4.3 Article

Evaluation and sensitivity testing of a coupled Landsat-MODIS downscaling method for land surface temperature and vegetation indices in semi-arid regions

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出版社

SPIE-SOC PHOTO-OPTICAL INSTRUMENTATION ENGINEERS
DOI: 10.1117/1.JRS.6.063569

关键词

Landsat; moderate-resolution imaging spectroradiometer; normalized difference vegetation index; land surface temperature; downscaling

资金

  1. NASA Earth System Science Fellowship [NNX07AO53H]
  2. NSF CAREER grant (Hydrologic Sciences) [EAR0846662]
  3. NSF ULTRA-Ex grant [BCS0948914]
  4. Directorate For Geosciences [0846662] Funding Source: National Science Foundation
  5. Division Of Earth Sciences [0846662] Funding Source: National Science Foundation

向作者/读者索取更多资源

The current study investigates a method to provide land surface parameters [i.e., land surface temperature (LST) and normalized difference vegetation index (NDVI)] at a high spatial (similar to 30 and 60 m) and temporal (daily and 8-day) resolution by combining advantages from Landsat and moderate-resolution imaging spectroradiometer (MODIS) satellites. We adopt a previously developed subtraction method that merges the spatial detail of higher-resolution imagery (Landsat) with the temporal change observed in coarser or moderate-resolution imagery (MODIS). Applying the temporal difference between MODIS images observed at two different dates to a higher-resolution Landsat image allows prediction of a combined or fused image (Landsat + MODIS) at a future date. Evaluation of the resultant merged products is undertaken within the Southeastern Arizona region where data is available from a range of flux tower sites. The Landsat + MODIS fused products capture the raw Landsat values and also reflect the MODIS temporal variation. The predicted Landsat + MODIS LST improves mean absolute error around 5 C at the more heterogeneous sites compared to the original satellite products. The fused Landsat + MODIS NDVI product also shows good correlation to ground-based data and is relatively consistent except during the acute (monsoon) growing season. The sensitivity of the fused product relative to temporal gaps in Landsat data appears to be more affected by uncertainty associated with regional precipitation and green-up, than the length of the gap associated with Landsat viewing, suggesting the potential to use a minimal number of original Landsat images during relatively stable land surface and climate conditions. Our extensive validation yields insight on the ability of the proposed method to integrate multiscale platforms and the potential for reducing costs associated with high-resolution satellite systems (e. g., SPOT, QuickBird, IKONOS). (C) 2012 Society of Photo-Optical Instrumentation Engineers (SPIE). [DOI: 10.1117/1.JRS.6.063569]

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