We live in an era of unprecedented environmental change, with extensive degraded landscapes and great opportunities to transform these unproductive lands in functional landscapes and restore ecosystems that provide multiple benefits to society and future generations from processes such as the Forest Landscape Restoration (FLR), seeking the restoration of forests along with food production, carbon sequestration, soil and water protection and conservation of biodiversity, providing a good quality of life for people living in these landscapes. To meet these ambitious processes is necessary to adopt a rich concept of "Forest", performing a structural previous survey the landscape, distinguishing forest types (natural or planted, native or exotic species, continuous or fragmented among others) for the monitoring and success activity. However, perform the measurement of structural attributes in the field, able to distinguish these types, it is unworkable and some remote passive sensors have low accuracy in tropical forest classification due to high rates of leaf area. Active remote sensing, LiDAR, produce three-dimensional images of the landscape enabling direct or indirect estimate important structural physical attributes of vegetation with high accuracy. The objective of this study is to evaluate what are the opportunities that LiDAR has to monitor landscape restoration programs in tropical forests with the distinction of forest types, biomass estimates and biodiversity.
News published in Agência FAPESP Newsletter about the scholarship: