## 4 Discussion and Conclusions
NPP is a forest parameter that is difficult to estimate empirically and can be subject to high levels of uncertainty [43; 69; 70]. The average values of Net Primary Productivity estimated from the years 2007-2013 in this study are closely comparable to those reported for similar ecosystems elsewhere [71; 72]. It is possible to observe from that lower values of NPP were located near urban settlements and agricultural fields. This pattern of low NPP values near settlements and human activities suggests that the forests are being degraded (e.g., land cover modifications due to the dynamics of slash-and-burn agriculture) and that this degradation is related directly to human activities. Although NPP estimations are difficult to perform and validate due to lack of field data, programs such the INIFAP's meteorological network that register climatic variables every 15 min, and Eddy covariance towers networks, along with remote sensing data, are promissory elements to support NPP modelling in a reliable way in the Mexican context for the purposes of the REDD+ programme. All human land activities that reduce the current carbon stock in a natural forest and therefore its natural carbon carrying capacity need to be included as the main driving forces and pressures on forest degradation, especially from a climate change perspective [73]. The determination of appropriate threshold values for classifying forest areas into forest degradation is crucial. The evidence has suggested that undisturbed forests can contribute significantly to the establishment of a benchmark that would enable the separation of \"undegraded\" and \"degraded\"forest classes. In the case of AGB, previous studies indicate that higher values of AGB are likely to be encountered in undisturbed natural forests [12; 63; 74]. The procedures used in this study can be updated and implemented with satellite imagery of higher resolution (temporal and spatial), but this may require incurring significant costs. Organizations dedicated to the production of new remote sensing products and tools have developed new satellites sensors with higher spatial resolution, which represent a new age of terrestrial observation and digital mapping that can be applicable for the purposes of programs like REDD+ [75; 76; 77; 78; 79]. The improvements in spatial resolution (pixel size), spectral resolution (number of wavebands), radiometric resolution (sensibility to detect radiation changes) and temporal resolution (data acquisition frequency), in optical remote sensing, bring the possibility of developing improved capabilities for measurement in quasi-real time [7; 28; 80; 81]. These advances can be implemented at both, regional and national scales and may be used for national planning or REDD+ related monitoring verification systems, but also it is worth noting that the exploration of data fusion and the inclusion of active remote sensing data (e.g., Radar and LiDAR) as sources of information are promising research areas. The decision to access the Landsat archive as the main source of satellite imagery was based on considerations of the availability and length of the historical archive and in the confirmed continuity of the program, at least until 2025 with Landsat 9 [17]. Moreover, Europe's Copernicus Earth Observation program includes the Sentinel-2 satellites designed to provide, under a free and open data policy, multiple global acquisitions with similar spectral and spatial characteristics as Landsat, ensuring continuity and a more robust archive to monitoring Earth's surface [28]. Within the REDD+ context, it is necessary to understand and identify the activities that are the drivers and pressures causing forest degradation. Further research on drivers and local activities is needed not only for formulating appropriate REDD+ strategies and policies but also for understanding the causal relationships at play in any given regional context.