## 5 Data Products, Processing and Distribution
### Data Processing System
#### 5.2.3 Imaging Spectrometer Data  
Pre-processing of the image spectrometer data requires the use of XCAP software (EPIX, Inc., Buffalo Grove, IL, USA) to convert L0 data in a proprietary VIF format to ASCII time stamps and an image cube in standard Band Interleaved by Line (BIL) format. Calibration coefficients (see below) are applied to both the downwelling irradiance data and upwelling imaging spectrometer data to compute at-sensor radiance (Figure 6). Prior to computing at-sensor reflectance, irradiance spectra are resampled spectrally to match the imaging spectrometer. Two reflectance products are computed as part of the workflow: at-sensor reflectance is computed as the fraction of irradiance detected by the imaging spectrometer, and surface reflectance is computed using the radiometric data and an atmospheric correction algorithm. Following the reflectance calculations, data are aggregated from the 1.5 nm native sampling interval using a Gaussian-based spectral resampling procedure to generate a distribution product with uniform 5 nm FWHM band spacing. This is a finer sampling and spectral resolution than is reported for NASA's Next Generation Airborne Visible/Infrared Imaging Spectrometer (AVIRISng) [26] and may be useful for measuring fine spectral features, such as solar  
Figure 11: **(a)** Digital Terrain Model (DTM) and **(b)** Canopy Height Model (CHM) products for a 9 \(\times\) 14 km study area in the Chequamegon-Nicollet National Forest, Park Falls District, WI, USA (5 June 2012; 45.9447\({}^{\circ}\)N 90.2519\({}^{\circ}\)W). The DTM shows lakes, rivers and landforms formed by glacial scouring and transported deposits during the Wisconsin glaciation, and variations in the CHM reflect a diversity of ecosystems and land use management practices.  
induced fluorescence [27]. From the reflectance data, common vegetation indices for greenness (e.g., Normalized Difference Vegetation Index, (NDVI); Enhanced Vegetation Index, (EVI); red edge), light use efficiency (e.g., Photochemical Reflectance Index) and leaf pigments (e.g., carotenoid, anthocyanin) are computed.  
Each pixel in the image cube is georeferenced using Geo-Correction for Airborne Platforms (GCAP) [28], a software package developed at NASA Goddard Space Flight Center that provides the user the capability to georeference a raster image using the image time stamps and GPS-INS data. Pixel coordinates are used to build a geographic lookup table in ENVI that is distributed with the radiance data cube and is used to create georeferenced layers for the reflectance data, vegetation indices and ancillary data products.  
Ancillary data products include valuable information for each pixel of the image cube, including: acquisition time, solar zenith angle, solar azimuth, incoming PAR, cloudiness index [21], aircraft elevation, aircraft altitude AGL, view angle and view azimuth. These time-space variables are computed from the LiDAR-derived DTM and a clear sky irradiance model [29]. The products will help end users create additional higher-order products (e.g., solar and view angles are needed for computing bidirectional corrected reflectance; terrain and canopy heights are needed for orthorectification) and facilitate scientific data analysis (e.g., cloudiness and solar illumination conditions affect canopy photosynthesis).  
Future development will focus on improved co-registration through automated control points and implementing orthorectification and atmospheric correction algorithms specifically designed for low altitude, wide FOV airborne imagers [30].