Abstract
Abstract. Hyperspectral data has great potential for vegetation parameter retrieval. However, due to angular effects resulting from different sun-surface-sensor geometries, objects might appear differently depending on the position of an object within the field of view of a sensor. Recently, lightweight snapshot cameras have been introduced, which capture hyperspectral information in two spatial and one spectral dimension and can be mounted on unmanned aerial vehicles. This study investigates the influence of the different viewing geometries within an image on the apparent hyperspectral reflection retrieved by these sensors. Additionally, it is evaluated how hyperspectral vegetation indices like the NDVI are effected by the angular effects within a single image and if the viewing geometry influences the apparent heterogeneity with an area of interest. The study is carried out for a barley canopy at booting stage. The results show significant influences of the position of the area of interest within the image. The red region of the spectrum is more influenced by the position than the near infrared. The ability of the NDVI to compensate these effects was limited to the capturing positions close to nadir. The apparent heterogeneity of the area of interest is the highest close to a nadir.
Highlights
Hyperspectral data has been shown to have great potential for the estimation biophysical and biochemical properties of vegetation (Aasen et al, 2014b; Thenkabail et al, 2012; Tilly et al, 2015)
It is evaluated if hyperspectral vegetation indices (VIs), like the NDVI, can compensate the angular effects and if the viewing geometry influences the apparent heterogeneity within an area of interest (AOI)
This study evaluated the influence of angular effects within hyperspectral images of snapshot cameras
Summary
Hyperspectral data has been shown to have great potential for the estimation biophysical and biochemical properties of vegetation (Aasen et al, 2014b; Thenkabail et al, 2012; Tilly et al, 2015). The apparent reflectance within an area of interest (AOI) perceived by a hyperspectral sensing system may differ depending on the viewing geometry, respectively the position of the AOI within the image Such angular effects have been shown to influence the retrieval of plant parameters (Burkart et al, 2015; Verrelst et al, 2008) and data products such as hyperspectral digital surface models (Aasen and Bolten, in review). The scope of this study is to investigate the influence of the different viewing geometries within one hyperspectral image retrieved by a lightweight UAV snapshot camera It is evaluated if hyperspectral vegetation indices (VIs), like the NDVI, can compensate the angular effects and if the viewing geometry influences the apparent heterogeneity within an AOI. The additional spatial dimension brings additional complexity into the data derived by these systems (Aasen et al, 2015, 2014a)
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
