Vegetated ecosystems have complex three-dimensional (3D) canopy structures with diverse plant type assemblages, crown architectures and historical disturbances. Vegetation structure changes dramatically with strong topographic, edaphic and climate gradients. Airborne lidar remote sensing has the potential to measure fine-scale 3D proprieties of forests with limited temporal and spatial coverage limitations due to prohibitively cost. Here, we present a composite high-resolution airborne lidar dataset covering 7380 km² over the Sierra Nevada, California, that has been calculated from a time-series (2014-2017) collected by the NASA-JPL Airborne Snow Observatory (ASO).

We coherently merge low resolution (~1 pt m^-2) ASO lidar measurements, primarily acquired to quantify snow volume and dynamics, to produce high-resolution point clouds that better describe forest structure and underlying topography (Ferraz et al., 2016). The methodology addresses the removal of lidar points corresponding to snow cover as well as the spatial bias in multi-temporal data due to uncertainties in platform trajectory and motion. We then derived many user-friendly raster products on 3D forest structure (relative heights, plant area index, foliage height diversity), forest functional diversity (richness, evenness, beta diversity) and topographic indexes (topographic wetness index, terrain ruggedness, slope) with spatial resolutions varying from 10 m to 1 km. Our dataset enables the study of landscape-scale studies on a myriad of applications (carbon storage, habitat niche and quality, hydrology, fire hazard and behavior,) over a large region rich in forest types diversity (e.g. alpine, montane, sub-montane forests), with contrasting land uses (e.g. protected vs managed forest) and well documented historical disturbances (e.g. fire). 

      The methods to describe the composite ASO lidar point clouds are descirbed in 

      Ferraz, A., Saatchi, S., Bormann, K.J., Painter, T.H. (2018). Fusion of NASA Airborne Snow Observatory (ASO) Lidar Time Series over Mountain Forest Landscapes. Remote Sensing, 10, 164.

      To methods to produce the raster products on forest 3D structure, underlying topography and forest functional diversity are described in :

      Schneider, F., Ferraz, A., Hancock, S., Duncanson, L., Dubayah, R., Pavlick, R., Schimel, D. (in review). Towards mapping the diversity of canopy structure from space with GEDI. Environmental Research Letters

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