Table 1:
Top of atmosphere reflectance sensor transformation functions (ETM+ to OLI and OLI to ETM+) derived by ordinary least squares (OLS) regression of the data illustrated in Figure 7, reduced major axis (RMA) regression coefficients, the number of 30m pixel values considered (n), the OLS regression coefficient of determination (r2 ), the OLS regression F-test p-value, the mean difference [2], the mean relative difference [4], and the root mean square deviation [3], between the OLI and ETM+ TOA reflectance data.
| Regression type | Between sensor OLS transformation functions and RMA regression coefficients | n | OLS r2 (p-value) | mean difference OLI – ETM+ (reflectance) | mean relative difference OLI – ETM+ (%) | root mean square deviation (reflectance) | |
|---|---|---|---|---|---|---|---|
| Blue λ (∼0.48μm) | RMA | OLI = −0.0029 + 1.0333 ETM+ | 29,697,049 | 0.710 (<0.0001) | 0.0013 | 0.69 | 0.0259 |
| OLS | OLI = 0.0173 + 0.8707 ETM+ | ||||||
| OLS | ETM+ = 0.0219 + 0.8155 OLI | ||||||
| Green λ (∼0.56μm) | RMA | OLI = 0.0014 + 0.9885 ETM+ | 29,726,550 | 0.776 (<0.0001) | 0.0001 | 0.11 | 0.0272 |
| OLS | OLI = 0.0153 + 0.8707 ETM+ | ||||||
| OLS | ETM+ = 0.0128 + 0.8911 OLI | ||||||
| Red λ (∼0.66μm) | RMA | OLI = 0.0009 + 1.0026 ETM+ | 29,678,433 | 0.838 (<0.0001) | 0.0012 | 1.13 | 0.0302 |
| OLS | OLI = 0.0107 + 0.9175 ETM+ | ||||||
| OLS | ETM+ = 0.0128 + 0.9129 OLI | ||||||
| Near infrared λ (∼0.85μm) | RMA | OLI = −0.0058 + 1.1007 ETM+ | 29,767,214 | 0.711 (<0.0001) | 0.0194 | 6.45 | 0.0637 |
| OLS | OLI = 0.0374 + 0.9281 ETM+ | ||||||
| OLS | ETM+ = 0.0438 + 0.7660 OLI | ||||||
| Shortwave infrared λ (∼1.61μm) | RMA | OLI = −0.0001 + 1.0659 ETM+ | 29,725,068 | 0.780 (<0.0001) | 0.0137 | 6.41 | 0.0543 |
| OLS | OLI = 0.0260 + 0.9414 ETM+ | ||||||
| OLS | ETM+ = 0.0246 + 0.8286 OLI | ||||||
| Shortwave infrared λ (∼2.21μm) | RMA | OLI = 0.0048 + 1.0983 ETM+ | 29,237,762 | 0.837 (<0.0001) | 0.0180 | 13.59 | 0.0441 |
| OLS | OLI = 0.0490 + 0.9352 ETM+ | ||||||
| OLS | ETM+ = 0.0075 + 0.8329 OLI |