Scale Effect of Vegetation Index Based Thermal Sharpening: A Simulation Study Based on ASTER Data X.H. Chen a, Y. Yamaguchi a, J. Chen b, Y.S. Shi a a Graduate School of Environmental Studies, Nagoya University, Nagoya, , Japan b State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, , China

Outlines Introduction 1 TsHARP 2 Scale Effect of NDVI-T Relationship 3 Improved TsHARP Method 4 6 Discussion and Conclusion 5

1. INTRODUCTION  Thermal infrared (TIR) band imagery has been widely applied in many studies (e.g. evapotranspiration esitimation; urban heat island; drought monitoring, etc.)  Unfortunately, the spatial resolution of TIR bands is usually coarser than that of visble-near infrared (VNIR) bands  Several thermal sharpening methods have been developed for sharpening spatial resolution of TIR band by using VNIR band

Vegetation Index Based Thermal Sharpening  TsHARP (Kutas et al, 2003) was intensively studied  Negative correlation between NDVI and surface temperature (T)  NDVI-T Relationship established on coarse resolution is applied on fine resolution.  Previous studies found that the spatial resolution does not affect NDVI-T relationship largely;  However, another factor, spatial extent, was largely neglected in the previous studies.  Our study aims to:  Investigate the scale effect of NDVI-T  Improve TsHARP by considering the effect of spatial extent

2. TsHARP  Establish relationship between T and NDVI on the coarse resolution  The regression relationship is applied to the NDVI at their finer resolution (NDVI high ).  Then, the divergence of the retrieved temperatures from the observed temperature field is due to spatial variability in T driven by factors other than vegetation cover, and can be assessed at the coarse resolution  This coarse-resolution residual field is added back into the sharpened map The slope is key parameter for sharpening result

3. SCALE EFFECT OF NDVI-T  3.1 Data  A subset image (256×256 pixels) with 90m resolution of ASTER captured in the grassland in Inner Mongolia, China (44.6ºN, 116.0ºE), on the date of July 16th, 2010, was used for study.  A subset image (256) VNIR bandNDVI Surface Temperature

SCALE EFFECT OF NDVI-T  Two aspects of “Scale”  Spatial Resolution (size of a pixel)  Spatial Extent (size of study area) 90m 720m1440m

NDVI-T Relationship on Different Resolutions  NDVI and T images were resampled to different spatial resolutions (90m to 2880m) by linear aggregation.  Slope ( a ) of NDVI-T on different resolutions were investigated The regressed slope increases slightly with increasing of spatial resolution

 Spatial Extent of m pixels  Original image is divided into N/(m×m) windows.  Average the values of the pixels in each window  Local difference image is derived by subtracting the original image with the averaged image  Regression is conducted on the local difference images of NDVI and T Local Difference Image NDVI-T Relationship on Different Extents

 Regressed slope ( a ) increases with the increasing of spatial extent following a power function  Compared with spatial resolution, spatial extent affects regressed slope more largely. (a) (b) Spatial extent (m)

4. IMPROVED TsHARP  Sharpening T image is equal to retrieving the local difference image of T on extent of a thermal pixel.  The regression relationship should be established on the spatial extent of one thermal pixel Spatial Extent Slope Slope on extent of whole image ( a ) Slope on extent of one thermal pixel ( a local ): Unkown without high resolution T image Slope on extent of 2×2 thermal pixels We use the power function of (spatial extent -regressed slope) to estimate the slope ( a local ) on the extent of one thermal pixel ； Improved TsHARP replaces a with a local

Algorithm Test  T image with 900m resolution was generated.  The coarse T image was sharpened to 90m using TsHARP and improved TsHARP respectively TsHARP (a) Improved TsHARP (a local ) Spatial extent (m) (23040m, 38.1)

Sharpened Result Image sharpened by Improved TsHARP is smoother than that by original TsHARP ℃ (c) TsHARP Improved TsHARP True T image Coarse T image

Accuracy Assessment Improved TsHARP TsHARP Best slope  The best value of slope is around 15.9  Improved method acquired higher sharpening accuracy  Original TsHARP over-sharpens the T image  Actual T image with 90m is used for accuracy assessment

15 5. DISCUSSION and CONCLUSION  Why spatial extent affects the NDVI-T relationship?  Other than NDVI, soil moisture also affects surface temperature. Assuming that  Since NDVI is somehow positively correlated with soil moisture, when T is regressed with only NDVI, the regressed slope becomes (for convenience, we assume the data is standardized)  As spatial pattern of moisture is smoother than NDVI, when spatial extent increases, the correlation between NDVI and Moisture increases, consequently the regressed slope also increases.

Conclusion  Spatial extent is an important factor affecting the NDVI-T relationship, and should not be neglected in the related studies  Improved TsHARP considers the effect of spatial extent and can acquire better sharpening result in this case of study.

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