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Global/Regional Change Study
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4. Results and Discussion
The observed NDVI-surface temperature relation displays the expected pattern, with increasing NDVI associated with decreasing surface temperature (e.g. Fig. 1). The satellite estimated air temperatures for the five sites and seven time periods are in general agreement with the ground-measured air temperature values (Fig. 2). The results, however, differ among the sample locations (Table 2). When data for all time periods are considered, the computed coefficient of determination (i) varies from a minimum of .03 at Chiang Mai to 0.81 at Khonkean. The poor results in terms of the value may be attributable to the influence of a limited number of extreme outlying values, most evident at Chiang Mai, Bangkok, and Ranong sites. The RMS differences range from a minimum of 0.7° C to 2.2 oC, suggesting that on average the method provides a reasonably high level of accuracy. The source of the variation requires additional investigation. The outliers are associated with the time of onset of the monsoonal rain period in Thailand, so they potentially reflect the effects of partially cloud contaminated satellite measurements that passed undetected by our cloud screening procedure. If we assume that the outliers do indeed represent artifacts and remove them from consideration, the results for all sites appear consistently good (Table 2). The r2 values then range from .46 to .93, and the RMS difference ranges from
0.4°C to 0.9°C.
Figure 1. Observed relation between NDVI and surface temperature at Bangkok for period of April 11-20,1992. Surface temperature decreases with increasing NDVI. Higher NDVI indicates more vegetation cover. Air temperature is estimated by extrapolation of NDVI through the NDVI value of full vegetation cover, assumed as 0.7.Observed Air Temperature /(C)
Figure. 2. Comparison of satellite estimated air temperature with the observed air temperature for the five sample locations and seven time periods.
Our use 10-day composite NDVI images to represent the mean air temperature conditions for time period requires further consideration. Because the composite procedure selects the maximum NDVI for the 10-day period to minimize cloud effects, the resultant NDVI images may be biased toward the temperature of the clearest day (i.e. highest NDVI). If temperatures vary during the composite period, the variation may not be adequately represented by the NDVI that is retained for the composite. We therefore expect that additional improvements in accuracy would be attained if the analysis is applied at the daily time scale, together with rigorous cloud screening. We are examining this possibility in our current research.
Although additional analysis is required, our initial results suggest that the contextual analysis method for estimating air temperature can be successfully and reliably applied in the seasonal moist tropics, but may depend heavily on the success with which cloud effects can be detected and removed. In our follow-on research we are expanding our analysis to include the surface moisture and atmospheric humidity variables.
Table 2. Validation results for satellite-estimated air temperature. Values in parentheses indicate results with out! in values removed.
| Location |
r2 |
RMS.D iff(0c) |
| Bangkok |
0.04(0.83) |
1.6(0.7) |
| Chiang mai |
0.03(0.93) |
2.2(0.4) |
| Khonkean |
0.81 |
019 |
| Ranong |
0.31(0.60) |
1.1(0.6) |
| Trang |
0.46 |
0.7 |
| All sites |
0.77 |
1.4(0.7) |
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