# A New Methodology for Estimating Surface Albedo in Heterogeneous Areas from Satellite Imagery
## 5 Experimental Results  
### Quantitative Evaluation  
The surface albedo results obtained by the three combined strategies are compared to the ABOVE product, which is considered as a reference. This comparison is made through the automation of the image processing by the Matlab(r) 9.3.0.713579 (R2017b) software. The areas and data selected to validate the various strategies combined were the same as in the previous sections. The results of the comparisons are shown in Table 7.  
\begin{table}
\begin{tabular}{c c c c c} \hline
**Classes** & **NDVI** & **Combined 1** & **Combined 2** & **Combined 3** \\ \hline Urban Areas & [\(-\)1.00–0.20) & V03 & V03 & V03 \\ Low Vegetation & [0.20–0.50] & V01 & V02 & V02 \\ High Vegetation & (0.50–1.00] & V03 & V03 & V02 \\ \hline \end{tabular}
\end{table}
Table 6: Combined methodologies proposed, with their criteria for NDVI Evaluation per pixel.  
\begin{table}
\begin{tabular}{c c c c} \hline
**Date** & **Code** & \begin{tabular}{c} **RMSE** \\ **A-Comb1** \\ \end{tabular} & \
\begin{tabular}{c} **RMSE** \\ **A-Comb2** \\ \end{tabular} &
\begin{tabular}{c} **RMSE** \\ **A-Comb3** \\ \end{tabular} \\ \hline
1 November 2015 & FPK & 0.0309 & 0.0377 & 0.0377 \\
13 November 2015 & BND & 0.0461 & 0.0405 & **0.0396** \\
13 October 2014 & FPK & 0.0442 & 0.0533 & 0.0535 \\
13 August 2015 & FPK & 0.0512 & 0.0429 & 0.0428 \\
28 March 2015 & SXF & **0.0607** & 0.0643 & **0.0642** \\
24 September 2013 & FPK & 0.0419 & 0.0436 & 0.0451 \\
13 April 2015 & SXF & **0.0409** & 0.0437 & **0.0425** \\
8 October 2016 & SXF & 0.0696 & 0.0727 & 0.0759 \\
15 November 2016 & BND & 0.0647 & 0.0461 & **0.0447** \\
7 November 2015 & SXF & 0.0530 & 0.0439 & 0.0470 \\
9 November 2016 & SXF & 0.0512 & 0.0457 & 0.0494 \\
25 October 2014 & BND & 0.0602 & 0.0562 & 0.0596 \\
23 May 2016 & BND & 0.0537 & 0.0545 & **0.0515** \\
30 July 2016 & FPK & 0.0333 & 0.0333 & 0.0324 \\
20 April 2016 & PSU & 0.0515 & 0.0546 & **0.0445** \\
25 July 2014 & FPK & **0.0299** & 0.0361 & 0.0360 \\
26 June 2015 & FPK & 0.0431 & 0.0435 & 0.0312 \\
8 June 2016 & BND & 0.0696 & 0.0713 & **0.0560** \\
23 September 2014 & BND & 0.0521 & 0.0534 & 0.0585 \\
14 November 2016 & PSU & 0.0490 & 0.0482 & **0.0429** \\
4 May 2015 & PSU & 0.0700 & 0.0714 & **0.0464** \\
12 September 2016 & BND & 0.0531 & 0.0544 & 0.0443 \\
11 October 2015 & PSU & 0.0374 & 0.0377 & 0.0430 \\
21 October 2013 & PSU & 0.0364 & 0.0368 & 0.0445 \\
21 August 2016 & SXF & **0.0312** & **0.0312** & 0.0440 \\
12 July 2013 & SXF & 0.0564 & 0.0562 & **0.0197** \\
4 September 2013 & BND & 0.0310 & 0.0307 & 0.0399 \\ \hline
**Mean RMSE** & 0.0470 & 0.0469 & **0.0445** \\ \hline \end{tabular}
\end{table}
Table 7: Comparative results between surface albedo ABOVE (A) data and combined methods (Comb1, Comb2, Comb3). The best methodologies for each case study are highlighted in dark green. The second-best methodology is emphasized in light green. The results that have improved with the combined methods with respect to the application of a single methodology are in bold.  
The results of Table 7 show that the combined methods 1 and 2 (Comb1 and Comb2) present very similar results. These results were expected due to the similarity between methods V01 and V02 (Table 6). On the other hand, the combined methodology 3 (Comb3) improves the results of methodologies V01 and V02, decreasing the RMSE in 85% of the cases, while improving it in 52% of the cases with respect to the use of the methodology V03.  
In general, combined method 3 (Comb3) gives better results than combined methods 1 and 2 (Comb1 and Comb2) and improves the outcome of both in 45% of the cases.  
Similarly, and taking into account the results of Tables 5 and 7, it is verified that the combined methodology 3 (Comb3) is the methodology that improves the results of the original methodologies V01, V02, and V03, having the lowest mean RMSE of all the cases studied, with a value of 0.0445.