Topic 1

Title: Identifying Stressed & Potentially Unstable Trees by Aerial Photography on Ohio's Highways
State Job Number: 14613
Final Report, October 2002  (790 KB)
Executive Summary, (53 KB)

Implementation Plan, ( KB) Not available yet

 

Trees are valuable assets and potential liabilities in a man dominated situations such as along Ohio’s highways.  While trees are often long-lived, they must decline and die like any other living thing.  Decline may be nearly instantaneous as in a lightning strike but a major tree normally declines over one to two decades.  The key is to identify declining trees and prune, maintain, or remove them before public safety is compromised.  The primary objective of this study was to begin the process to identify stressed or declining trees using aerial photography.  After stressed or declining trees were identified, cost effective means of automating the process could be developed.  Theoretically, stressed or declining trees can be recognized automatically in multi-spectral/hyper-spectral imagery by analyzing the spectral signatures. This study aimed at obtaining multi-spectral imagery and to test the feasibility of identifying declining trees in a known area (the Shade Tree Evaluation Plot in Wooster, OH).

 

 

Topic 2

Title: High Accuracy Dynamic Highway Mapping Using a GPS/INS System with On-The-Fly (OTF) GPS Ambiguity Resolution
State Job Number: 14661
Final Report, September 2004  (646 KB)
Executive Summary, (26 KB)

Implementation Plan, (79 KB)

 

Conventionally, the road centerline surveys have been performed by the traditional survey methods, providing rather high, even sub-centimeter level of accuracy. The major problem, however, that the Departments of Transportation face, is the safety of the survey crew and the disruptions to the traffic flow, and to a large extent – even inaccessibility of some highways to the surveys crews due to safety hazard. The survey cost also becomes an issue, as due to the traffic and other environmental constraints, these surveys are relatively expensive, while the rate of production is slow, and therefore, frequent updates (re-surveys) are not feasible. This prompted the Ohio Department of Transportation, District 1, to replace the conventional survey by an automated mobile mapping system, which would collect the data while moving at the traffic speeds, ensuring at the same time the safety of the survey personnel.

 

 

Topic 3

Title: High-Accuracy Direct Aerial Platform Orientation with Tightly Coupled GPS/INS System
State Job Number: 14781
Final Report, September 2004  (1,232 KB)
Executive Summary, (19 KB)

Implementation Plan, (561 KB)

 

Obtaining sensor orientation by direct measurements is a rapidly emerging mapping technology. Modern GPS and INS systems allow for the direct determination of platform position and orientation at an unprecedented accuracy. In airborne surveying, aircraft trajectory and platform orientation can be determined at the level of few cm and 20-30 arcsec, respectively at an almost continuous time scale. The use of such integrated GPS/INS systems offers immediate benefits for large-format camera-based airborne surveying by substantially reducing the need for ground control and by basically eliminating aerial-triangulation, except for system calibration. For emerging sensors such as LIDAR, RADAR, multi-/hyper-spectral imagers, however, the use of the direct orientation systems is mandatory since indirect methods such as control point-based aerial-triangulation are not feasible.

 

 

Topic 4

Title: Airborne LIDAR - A New Source of Traffic Flow Data
State Job Number: 134145
Final Report, October 2005  (24,659 KB)
Executive Summary, (111 KB)

Implementation Plan, (520 KB)

LiDAR (or airborne laser scanning) systems became a dominant player in high-precision spatial data acquisition to efficiently create DEM/DSM in the late 90’s. With increasing point density, new systems are now able to support object extraction, such as extracting building and roads, from LiDAR data. The novel concept of this project was to use LiDAR data for traffic flow estimates. In a sense, extracting vehicles over transportation corridors represents the next step in complexity by adding the temporal component to the LiDAR data feature extraction process. The facts are that vehicles are moving at highway speeds and the scanning acquisition mode of the LiDAR certainly poses a serious challenge for the data extraction process. The OSU developed method and it implementation, the I_FLOW program, have demonstrated that LiDAR data contain valuable information to support vehicle extraction, including vehicle grouping and localizations. The classification performance showed strong evidence that the major vehicle categories can be efficiently separated. The I_FLOW program is ready for deployment.

 

 

Topic 5

Title: Geo-Referenced Digital Data Acquisition and Processing System Using LIDAR Technology
State Job Number: 14799
Final Report, February 2006  (98,135 KB)
Executive Summary, (123 KB)

Implementation Plan, ( KB) Not available yet

 

LiDAR technology, introduced in the late 90s, has received wide acceptance in airborne surveying as a leading tool for obtaining high-quality surface data at decimeter-level vertical accuracy in an unprecedented short turnaround time. State-of-the-art LiDAR systems can easily achieve 2-3 cm ranging accuracy, which is certainly the accuracy range required by engineering-scale mapping. However, this is also the accuracy range that cannot be realized by routine navigation-based direct sensor platform orientation. The main objective of the project was to achieve this accuracy as closely as possible and then introduce it into the daily operation of ODOT Office of Aerial Engineering. Several tests confirmed that by using LiDAR specific ground targets, engineering-scale mapping accuracy can be achieved in normal production. The final report presents surface modeling studies, sensor calibration developments, the concept and design of LiDAR specific ground targets; followed by performance validation results, based on test flights performed by the OAE staff and preliminary investigation of image fusion with LiDAR data.