With MSN® Virtual Earth™ and Google™ Earth, 3D geospatial data is finding its way into daily life. A digital terrain model (DTM) is one of the most important 3D geospatial data types. One of the key automation technologies in softcopy photogrammetry is to generate a DTM automatically. The most reliable and widely used algorithm for DTM generation is normalized image correlation. However, this algorithm has limitations when dealing with elevation discontinuities such as building edges, because it is based on the assumption that elevation within a window hardly changes.
NGATE, a remarkable innovation invented by GXP’s Dr. Bingcai Zhang, provides automatic generation of DEMs and DSMs and, as far as we can judge from the experiments we have conducted to date, far outperforms ATE. The algorithms behind the NGATE technology are ingenious. NGATE uses both image correlation and edge matching. The edge matching algorithm can deal with building edges or elevation discontinuities well. The results from image correlation are used to constrain and guide the edge matching process. At the same time, the results from edge matching are used to assist image correlation.
We applied NGATE on 66 images (GSD = 0.14 feet = 1.68 inches = 4.3 cm) acquired with a Microsoft UltraCam-D™ digital airborne camera over an urban area. The resulting DTM with 21 million 3D points from NGATE has the following characteristics:
- On natural terrain, the NGATE DTM has an RMS (root mean square) error of 0.4 feet in height
- On streets and parking lots, NGATE DTM has an RMS error of 0.3 feet
- On center points of flat roof buildings, NGATE DTM has an RMS error of 0.5 feet
- On corner points of flat roof buildings, NGATE can capture 94% of corners with an RMS error of 0.9 feet
- On center points, edge points, corner points, and ground points of complex buildings, NGATE DTM has an RMS error of 0.9 feet. 90% of these points have an RMS error of 0.4 feet
- Building edges are well preserved
- Streets are precisely modeled
- Positions and shapes of residential houses are accurately depicted
The above results must be considered in perspective. No editing was conducted prior to the computation of the RMS values. Owing to the design of the flight mission, the parallactic angles subtended by many of the points were small, i.e., not all of the base-height ratios were optimal. And the RMS of 0.9 feet at building corners is impressive given that those are the most challenging points for traditional image matching.
DTMs from NGATE are very dense and accurate — similar to LIDAR data. We have used LIDAR data to extract 3D buildings with encouraging results and we expect that we may achieve similar success with DTM from NGATE as a part of our ongoing research.