## 5 Conclusions and Prospects  
The aim of this work was to show that it is presently possible to monitor SUHI and its connection with LC changes on a long-term and wide spatio-temporal basis by leveraging the large-scale analysis capabilities of GEE. A general procedure was defined and implemented, thanks to the joint use of GEE and CE, and the indicator _Detrended Rate Matrix_ was introduced to globally represent the net effect of LC changes on SUHI. Figure 21: San Francisco MA: _Detrended Rate Matrix_. Figure 20: San Francisco MA: LC situation in 1992 (**a**) and in 2011 (**b**). In red, the _Urbanized_ class, in light green, the _Cultivated_ class, in dark green, the _Forest_ and _Shrubland_ classes. The procedure was applied to six diverse U.S. MAs, characterized by different climatic conditions and significant urban expansions over the 1992-2011 period. Three main simplifications were introduced in this first application of the proposed procedure to test its feasibility:  
* the spatial analysis was performed at a spatial resolution 10-times lower than the original available information, both regarding LST and LC (a GSD equal to 300 m instead of the original 30-m GSD);
* only three main LC classes were considered, suitably grouping those related to _Urbanized_, _Cultivated_ and _Forest/Shrubland_ areas, which were differently defined in the 1992 and 2011 versions of the USGS NLCD;
* a linear model for the LST temporal evolution was adopted. It is however important to underline that these simplifications are not intrinsic to the procedure and can be released in the future. A starting analysis to tune the procedure was performed on the Atlanta MA. A general LST increase was detected, also for LC stable pixels, which kept their original LC over the whole period 1992-2011; anyway, the quite high estimated increasing rates, in the range 0.29-0.37 \({}^{\circ}\)C/year, appeared unrealistic. Therefore, considering a small portion of the urban area located around a permanent station for air temperature measurement, an extensive comparison was performed between the LST and the air temperature measured at the time of each image acquisition over the period 1992-2011, and a significant inconsistency (0.22 \({}^{\circ}\)C/year for LST vs. 0.08 \({}^{\circ}\)C/year for air temperature) was highlighted. A calibration issue in the LST retrieval procedure from Landsat imagery was supposed to explain such a difference; this was the main reason to introduce the _Detrended Rate Matrix_, in order to eliminate the effect of the biased LST increases and to highlight the net effect of the LC changes on the SUHI. The application of the _Detrended Rate Matrix_ evidenced a strong correlation between the highest increasing LST rates and the transformations from rural to urbanized LC found, common to all the studied ROIs. Hence, the results clearly show how urbanization heavily influences the magnitude of the SUHI effects with significant increases in the LST, up to 0.12 \({}^{\circ}\)C/year, and demonstrate the effectiveness of the proposed methodology, whose real strength lies in its simplicity, ease of use and rapidity, thanks to the GEE computing capabilities. Indeed, it was possible to analyze a huge amount of data (see Table 1) in a short time (few minutes), not even imaginable until recently. Furthermore, the analysis can be easily extended to other urban areas, provided that a sufficient number of Landsat images is available. The present feasibility of the proposed procedure and the encouraging obtained results, although preliminary and requiring further investigations, pave the way for a possible global service on SUHI monitoring, able to provide valuable indications to address an increasingly sustainable urban planning of our cities.