## 5 Future Directions  
The improvements in remote sensing data and techniques, and the effort to install and monitor long-term ecological sites are necessary to answer local and regional questions. Integrative analyses are still very restricted, and probably are the next challenge to improve our knowledge of Amazonian.  
Multi-collaborative projects in Amazonia have a successful history on acquiring, documenting, publishing and sharing ecological data. Examples of these programs include the Biological Dynamics of Forest Fragments Project (BDFFP), Center for Tropical Forest Science (CTFS), Tropical Ecology Assessment and Monitoring Initiative (TEAM), the Amazon Forest Inventory Network (RAINFOR), among others. However, due to the unlikely possibility of setting a randomly distributed network of field plots covering the Amazonian landscapes, remote sensing data can play a key role. For example, one step that could be adopted by scientist is the landscape evaluation of the area where they intend to set a new plot/site. Landsat data has proven to be adequate for detecting different forest physiognones in dense Amazonian forests [45, 150, 151], and it has been released free of charge by the National Institute for Space Research (INPE).  
A better documentation and standardization of field data and protocols is also needed. Although field courses, workshops and technical training has been shown to be highly effective, the limited resources requires a better use of the advances in the World Wide Web, such as to improve communication and data sharing (e.g., [152]) or to provide more details on site and data collections (e.g., using the on-line Supporting Information section of scientific journals).  
The temporal scale for monitoring the different components of the Amazonian forests is a key issue for remote sensing data integration. Although for the quantification of above ground biomass, forest growth and recruitment, and changes in species composition can be achieved with inter-census intervals of 2 or more years, the understanding of canopy processes, such as direct observation of leaf -phenotype requires intensives measurements. Monthly images derived from remote sensing datasets showed to detect changes in the canopy of densely vegetated areas of Amazonia, and the validation of these observations are necessary. Despite increasing the costs for setting a plot with monthly measurements, this information is essential for the understanding of how tropical forests are responding to changing environmental factors.  
As drought frequency has been predicted to increase in the Amazon, it is also expected that fires will increase. Techniques, such as the linear un-mixing model have proved adequate to detect burn scars in primary forests. However, the development of a methodology to detect the levels of susceptibility of primary forest to fires would be a great contribution, as it could be used as an \"alert system\" of forest flammability. Nonetheless, to achieve this objective, more research that combines both remote sensing and field measurements over burnt areas are necessary to fully understand the local factors and conditions that triggers the spread of fires and its intensity on primary forests.