High-Resolution Orthorectified Imagery from 1999, Niwot Ridge LTER Green Lakes Valley Project Area, Colorado

The 1:12,000 photos were flown by Rocky Mountain Aerial, the LTER project manager is Don Cline. The Green Lakes Valley orthophoto was produced using 8 black and white photograph stereopair diapositives, flown at 1:12,000 scale in September, 1994 by Rocky Mountain Aerial, Denver, Colorado. Two flightlines were used to create this orthophoto, as there was not enough information in one flightline to include the entire GLV watershed. The diapositives were scanned in using ASIs high resolution drum scanner. An evenly spaced 25-m cellsize DEM was created from dtm.xyz using the outer boundary of the photographs. This DEM was used to register the 1:12,000 stereopairs to the UTM coordinate system with a horizontal location accuracy of 25-m. Once the 1:12,000 photographs were registered and rectified a .5-m cellsize digital orthophoto was produced for the Green Lakes Valley. There were a few problems with orthophoto generation in this area, mostly because of the steep terrain. Firstly, the stereopairs were NOT flown to generate othophotos, they were flown to generate DEMs. Because of this there was not enough overlap for generation of a seamless orthophoto. As the photos were warped to fit a planimetric base, there were a few areas with no data in the middle of the orthophoto. These areas were minimized because of ASIs expertise, but they show up as small black bars in the middle of the orthophoto. There are also some layover problems because of the steep terrain. This is caused by a steep mountain on the edge of the photo that lays over in one direction on one photo and lays over in another direction on the photo beside it. NOTE: This EML metadata file does not contain important geospatial data processing information. Before using any NWT LTER geospatial data read the arcgis metadata XML file in either ISO or FGDC compliant format, using ArcGIS software (ArcCatalog > description), or by viewing the .xml file provided with the geospatial dataset.