872E | 42.1135N | 1054 | 0.8836 |
8 | Yantai Sea | Water body | Yantai | 121.4653E | 37.5148N | 0 | 0.9869 |
Bands | Bands No. | Spectral Range (µm) | Resolution (m) | NEDT/SNR |
---|---|---|---|---|
VNIC | Pan | 0.45~0.90 | 2.5 | ≥28 dB@sun altitude angle is 30° and surface reflectance is 0.03 ≥48 dB@sun altitude angle is 70° and surface reflectance is 0.5 |
B1 | 0.45~0.52 | 10 | ||
B2 | 0.52~0.59 | 10 | ||
B3 | 0.63~0.69 | 10 | ||
B4 | 0.77~0.89 | 10 | ||
B5 | 0.40~0.45 | 10 | ||
B6 | 0.59~0.625 | 10 | ||
B7 | 0.705~0.745 | 10 | ||
B8 | 0.860~1.040 | 10 | ||
IRS | B9 | 7~12 | 16 | NEΔT ≤ 0.1 K@300K |
Instrument | Spectral Range (µm) | Operating Environment (°C) | Accuracy | Resolution | FOV (°) |
---|---|---|---|---|---|
SI-111 | 8~14 | −55~80 | ±0.2 K | 0.1 K | 44 |
KT-15 | 9.6~11.5 | 0~55 | ±0.5 K | 0.06 K | 2 |
102 F | 2~16 | 15~35 | 1 cm−1 | 4 cm−1 | 4.8 |
Study Area | Site | Number of Images |
---|---|---|
Baotou | Ulansuhai | 3 |
Baotou | Bare soil | 3 |
Baotou | Kubuqi desert | 3 |
Baotou | Baotou sand | 2 |
Baotou | Baotou Crop | 3 |
HRB | Zhangye wetland | 4 |
HRB | Desert | 3 |
Yantai | Yantai Sea | 5 |
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Dou, X.; Li, K.; Zhang, Q.; Ma, C.; Tang, H.; Liu, X.; Qian, Y.; Chen, J.; Li, J.; Li, Y.; et al. Estimation of Land Surface Temperature from Chinese ZY1-02E IRS Data. Remote Sens. 2024, 16, 383. https://doi.org/10.3390/rs16020383
Dou X, Li K, Zhang Q, Ma C, Tang H, Liu X, Qian Y, Chen J, Li J, Li Y, et al. Estimation of Land Surface Temperature from Chinese ZY1-02E IRS Data. Remote Sensing. 2024; 16(2):383. https://doi.org/10.3390/rs16020383
Chicago/Turabian StyleDou, Xianhui, Kun Li, Qi Zhang, Chenyang Ma, Hongzhao Tang, Xining Liu, Yonggang Qian, Jun Chen, Jinglun Li, Yichao Li, and et al. 2024. "Estimation of Land Surface Temperature from Chinese ZY1-02E IRS Data" Remote Sensing 16, no. 2: 383. https://doi.org/10.3390/rs16020383
APA StyleDou, X., Li, K., Zhang, Q., Ma, C., Tang, H., Liu, X., Qian, Y., Chen, J., Li, J., Li, Y., Wang, T., Wang, F., & Yang, J. (2024). Estimation of Land Surface Temperature from Chinese ZY1-02E IRS Data. Remote Sensing, 16(2), 383. https://doi.org/10.3390/rs16020383