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The present work describes a transferability analysis for soil and water bioengineering techniques as an instrument for sustainable erosion control in Central and South America based on an empirical data base from the last decades. In total, 31 case studies in Mexico, Nicaragua, Guatemala, Colombia, Ecuador and Brazil generated a database from an area where soil and water bioengineering techniques are not commonly used. The Transferability Analysis is structured in seven steps: (1) Objectives of the procedure, (2) Impacts of the measure, (3) Identification of up-scaling/down-scaling needs (4) Identification of the main phases and its components, (5) Identification of the level of importance of the components, (6) Assessment of the components in the context of the Take-Up Site and (7) Conclusions. For the assessment of soil and water bioengineering via the Transferability Analysis, in step 4 the following main phases have been identified from the data base: (a) Planning Phase, (b) Construction Phase, (c) Use Phase, as well as (d) End of Life Phase of a construction. Within these categories, 14 components have been defined: (a) know-how of soil and water bioengineering techniques, local climate conditions, botany, hydraulics, pedology; (b) materials, qualified labor, equipment and mechanical instruments, economic resources; (c) monitoring, efficiency, sustainability, maintenance; (d) replicability. The following assessment of the components allowed to determine key barriers, as well as key support factors for the transfer of soil and water bioengineering. As a result, barriers appeared to be the components qualified labor, equipment/mechanical instruments, hydraulics, know-how in soil and water bioengineering and pedology. Neither barriers, nor supporting key factors resulted to be the components local climate conditions, economic resources and efficiency. Supporting key factors for the transfer were materials, monitoring, sustainability, maintenance and replicability. The most important key factor of success was assessed to be botany, as various plant species with important characteristics for soil and water bioengineering are available in Central and South America, able to compensate the constraints through barriers in certain cases.

In wildfire areas, earth observation data is used for the development of fire-severity maps or vegetation recovery to select post-fire measures for erosion control and revegetation. Appropriate vegetation indices for post-fire monitoring vary with vegetation type and climate zone. This study aimed to select the best vegetation indices for post-fire vegetation monitoring using remote sensing and classification methods for the temperate zone in southern Ecuador, as well as to analyze the vegetation’s development in different fire severity classes after a wildfire in September 2019. Random forest classification models were calculated using the fire severity classes (from the Relativized Burn Ratio—RBR) as a dependent variable and 23 multitemporal vegetation indices from 10 Sentinel-2 scenes as descriptive variables. The best vegetation indices to monitor post-fire vegetation recovery in the temperate Andes were found to be the Leaf Chlorophyll Content Index (LCCI) and the Normalized Difference Red-Edge and SWIR2 (NDRESWIR). In the first post-fire year, the vegetation had already recovered to a great extent due to vegetation types with a short life cycle (seasonal grass-species). Increasing index values correlated strongly with increasing fire severity class (fire severity class vs. median LCCI: 0.9997; fire severity class vs. median NDRESWIR: 0.9874). After one year, the vegetations’ vitality in low severity and moderate high severity appeared to be at pre-fire level.