A vehicle-based laser system for generating high-resolution digital elevation models

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dc.contributor.author Li, Peng
dc.date.accessioned 2010-05-04T19:29:09Z
dc.date.available 2010-05-04T19:29:09Z
dc.date.issued 2010-05-04T19:29:09Z
dc.identifier.uri http://hdl.handle.net/2097/3890
dc.description.abstract Soil surface roughness is a major factor influencing soil erosion by wind and water. Studying surface roughness requires accurate Digital Elevation Model (DEM) data. A vehicle-based laser measurement system was developed to generate high-resolution DEM data. The system consisted of five units: a laser line scanner to measure the surface elevation, a gyroscope sensor to monitor the attitude of the vehicle, a real-time kinematic GPS to provide the geographic positioning, a frame-rail mechanism to support the sensors, and a data-acquisition and control unit. A user interface program was developed to control the laser system and to collect the sensors data through a field laptop. Laboratory experiments were conducted to evaluate the performance of the laser sensor on different type of targets. The results indicated that the laser measurement on a white paper had the least variability than that on other targets. The laser distance measurement was calibrated using the data acquired on the white paper. Static accuracy tests of the gyroscope sensor on a platform that allowed two-axis rotations showed that angle measurement errors observed in combined pitch/roll rotations were larger than those in single rotations. Within ±30° of single rotations, the measurement errors for pitch and roll angles were within 0.8° and 0.4°, respectively. A model to study the effect of attitude measurement error on elevation measurement was also developed. DEM models were created by interpolating the raw laser data using a two-dimensional, three-nearest neighbor, distance-weighted algorithm. The DEM models can be used to identify shapes of different objects. The accuracy of the laser system in elevation measurement was evaluated by comparing the DEM data generated by the laser system for an unknown surface with that generated by a more accurate laser system for the same surface. Within four replications, the highest correlation coefficient between the measured and reference DEMs was 0.9371. The correlation coefficients among the four replications were greater than 0.948. After a median threshold filter and a median filter were applied to the raw laser data before and after the interpolation, respectively, the correlation coefficient between the measured and reference DEMs was improved to 0.954. Correlation coefficients of greater than 0.988 were achieved among the four replications. Grayscale images, which were created from the intensity data provided by the laser scanner, showed the potential to identify crop residues on soil surfaces. Results of an ambient light test indicated that neither sunlight nor fluorescent light affected the elevation measurement of the laser system. A rail vibration test showed that the linear rail slightly titled towards the laser scanner, which caused small variations in the pitch angle. A preliminary test on a bare soil surface was conducted to evaluate the capability of the laser system in measuring the DEM of geo-referenced surfaces. A cross-validation algorithm was developed to remove outliers. The results indicated that the system was capable of providing geo-referenced DEM data. en_US
dc.description.sponsorship U.S. Department of Agriculture; Agricultural Research Service en_US
dc.language.iso en_US en_US
dc.publisher Kansas State University en
dc.subject Digital Elevation Model en_US
dc.subject Surface Roughness en_US
dc.subject Laser Line Scanner en_US
dc.subject AHRS en_US
dc.title A vehicle-based laser system for generating high-resolution digital elevation models en_US
dc.type Dissertation en_US
dc.description.degree Doctor of Philosophy en_US
dc.description.level Doctoral en_US
dc.description.department Department of Biological & Agricultural Engineering en_US
dc.description.advisor Naiqian Zhang en_US
dc.subject.umi Engineering, Agricultural (0539) en_US
dc.subject.umi Engineering, General (0537) en_US
dc.date.published 2010 en_US
dc.date.graduationmonth May en_US

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