Data research activities focus on the evaluation of new UAS compatible sensors and development of data processing techniques to take advantage of increased resolutions and accuracy to generate better traditional and new data products to help answer scientific and natural resource questions.
An orthophoto is an undistorted aerial photograph with a completely uniform scale that allows it to function as a map. A significant amount of geometric correction, known as orthorectification, is required to bring about this high level of uniformity. High resolution imagery with ground sample distances of less than six inches can be derived from low-altitude UAS flights using commercial off-the-shelf cameras and computer vision (structure from motion) software.
A unique capability for a camera conversion allows a low-cost method of capturing near-infrared imagery useful for vegetation analysis on low-altitude UAS aerial flights. The camera conversion involves utilizing a notch filter that blocks the low to mid red light range. The result is a camera sensor that detects the red (near infrared edge of the electromagnetic spectrum) centered around 690-720 nm near infrared, green, and blue.
Geographic point clouds are a set of data points in a three-dimensional coordinate system and typically represented as X, Y and Z. Point clouds, which can vary from sparse to dense, can be collected by Light Detection And Ranging (LiDAR) scanners or derived by using photogrammetric (structure from motion) techniques on aerial imagery. Point cloud data is an invaluable resource for a variety of geographic applications that evaluate and monitor landscape change.
Point cloud data overlaid on mosaicked aerial imagery generates realistic natural color 3D models for use in computer simulations, display as a two-dimensional image via 3D rendering, or printing from a 3D printer.
Feature extraction is a method of automating the process of recognizing spectral patterns within an image and outlining or classifying those features into a newly defined dataset. UAS low-altitude flights allow for this to be accomplished on a very large scale with the high resolution images enabling very accurate identification of features.
A unique capability for a camera conversion allows a low-cost method of capturing near-infrared imagery useful for vegetation analysis on low-altitude UAS aerial flights. The conversion involves utilizing a notch filter that blocks the low to mid red light range. The result is a sensor that detects the red (near infrared edge of the electromagnetic spectrum) centered around 710-740 nm, green, and blue. NDVI calculations that create a standardized index utilizing the amount of infrared light that is reflected from a plant and has a strong correlation to the health of the plants imaged. Traditionally the bright red display of the color ramp indicates healthy or highly reflective plants and the blue color indicating the lower reflectivity and possibly less healthy vegetation.
A contour line (or "contour") joins points of equal elevation (height) above a given level, such as mean sea level. A contour map is a map illustrated with contour lines, for example a topographic map, which shows valleys and hills, and the steepness of slopes. The contour interval of a contour map is the difference in elevation between successive contour lines.
A Digital Surface Model (DSM) is a digital cartographic/geographic dataset of reflective surface elevations of horizontal and vertical (xyz) coordinates. The surface elevations for ground positions are sampled at regularly spaced horizontal intervals and can be derived at very high ground resolution when using a low-altitude UAS with standard commercial off-the-shelf cameras. DSM's contain elevations of natural terrain features in addition to vegetation and cultural features such as buildings and roads.
Volumetric calculations begin with the generation of accurate elevation models, traditionally based on data derived from manual on-site measurements, surveying techniques, and photogrammetric methods. Now the introduction of UAS based collection of very high-resolution aerial imagery offers a low-cost option for generating the elevation models needed to support the creation of accurate volumetric measurements.
Keyhole Markup Language (KML) is an XML notation for expressing geographic annotation and visualization within internet-based, two-dimensional maps and three-dimensional Earth browsers. The KML file specifies a set of features (place marks, images, polygons, 3D models, textual descriptions, etc.) for display in Google Earth or any other geospatial software that supports KML encoding.
Creating Normalized Difference Vegetation Index (NDVI) From UAS - Color Infared Imagery Using ENVI 4.8
Creating Normalized Difference Vegetation Index (NDVI) From UAS - Color Infared Imagery Using Fiji ImageJ
Extracting and Inserting EXIF Data on an Image File From UAS Imagery with GPS Coordinates
GOM Media Player Uses a Burst Capture Routine to automatically capture still frame images at set intervals.
Blue Marble Geographics Global Mapper - Viewer/editor capable of displaying the most popular raster, elevation and vector datasets.
ENVI - ENVI uses proven scientific methods and automated processes to help easily extract information from geospatial imagery.
ImageJ - ImageJ is a public domain Java image processing program inspired by NIH Image for the Macintosh. It runs, either as an online applet or as a downloadable application, on any computer with a Java 1.4 or later virtual machine. Downloadable distributions are available for Windows, Mac OS, Mac OS X and Linux.
Exiv2 - Exiv2 is a C++ library and a command line utility to manage image metadata. It provides fast and easy read and write access to the Exif, IPTC and XMP metadata of images in various formats. Exiv2 is available as free software and with a commercial license, and is used in many projects.