## 3 Results
As Landsat 8 was launched on an Atlas-V rocket in February 2013, there are no available data before 2013. Landsat 8-9 is a 30 m resolution image. Figure 5 shows the spatial distribution for LST within the CRW. In 2015 and 2017, LST had the highest values out of all the years studied, and the spatial distribution for LST was not available. Figure 4: Correlation between land surface temperature and the normalized difference vegetation index. Figure 3: Spatial distribution of NDVI estimated from MOD13Q1 between 2012 and 2022. Data for MOD17A2 (GPP) were not available for 2012 and 2022.  
yet in 2015, there was an extreme drought. Additionally, in 2017, Hurricane Maria caused bare land or a major lack of vegetation. Land surface temperature presented high values in 2017 after Hurricane Maria due to the lack of vegetation. This agrees with a study presented by [PERSON] [25], where it is mentioned that soil that is exposed to radiation reflects part of it and retains the rest, which increases the soil's temperature. This would also be the case for 2015, but it remained this way for a longer period due to a lack of water. For 2020, there is some discrepancy between data from September 28 and the data used to substitute clouds, which were taken from October to November. LST and ET daily values are compared on the scatterplot graph in Figure 6. In this case, as daily data are being observed, the correlation is not as clear as in the previous one. Nevertheless, it is suggested that, on that day, most of the evapotranspiration occurred at higher temperatures. At higher temperatures, it is usually noted that plants will transpire more, and a greater amount of water will evaporate. These standards may have not applied in 2015 because it is noted that ET, NDVI, and GPP are more responsive to precipitation, which was null during this timeframe. MOD16A2 products have fill values. These are values from 32,761 through 32,767, and it is recommended they are disregarded. When excluding these values, the data sets from 2015 to 2022 lost most of their data. Therefore, lost data had to be replaced for this study. To accomplish this, we used data values from 2012 to 2022 from GOES-PRWEB. From each dataset, 85 points were extracted and integrated into our MOD16A2 raster. We then proceeded to complete the MODIS products' missing information (Figure 7) using inverse distance weighted interpolation (IDW). IDW interpolation from GOES-PR underestimated the values of actual ET in comparison with that obtained from MODIS. It is to be considered that the points further away from the interpolated data will not be as reliable as the points closer to the fishnet points. Therefore, values obtained from GOES-PR were not used to create correlation graphs or matrices. Figure 5: Spatial distribution for LST\({}_{Corrected}\) estimated from Landsat 8–9 OLI-TIRS between 2013 and 2022. Evapotranspiration is directly related to plant maturity and amount. Therefore, it is expected that an increase in ET will be related to an increase in NDVI values (Figure 8). Compared with other years, in 2017, ET and NDVI were at their lowest values due to Hurricane Maria. Although NDVI responds well to moderate or extreme wet events, Hurricane Maria's main impact on the island was from its strong winds. Nevertheless, the trend between 2017 and other years tends to be the same, where an increase in NDVI will cause an increase in ET, and vice versa. Figure 6: Correlation between land surface temperature and actual evapotranspiration for 2015. Figure 7: Spatial distribution of ET estimated from MOD16A2 between 2012 and 2022. In Figure 9, the correlation between GPP and ET is positive. A positive trend means that an increase in GPP will produce an increase in ET, and vice versa. For GPP, production values of 3276.19 g/C/day were not taken into consideration, as these values are nonterrestrial fill value classes. In this case, these values' land cover was assigned as urban/built-up. Figure 10 shows the spatial distribution of GPP from 2012 to 2021.