Comparison of Satellite-Derived Land Surface Temperature and Air Temperature from Meteorological Stations on the Pan-Arctic Scale
Abstract
:1. Introduction
2. Data
2.1. Remote Sensing Data
2.1.1. AVHRR Polar Pathfinder Land Surface Temperature
2.1.2. MODIS Land Surface Temperature (MOD11C1, MYD11C1)
2.1.3. Land Surface Temperature from AATSR
2.2. Global Surface Summary of Day Data—Version 7
3. Methodology
- (1)
- Extraction of meteorological stations on pan-arctic scale (above 60 degrees north).
- (2)
- Identification of geographic location of meteorological stations and extraction of data from pixels in remote sensing-based LST products.
- (3)
- Comparison of LST and Tair time series for the whole temporal coverage of each product.
- (4)
- Reduction of both databases to the overlapping time period of the remote sensing products (2000–2005).
- (5)
- Inter-annual comparison of LST and Tair data based on the overlapping time period.
- (6)
- Link of the results to land cover classes extracted for each meteorological stations based on GLC2000 (Global Land Cover 2000).
- The extractions of the meteorological stations, which are situated north of 60 degrees, are done by metadata file, which was provided by the NCDC. This file includes additional information for each station, such as station ID, starting time of acquisition, geographic coordinates, country and measured parameters. This extraction results in over 600 stations suitable for this analysis. After an automated consistency check, identifying missing daily data, the data gaps where filled to create a consistent database. Meteorological stations, which have shown a significant number of missing data, were not used for this study.
- To develop a comprehensive validation database, the geographic coordinates of each of the selected meteorological stations was extracted from the metadata and applied to the remote sensing time series product. Afterwards it was possible to convert the pixel stack from the LST products, which are including each time step, into a single vector. For each meteorological station, a matrix was developed, which included the time, the LST that was based on the remote sensing data, and the Tair values.
- In a first step, the remote sensing-based LST was compared to Tair measurements for the complete time series of each product (Section 4.1). Only daytime temperature information was used in this study. This analysis should give an impression about the agreement between both parameters.
- To derive a detailed insight in the comparison and to assure the comparability of this study, the overlapping period of the remote sensing products (2000–2005) was analyzed (Section 4.2).
- For this time period, the inter-annual variability between LST and Tair were analyzed, using different statistical parameters, such as the Pearson correlation coefficient (R), the slope (S) and the intercept of the regression line (I), as well as the mean difference (MD).
- Prior to the inter-annual variability by comparing LST and Tair time series information, the results were linked to land cover units (Sections 4.3 and 4.4). The goal was to provide information about land cover classes, which are showing the highest variability and discrepancies between remote sensing and ground temperature measurements. The aim was to use the most recent global land cover product GlobCover 2009, developed by ESA [50]. Unfortunately, this classification is not suitable for this analysis, since the land cover class “needle-leaved deciduous forest” (80) does not appear in the final product. The reason for that is that this class needs a seasonal observation from a remote sensing satellite, which was not sufficient for this classification [50]. Thus, the Global Land Cover Classification 2000 (GLC2000), produced by the Joint Research Centre (JRC), was used for this study. This classification is based on satellite data from VEGETATION on SPOT-4 and uses the standardized Land Cover Classification System (LCCS) developed by FAO (Food and Agriculture Organization) as land cover legend [51]. A brief overview of the methodology is shown in Figure 1.
4. Results and Discussion
4.1. Correlation of Remote Sensing-Based LST Estimates with Tair Measurements
4.2. Inter-Annual Variability of LST Estimates for the Time Period between 2000 and 2005
4.3. Comparison of Land Surface Temperature and Air Temperature for Selected Land Cover Classes
4.4. Pan-Arctic Perspective of the Mean Difference for the Time Period of 2000–2005
5. Conclusion and Outlook
Acknowledgments
- Conflict of InterestThe authors declare no conflict of interest.
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Land Cover | AATSR | AVHRR | MOD Terra | MOD Aqua | ø | AATSR | AVHRR | MOD Terra | MOD Aqua | ø |
---|---|---|---|---|---|---|---|---|---|---|
R | Mean Difference | |||||||||
tree, needle, ever | 0.38 | 0.29 | 0.29 | 0.33 | 0.32 | 2.66 | 2.70 | 1.49 | 1.78 | 2.16 |
tree, needle, deci | 0.49 | 0.48 | 0.50 | 0.50 | 0.49 | 1.51 | 1.46 | 1.17 | 1.51 | 1.41 |
tree, mixed | 0.39 | 0.37 | 0.36 | 0.38 | 0.38 | 1.76 | 2.86 | 0.98 | 1.19 | 1.70 |
mos: tree/other veg | 0.46 | 0.42 | 0.43 | 0.45 | 0.44 | 1.44 | 1.59 | 0.82 | 1.21 | 1.26 |
shrub, deciduous | 0.42 | 0.30 | 0.24 | 0.35 | 0.33 | 3.04 | 3.96 | 1.59 | 1.75 | 2.59 |
herbaceous | 0.45 | 0.41 | 0.40 | 0.42 | 0.42 | 3.03 | 3.96 | 1.52 | 1.72 | 2.56 |
sparse herb or shrub | 0.33 | 0.24 | 0.27 | 0.29 | 0.28 | 2.05 | 3.13 | 1.47 | 1.75 | 2.10 |
flood shrub/herb | 0.42 | 0.38 | 0.41 | 0.44 | 0.41 | 2.13 | 1.87 | 1.22 | 1.13 | 1.59 |
water bodies | 0.42 | 0.35 | 0.38 | 0.40 | 0.39 | 2.92 | 3.20 | 1.56 | 1.65 | 2.33 |
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Urban, M.; Eberle, J.; Hüttich, C.; Schmullius, C.; Herold, M. Comparison of Satellite-Derived Land Surface Temperature and Air Temperature from Meteorological Stations on the Pan-Arctic Scale. Remote Sens. 2013, 5, 2348-2367. https://doi.org/10.3390/rs5052348
Urban M, Eberle J, Hüttich C, Schmullius C, Herold M. Comparison of Satellite-Derived Land Surface Temperature and Air Temperature from Meteorological Stations on the Pan-Arctic Scale. Remote Sensing. 2013; 5(5):2348-2367. https://doi.org/10.3390/rs5052348
Chicago/Turabian StyleUrban, Marcel, Jonas Eberle, Christian Hüttich, Christiane Schmullius, and Martin Herold. 2013. "Comparison of Satellite-Derived Land Surface Temperature and Air Temperature from Meteorological Stations on the Pan-Arctic Scale" Remote Sensing 5, no. 5: 2348-2367. https://doi.org/10.3390/rs5052348