Nature conservation is critical for securing an adequate supplying of environmental services to humans. Paradoxically, financial resources for conservation are normally scarce and, forest ecosystem restoration activities are expensive. So, a careful and detailed planning is vital for optimizing economic funds when ecosystems restoration practices are implemented. In this work, we developed a methodology to find physically-degraded sites in order to determine both, urgency and feasibility to carry out ecological forest restoration activities in the Priority Region for Conservation Xilitla in the state of San Luis Potosí (Mexico). Both, Universal Soil Loss Equation (USLE) and Multi-Criteria Decision Analysis (MCDA) were integrated together by using climatic, soil, remotely-sensed, and proximity data at a 30 m spatial resolution. The results indicated that, more than 80% of the bare soil land in the protected area is under several conditions that lead to feasible ecosystem restoration. This methodology can be further applied to know about the spatial location of soil degraded sites when planning forest restoration practices in natural protected areas.

Fire modifies vegetation dynamics in terrestrial ecosystems. Abundant literature has studied the post-fire effects with satellite sensors; however, relatively fewer studies have used unmanned aerial vehicles (UAVs) to assess the dynamics of greenness prior to and immediately following prescribed fires. Using multispectral sensors mounted on UAVs, we documented the results of the normalized difference vegetation index (NDVI) as a proxy for pre- and post-fire greenness in a natural forest stand in northern Mexico. Using spectral reflectance techniques and the statistical analyses of Kruskal–Wallis and pairwise Wilcoxon rank-sum tests, statistically significant differences were found in the NDVI values, measured before and after controlled burning (p < 0.05). The results showed an increase in post-fire “greenness” from 0.57 to 0.65. This was interpreted as an immediate change in vegetation activity in the canopy, which could be attributable as a stimulus to heat stress. Complementary spectral indices also reinforce our findings; we recognize that further research is required, for instance, to address the timing of image capture. Our findings demonstrate the potential and some of the challenges associated with the use of UAVs to monitor prescribed fires, while also suggesting the need for more detailed physiological and phenological studies. High spatial and spectral resolution maps of greenness represent a valuable starting point for subsequent temporal monitoring and contribute to the knowledge of fire effects at fine spatial resolutions.